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A survey of surface mount device placement machine optimisation: Machine classification
Abstract
The optimisation of a printed circuit board assembly line is mainly influenced by the constraints of the surface mount device (SMD) placement machine and the characteristics of the production environment. This paper surveys the characteristics of the various machine technologies and classifies them into five categories (dual-delivery, multi-station, turret-type, multi-head and sequential pick-and-place), based on their specifications and operational methods. Using this classification, we associate the machine technologies with heuristic methods and discuss the scheduling issues of each category of machine. We see the main contribution of this work as providing a classification for SMD placement machines and to survey the heuristics that have been used on different machines. We hope that this will guide other researchers so that they can subsequently use the classification or heuristics, or even design new heuristics that are more appropriate to the machine under consideration.
... Differently, the SMT can directly attach a component on the surface of a PCB [1]. Various kinds of SMT machines have been used in industry, including sequential pick-and-place, multihead, dual-delivery, turret type, multi-station, and concurrent pick-and-place [2,3]. This research focuses on the kind of multi-head gantry SMT machine. ...
... The total NC time is defined by Eq. (2). ...
... Specifically, the first stage focuses on determining the best assembly path for assembly heads and feeder assignments for components; the second stage assigns nozzles to assembly heads to best support the fulfillment of the planning results obtained from the first stage. (2) In the problem sizes of 20 × 1 × 12 × 12, 40 × 1 × 12 × 12, 80 × 1 × 12 × 12, and 160 × 1 × 12 × 12, the IFA + DP outperforms the other hybrid approaches in terms of total assembly time while the WOA + DP has a consistent performance of second-best. (3) In the extensive experiments, the PSO + DP, GA + DP, and FA + DP are consistently inferior to the IFA + DP and WOA + DP in terms of total assembly time. ...
This paper proposes a two-stage framework for developing hybrid approaches to solve the three printed circuit board assembly (PCBA) problems, component sequencing problem (CSP), feeder assignment problem (FAP), and nozzle assignment problem (NAP), simultaneously for a multi-head gantry SMT (surface-mounting technology) machine. The three essential PCBA problems affect the productivity of a multi-head gantry SMT machine considerably. However, due to the difficulty and complexity, the NAP (which assigns a given set of nozzles to the assembly heads of a machine) has been often neglected or roughly resolved in past research. The lack of considering the NAP leads to the underestimation of the total assembly time required for one printed circuit board (PCB) and eventually results in inaccurate production planning. The two-stage framework consists of metaheuristic and dynamic programming (DP) methods, which can deal with the three PCBA problems systematically. Various metaheuristics including firefly algorithm (FA), improved FA (IFA), genetic algorithm (GA), particle swarm optimization (PSO), and whale optimization algorithm (WOA) have been respectively used in this framework and experiments have been conducted to investigate their effectiveness. The results show that the hybridization of IFA with DP outperforms the others in terms of total assembly time.
... Improving the assembly time of one PCB for a SMT machine is critical as a significant benefit can be obtained from a large batch. There are different kinds of SMT machines currently used in industry, such as sequential pick-and-place, multi-head, dual-delivery, turret type, multi-station, and concurrent pickand-place machines [2] [3]. In this research, the kind of multihead gantry SMT machine (multi-head and sequential pickand-place) is focused as they have been widely used in industry [4] [5]. ...
... Typically, a multi-head gantry SMT machine supports different kinds of feeders such as stick feeder, tape feeder and tray carrier to ensure component availability [2]. The stick feeders are used for "sticks" (or ''tubes'') while the tape feeders are used for reels. ...
... For example, given H=4 and k=1 for the component j, the Mod( + , ) = Mod(1 + 4, 4) = 1 so that the component j is identified as a first component. The 1( , )is the distance between the feeder slots of component and , which is estimated by(2).1( , ) = | ( ) − ( )|(2)where ( ) and ( ) are feeder/tray positions of component i and j, respectively. The p(0) is set to 0. In the second case, the Mod( + , ) ≠ 1 which indicates that the component j is not the 1 st component in a component fetch cycle and the condition, , ∈ M1 ...
This research proposes a Multi-swarm and Discrete Firefly Algorithm (MDFA) to deal with the component sequencing problem (CSP) and feeder assignment problem (FAP) simultaneously for a multihead gantry surface-mounted technology (SMT) machine. The MDFA is an improved version of standard Firefly Algorithm (FA) which is a kind of nature-inspired and population-based metaheuristic. To our best knowledge, the FA has never been used to deal with the CSP and FAP simultaneously for the multi-head gantry SMT machine. Empowered by novel features such as multiple swarms as well as adaptive and discrete moving step, in addition to using an exploration-to-exploitation strategy, the MDFA is found capable of searching a solution space effectively. To investigate its effectiveness, the MDFA has been compared to the standard FA, particle swarm optimization (PSO), and genetic algorithm (GA). The experimental results show that the MDFA outperforms the others in terms of assembly time.
... An electronic device that mounts or places electronic components directly onto the surface of PCBs is called an SMT placement machine. Analyses of SMT assembly lines have shown that SMT placement machines are often a bottleneck whether arranged in parallel or sequentially [1][2][3]. The focus of this research is the optimization of a dualgantry pick-and-place machine, which is a category of SMT placement machines, to increase the throughput of an SMT line. ...
... There are many types of SMT placement machines, such as turret-type (also called chip shooter), multi-station, dual-delivery (or dual-gantry), etc. [3]. The technological characteristics of SMT placement machines influence the nature of the problem and its model formulation with constraints [4]. ...
... Each gantry can take nozzles and components from only its own station but can place components on the PCB at the other station. The unique and important feature of a dual-gantry machine is that each pick-and-place operation alternates between two stations [3]. To be specific, while one gantry is picking up components from feeder slots, the other gantry is placing components on the PCB. ...
... The turret-type SMD is usually called the chip shooter. The fixed turret head rotates between fixed pickup and placement positions, while the feeder rack and PCB table move, such that the turret head can pick the correct component and place it in the correct position [3,7,10]. It is mainly used to place low-precision and simple components; e.g., LED bulbs. ...
... It is mainly used to place low-precision and simple components; e.g., LED bulbs. To overcome the limitation of the chip shooter machine, multi-head gantry-type CAP machines have been invented to provide a more flexible pick-and-place assembly at a higher speed [3,7]. The multihead gantry-type machine has a fixed feeder base and PCB table, which increases the placement precision. ...
... The single gantry-type SMD machine optimization is most fundamental to the PCB assembly problem in the context of a hierarchical decomposition approach [2,15]. However, SMD machine vendors and software companies still cannot solve the single machine problem efficiently [3]. Most literature focuses on feeder assignment and pick-andplace sequence problems. ...
This paper presents an optimization study of the single gantry high-speed rotary-head collect-and-place (CAP) surface mount device (SMD) machine. The rotary-head gantry-type CAP machine has the advantage of high flexibility and speed, which is widely used in the PCB assembly of smart phones, tablets, laptops, and monitors. However, the pick-and-place process in SMD machines is the most time-consuming stage that determines the cycle time of a PCB assembly lines. This single gantry optimization problem can be decomposed into nozzle assignment, feeder assignment, and component pick-and-place sequence problems. Because they are highly interrelated to each other, an integer programming model is developed to solve them simultaneously. Based on the operational characteristics of high-speed machines, an adaptive nearest neighbor tabu search (ANNTS) is proposed to integrate the solution processes of feeder assignment, pick-and-place sequence, and multiple nozzle types assignment. Compared to CPLEX results, the ANNTS finds all optimal solutions of 14 randomly generated small-sized data sets. Another 13 industrial data sets are used to test the variants of the ANNTS, which include different initial solutions and search heuristics. Compared to the large clusters of operations (LCO) heuristic (Kulak et al. Int J Prod Res 45(17): 3949–3969, 2007), the ANNTS yields a 23.32 % distance saving on average for the single nozzle type problems. The ANNTS improves the productivity by 5.79 % on average, compared to the industrial package results.
... Last, when moving to a new PCB type the feeder, head and nozzle settings demand manual intervention in the production process, which has an impact on the overall efficiency of the production process. While the characteristics of the mounting machines may vary, the machine types can be classified into five main categories (Ayob and Kendal 2008). These are a dual delivery machine, where pick-and-place operations alternate between the two sides of the machine, there are two arms, and while one is placing components the other can pick up new ones; multistation machine (or modular machine), where several placement modules are connected via a conveyor belt and the modules operate autonomously; turret-type machine (chip shooter), where a rotating turret (operating like a carousel) holds a number of nozzles that are filled with components at a fixed pickup position and then placed in a fixed placement position, the PCB table moves in the X or Y direction and the feeder unit in the X-direction; multi-head machine (pick-andplace or collect-and-place machine) has an X-Y gantry used to move components from the feeder unit to the PCB. ...
... However, for PCB assembly the characteristics of the placement machine modules (especially capacity constraints) and the compatibility rules between the equipment (head, nozzle) and the component types are more complex. The solution approaches available for the singlemodel case employ exact methods (Baybars 1986) and heuristics (Ayob and Kendal 2008). For the mixed-model case, the solution methods include integer programing (Thomopoulos 1970), branch-and-bound (Bukchin and Rabinowitch 2006), Lagrange relaxation (Lapierre, DeBargis, and Soumis 1998) and heuristics (Crama et al. 1998;Simaria and Vilarinho 2004;Ho, Ji, and Dey 2008;Akpinar, Bayhan, and Baykasoglu 2013). ...
A popular gantry-type placement machine includes several interconnected, autonomously operating component placement modules and the machine was designed so as to able to use different kinds of placement heads and vacuum nozzles in the modules, which can be easily changed. Although this increases the flexibility of the production line, the reconfiguration phases of the modules may be unproductive and one should keep them to a minimum. In addition, the production times can be shortened by balancing the workloads of the machine modules. Here, a two-step optimisation method for the machine reconfiguration and workload balancing in the case of multiple Printed Circuit Borad (PCB) batches of different sizes and PCB types is presented. The objective is to minimise the total production time, and keep the machine configuration the same for all batches. The proposed algorithm is iterative and it applies integer programming for the workload balancing along with an evolutionary algorithm that searches for the best machine configuration. In experiments, for single PCB types the proposed algorithm obtained optimal or near optimal solutions. For multiple PCB types the solutions favour the PCB types that have a bigger production time due to greater batch sizes, but the total production time is still close to optimal.
... It connects electronic parts together. The board has layers stacked together, made of materials that conduct or insulate [5] . The conducting layers have paths and shapes like wires on a flat surface. ...
The study uses computer-aided design (CAD) software to design and fabricate printed circuit boards (PCBs). The primary goal is to conduct a thermal study with the goal to determine its suitability for use in avionic applications. A Brushless DC (BLDC) motor is connected to the PCB via 24 Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) which are connected to it by a Pulse Width Modulation Signal (PWMS). Given the potential effect of these MOSFETs' failure on the functionality of the PCB, maintaining their reliability becomes more crucial as external temperatures rise. The PCB is tested at ambient (28°C) conditions with isolated load, no load, and maximum load settings. Following that, simulated outcomes with Siemens Simcenter FlothermXT are compared with the experimental findings. An in-depth understanding of MOSFET thermal behaviour, including changes in temperature at the component and board levels, is made possible through this comparative analysis. The aim of this iterative approach is to maintain the PCB's safe operation within the set temperature limits. Keywords: Avionic Package, MOSFET, PCB, Thermal Analysis, Spring Load, Load Condition
... In the above equations, Eq. (1) represents the objective function, which means minimizing the maximum working time of the three workbenches. Equation (2) represents that the working time of the workbench is divided into two parts, which are composed of the time for the workbench to be attached and the time for the mounting head to change the nozzle at the nozzle exchange station. Equation (3) represents the calculation method of the workbench patch time. ...
A chip mounter is the core equipment in the production line of the surface-mount technology, which is responsible for finishing the mount operation. It is the most complex and time-consuming stage in the production process. Therefore, it is of great significance to optimize the load balance and mounting efficiency of the chip mounter and improve the mounting efficiency of the production line. In this study, according to the specific type of chip mounter in the actual production line of a company, a maximum and minimum model is established to minimize the maximum cycle time of the chip mounter in the production line. The production efficiency of the production line can be improved by optimizing the workload scheduling of each chip mounter. On this basis, a hybrid adaptive optimization algorithm is proposed to solve the load scheduling problem of the mounter. The hybrid algorithm is a hybrid of an adaptive genetic algorithm and the improved ant colony algorithm. It combines the advantages of the two algorithms and improves their global search ability and convergence speed. The experimental results show that the proposed hybrid optimization algorithm has a good optimization effect and convergence in the load scheduling problem of chip mounters.
... Most of the component placement machines work in pick-andplacement cycles where in each cycle the placement head collects a set of components from a feeder unit to vacuum nozzles, moves above the board and places them to the right positions. The machine types can be classified into categories (e.g., five categories by Ayob and Kendal [12]) based on the number of head mechanisms, the number of nozzles, and the movements of the head and the PCB holding table. In the recent days, one of the popular machine types is the modular gantry-type component placement machine, e.g., Fuji NXT or Siemens Siplace (see [13]). ...
In recent electronic industry, the assembly of electronic components on Printed Circuit Boards (PCB) is one of the most crucial tasks. Here, gantry type placement machines are popular because of the flexibility of their configurations. The Machine Configuration and (Work) Load Balancing (MCLB) problem determines the proper configurations of the machine modules in the assembly line and the allocation of the component placements among the modules minimizing the total production time. This is a difficult optimization problem, especially when the assembly line produces several batches of multiple PCB types using a common machine setup for all PCB types. In the present study, a graph model and a mathematical formulation are given for the multi-model problem (MCLB-M). A heuristic method is also presented, called Divide and Combine (DaC), which divides the multi-model problem into single product problems and solves them independently. The solutions are then combined to form a common sub-configuration of the modules. Finally, the global problem is solved by reducing its size using the fixed sub-configuration. The presented method is independent of the optimization algorithms used for the sub-problems; an integer programming model and a heuristic algorithm are used for the single problems, and an integer programming for the reduced global problem. The tests showed that the DaC method is robust and works well for problems of different size.
... (10,11) In addition, meter-scale large-area lighting devices can be applied to cover a whole ceiling or surfaces of furniture because the area of conventional home and office rooms is several square meters and conventional fluorescent light tubes are 1.4 m long. (12)(13)(14) Previous studies on flexible lighting devices, including LEDs on flexible PCBs (15) and organic LEDs on plastic substrates, (16,17) have shown the bending of devices two-dimensionally (i.e., rolling the device on a cylinder), but they cannot be bent three-dimensionally to cover the complicated shape of furniture and equipment in rooms because of the high mechanical rigidity of the plastic substrate. Conventional plastic sheet substrates, including polyester films and polyimide films, have high mechanical rigidity and stiffness. ...
... A majority (31.5%) of the respondents are in the 21 -30 years' age group followed by the 30 -40 years old group (25.5%), 40 -49 years old (19.0%), below 20 years old (14.5%), and (1.5%) are respondents above 50 years' age group. This study signifies that ecotourism is a "youthful" activity for the younger generation [23]. ...
Gelam Forest significantly has a unique biodiversity composition that is not found in other areas. This unique biodiversity has high potential for ecotourism that has yet to be explored and promoted in Malaysia. The purpose of this study is to estimate the economic value of Gelam (Mellaleuca spp.) forest for being developed as one of the potential ecotourism attractions in Kelantan. The primary data were collected through face to face surveys with the local community in districts of Bachok. A total of 200 respondents were participated in this study which consists of nearby locals that have different demographics. Contingent valuation method (CVM) was applied in this study to determine the local community's willingness to pay for ecotourism resources conservation at Gelam Forest. The result from logit regression indicates that the bid amount (price), income and education of respondents were significant predictors that influenced the level of willingness to pay for ecotourism resources conservation of Gelam Forest nearby to Universiti Malaysia Kelantan Bachok Campus. The estimated mean for public's willingness to pay is found to be RM 4.20 per head per year. It was concluded that Gelam Forest conservation initiatives were feasible for ecotourism development in future. The financial resources obtained from the amount of WTP might be used for conservation and as a fund for maintenances purposed.
... The optimisation issues associated with the automated installing of electronic components CONTACT Reza Tavakkoli-Moghaddam tavakoli@ut.ac.ir on a PCB are reviewed by Kendall 2008, 2009). Ayob and Kendall (2008) also showed that the complexity of the problem has led the problemdividing strategies to manageable problems become more popular. Some technical issues of robots in PCB assembly, in particular for HRC, were mentioned in (Ruggeri et al. 2017), which also proposes new robot technologies for these tasks. ...
The advancement of technology and the empowerment of the industry have made humans and robots more closely tied together, known as human-robot collaboration. A sector that specifically utilises this collaboration is the printed circuit boards industry. Therefore in this industry, proper allocation of tasks to humans and robots is crucial. This study investigates this type of allocation to minimise makespan. A Constraint Programming based (CP) approach is developed to solve the problem as the main novelty of this study. A single board problem, as the basic model, is developed by adding more assumptions including different groups of tasks, no-wait scheduling of tasks, multi-agent planning, and multiple boards sequencing. Then, different experimental instances are generated and solved to analyse the performance of CP and the sensitivity of idle time and makespan to key parameters of the problem. The superiority of the computational results of CP over mathematical programming is evident.
... The traditional manual assembly line system cannot meet the demands of the PCBs because of the complexity of the latest electronic devices due to miniaturisation and micromotion of high performance products (Duman and Ceranoglu 2003). To cope with the variety of PCB product demand and quantity, PCB manufacturing industries are shifting towards the automation by introducing highly effective automated surface-mounted technology (SMT) (Ayob and Kendall 2008). In the automated PCB assembly system, the SMT is used for component placement operation because the placement process is deemed as the bottleneck process (He, Li, and Yoon 2017). ...
The production planning and scheduling problems of printed circuit board (PCB) assembly line robustly influence the production efficiency of PCB industries. The current study focuses on the optimisation of the multi-level planning and scheduling problem by minimising the cycle time of the PCB assembly lines. Two levels of planning problems i.e. component allocation problem (CAP) and component placement sequence problem (CPSP) are solved simultaneously using mixed integer linear programming model. In CAP, a model is formulated with the objective of balancing the workload among the surface mounted machines (SMM), while in CPSP, a model is formulated to find optimum sequencing for allocated components at each SMM. A novel hybrid spider monkey optimisation (HSMO) algorithm is proposed with the addition of new sorting food sources and genetic operators in the standard spider monkey optimisation (SMO) algorithm. The performance of the proposed HSMO algorithm is validated by comparing the solutions with well-known algorithms, i.e. genetic algorithm (GA), particle swarm optimisation (PSO), simulated annealing (SA) and artificial bee colony (ABC) algorithms. The proposed HSMO algorithm is tested on different problem set instances scaled based on the realistic production of PCB industries. The detailed analysis of results indicates that the proposed HSMO algorithm outperforms the compared algorithms in efficiency and effectiveness.
... The optimisation issues arising in the automated placement of electronic components on a PCB was considered in two surveys, Kendall (2008, 2009). Ayob and Kendall (2008) also point out that the complexity of these problems has led to a somewhat popular strategy of dividing the problem into subproblems of manageable sizes, as we will do by introducing our matheuristic approach. Some technical issues of robots in PCB assembly, in particular for human-robot collaboration, were pointed out in Ruggeri et al. (2017), which also proposes new robot technologies for these tasks. ...
Advances in the technologies of sensors and lightweight robots increasingly enable direct physical interaction between humans and robots. This so-called human–robot collaboration is supposed to offer more flexibility in production processes, as opposed to fully automated processes. The aim of this contribution is to describe an integer linear programming model which optimally coordinates the distribution of tasks between humans and robots in a realistic production process of printed circuit boards (PCBs), where the objective is to minimise the completion time of a board. In addition, we discuss an extended case wherein a whole set of different boards is to be assembled, which is highly relevant for low volume production with a high degree of customisation. After stating an extended integer linear programming (ILP) formulation, we propose two practical approaches for solving the computationally more complex second scenario: an order-based heuristic approach and a matheuristic applying a truncated variant of the ILP model with different sequencing strategies. The computational evaluation based on a real-world use case from the PCB industry underlines the efficacy of the matheuristic approach for obtaining a good overall makespan.
... And their performance should meet the requirement standards. In the assembly process, the usage of different type placement head is also required in order to achieve concurrent high speed P&P process [4]. The processing speed is also affected by the frequent nozzle changes for different sized SMD components. ...
Surface Mount Device (SMD) is widely used in an automated Printed Circuit Board (PCB) assembling plant. Soldering SMD is a tedious and time-consuming process when it is done using bare hands. Industries require bulk production and hence it cannot be achieved by manual labour. For this fully automated SMD Pick and Place (P&P) machines are available in the market but the cheapest one starts at INR 15 Lakh (Yamaha yv-100x—Refurbished) and they are proprietary. Start-ups especially India based, find it difficult to afford such machine. In this paper, this issue is addressed and built an automated SMD P&P machine which is open source and far cheaper than the cheapest one in the market. However, the algorithm of the developed SMD P&P Machine and the one in the market remains the same but it functions differently and the steps are as follows; (i) Component are loaded onto the feeder tray (ii) Centroid file( machine file in ASCII format which comprise reference designator, X, Y, rotation, top or bottom side of the PCB board) is fed to the machine (iii) From the feeder tray component is picked by placement head using vacuum suction (iv) If the component is available in the placement head then correcting of component’s orientation and alignment using image processing is done else placement head is made to re-pick the component from feeder tray (v) Properly aligned and oriented component is placed on the PCB by releasing the vacuum. The proposed model is open source in both hardware (Raspberry Pi & Arduino) and software which is user friendly and easy to customize as per requirements.
... Nowadays, the multiple-spindle dual-gantry SMT machine is more popular in industrial practice because of its high-speed and high-flexibility [3,4,5]. There are three types of gantry-head: piano-type; revolver-type; and rotarytype [6]. The performance of piano-type machines is sensitive to simultaneously component pickups, which can save the gantry-head moving distance in the feeder base. ...
This paper presents an optimization study of dual-gantry high-speed rotary-type pick-and-place surface mount device (SMD) machine. In the dual-gantry SMD machine, there are two feeder bases and gantry heads, such that two placement heads can pick-and-place synchronously in one PCB, which has an advantage in assembly PCB with more component types. The dual-gantry optimization problem is decomposed into nozzle arrangement, feeder assignment, pick-and-place sequence, component allocation, and gantry schedule problems. To balance the workload between gantries and reduce the wait time in the gantry's synchronous movement, a balanced adaptive tabu search (BATS) algorithm is proposed. Based on the 16 industrial data tests, the proposed algorithm yields a 7.04% improvement on average compared to the industrial package.
... The multi-head surface mounting device (SMD) (see Ayob and Kendall 2008) is one of the most popular auto-assembly machines due to its relative high speed in mounting components on printed circuit board (PCB) and low price. The optimization problem for improving the throughput of its operations, however, is shown to be highly complex. ...
... The Reflow Process is a part of the process of Surface Mount Technology (SMT), technology where the components are mounted directly on the surface of the printed circuit board [10]. Processes of SMT assembly lines usually involve welding paste, placement of components and the operations of Reflow Welding [11]. The Reflow welding process consists of heating up the whole mounted board to liquefy the solder paste to form welding unions between SMDs and PCB without altering the original characteristics of the electric components. ...
In recent years, many efforts have been expended by companies in the search for technological improvement of their products by adding features such as lightweight materials, reduced size and high levels of performance at the lowest cost, to meet a worldwide demand in this regard. This article aimed to conduct an analysis of the quality of the Reflow of soldering in exchange of component of BGA technology. The methods and techniques used were the qualitative-quantitative approach, conducted by the case study technique in the welding process of the BGA component by collecting (cross section and X-ray) and data analysis (alignment, cracks and voids) within the process. The achieved results showed that the Reflow welding process in the exchange of BGA component meets the criteria for acceptance of international standards IPC -A - 610E and IPC 7095B. This fact leads to the inference that the quality of the process in question may reflect in better conditions and cost competitiveness for the investigated organization.
... • Finally the PCB is cleaned from contaminants exposed during the assembly process. Components placement machines in SMT environment can be categorized into five types with each placement machine possesses its own specifications as well as operations; these being dual-delivery, multi-station, turret-type, multi-head and sequential pick-and-place SMD placement machines (Ayob & Kendall 2008). This study focuses on turret-type assembly machine also known as concurrent chip shooter (CS), where the major advantage of this CS machine is its high speed because all the parts such as the feeder carrier with several feeders holds the components, X-Y table carrying ). ...
A Chip Shooter placement machine in printed circuit board assembly has three movable mechanisms: an XY table carrying a printed circuit board, a feeder carrier with several feeders holding components and a rotary turret with multiple assembly heads to pick up and place components. In order to minimize the total traveling time spent by the head for assembling all components and to reach the peak performance of the machine, all the components on the board should be placed in a perfect sequence, and the assembly head should retrieve or pick up a component from a feeder that is properly arranged. There are two modeling approaches of solving the components scheduling problem: integrated and iterative approaches, most popular meta-heuristic used so far for components scheduling problem is population based using integrated modeling approach. This work presents a single based meta-heuristic known as Simulated Annealing with an iterative modeling approach was adopted. The computational study is carried out to compare other population-based algorithms that adopted integrated approach. The results demonstrate that the performance of the simulated annealing algorithm using iterative approach is comparable with other population-based algorithms using integrated approach.
... After the printed circuit board (PCB) is completed, electronic components must be attached to form a functional printed circuit assembly (PCA) [34]. In throughhole construction, component leads are inserted in holes. ...
In the recent years, printers, especially inkjet printers, have become very commonly used in households, causing significant environment impact. In this paper, a life cycle assessment for an inkjet printer - model HP DeskJet D1360 manufactured in Taiwan, used and disposed in Poland was performed. The system boundaries of this study includes also consumables essential for printer operating: paper and ink as well as electricity consumption. Values for eleven impact categories were provided with the application of the Eco-indicator 99 method, expressing the significant environmental burden. For the whole life cycle the most significant stage is paper usage, followed by the manufacturing of the product and electricity consumption.
... In this study, we focus on optimizing the operations of chip shooter placement machines because they are widely accepted as the latest technology high speed placement machines [10,27,28,39,6]. Basically, these machines have multiple rotating pick and place heads and a linear feeder carriage that moves horizontally and makes available one of the next components to be placed in line with the placement head. ...
In this study we undertake the optimization of chip shooter component placement machines which became popular in assembling printed circuit boards (PCB) in recent years. A PCB is usually a rectangular plastic board on which the electrical circuit to be used in a particular electronic equipment is printed. The overall optimization of the chip shooter placement machines leads to a very complicated optimization problem which we formulate here for the first time (without any simplifying assumptions). However, it is possible to decompose the problem into placement sequencing problem and feeder configuration problem which turn out to be sequence dependent traveling salesman problem (SDTSP) and Quadratic Assignment Problem (QAP), respectively. We use simulated annealing metaheuristic approach and the heuristics developed for the SDTSP in an earlier study to solve these two problems in an iterative manner. We also attempt to solve the combined overall optimization problem by simulated annealing and artificial bee colony metaheuristics and compare their performances with the iterative approach. The results are in favor of iterative approach.
The present study aims at exploring the effect of communicating robots’ intent through visual cues, to the human on a complex human-robot collaborative task. Specifically, it aims to investigate (i) whether the use of such “anticipatory cues” will have a positive effect on task efficiency, human safety and collaborating fluency, (ii) the degree of this effect with varying robots’ speed and (iii) whether a retention effect will be observed after the removal of the cues. For exploring these issues, a human - dual robot industrial assembly task was designed in a Virtual Reality simulation environment and testing was carried out by 64 volunteer participants. Results showed that communicating robots’ intent through visual cues enhanced human anticipatory behavior, resulting in a significant improvement in human safety, team efficiency and collaborative fluency, in conjunction with a
favorable subjective tendency towards the robots. However, the positive effect of the anticipatory cues was not found to increase with higher robot speed. Finally, the findings suggest that prior exposure to the cues made participants more confident in coordinating with the robots, even when the cues were removed from them, thus retaining their prior efficiency but with a negative effect on safety. In summary, the study provides evidence that
use of anticipatory visual cues accelerates the legibility of robot movement and fosters human confidence and familiarization. The use of anticipatory cues seems promising for high-pace, non-repetitive interactions with collaborative robots or as a training aid in more repetitive human-robot collaborative tasks.
The optimization of printed circuit board assembly (PCBA) for a beam head placement machine is a multivariable and multiconstraint combinatorial problem. Current techniques falter in solving a variety of PCBA problems since heuristic algorithms lack theoretical guarantees of optimality, and mathematical modeling methods have high computational complexity for the whole problem. This article proposes a novel two-phase optimization for PCBA, integrating the advantages of mathematical modeling with heuristic algorithms. We divide the problem into the head task assignment and the placement route schedule. For the former, an effective integer linear programming model with component partition is proposed, encompassing key efficiency-influencing factors. A recursive heuristic-based initial solution speeds up the solving convergence, while the reduction strategies enhance model solvability. For the placement route schedule, a tailored greedy algorithm yields high-quality solutions, leveraging the results of the model, and an aggregated route relink heuristic does further optimization. In addition, we propose a selection criterion for the solution pool of the model to pre-evaluate the placement movement, which builds the connection between the two phases. Finally, we validate the performance of the two-phase optimization, which provides an average efficiency improvement of 8.66%–21.83% compared to other mainstream research.
Telefon, televizyon, bilgisayar, otomobil ve akıllı cihazlar gibi birçok üründe bir alt bileşen olarak kullanılan elektronik kartların verimli bir şekilde çalışmaları uygun tasarım, üretim ve kaliteye bağlıdır. Üretim süreçlerinde yüksek ürün çeşitliliği, üretim kapasite kısıtları ve model değişikliklerindeki hazırlık süreleri, katma değersiz ara operasyon ve sürelerle sonuçlanarak verimsizliğe neden olabilir. Bu çalışma, elektronik kart üretimi için hat atama problemlerini ele alarak verimlilik artışı ve maliyet düşürme amaçlı yenilikçi ve etkili yaklaşımlar önermektedir. Elektronik kartların farklı üretim ve test hatlarında en büyük üretim miktarını sağlayacak üretim planı farklı kriterler (örn. ürün ağacı, ortak bileşen kullanımı, bileşen adetleri, talepler, operasyon süreleri ve süreç akışında uğrayacağı istasyonlar ve sıralar) göz önünde bulundurularak belirlenmektedir. NP-zor problemi sınıfında yer alan PCB hat atama problemi, kümeleme analizi ve 0-1 karma tamsayılı matematiksel modelle çözülmektedir. Modelin sonuçları üretim hattının işleyişini modelleyen simülasyon modeli ile analiz edilmiştir. Gerçek verilerle yapılan uygulamada, önerilen yaklaşım kullanılarak üretim miktarında mevcut duruma oranla %22 oranında iyileşme sağlanmıştır. Önerilen yaklaşım, birden çok yüzey montaj teknolojisi (SMT) özelliğine sahip otomatik dizgi hattı, birden çok süreç akışı ve birden çok test ayar istasyonuna sahip bir elektronik kart üreticisinin çizelgelemesi için uygulanabilir.
Hopfield neural network (HNN) is a well-studied optimization method, but has not been able to solve the capacitated location routing problems (CLRP). Transporting components from the feeders to the placement points by a capacitated head set, the pick-and-place location routing in multi-functional placers is studied as a typical CLRP. The original problem is decomposed into three subproblems deciding the placement points grouping, feeders location and inner-group placement sequencing, respectively. The first two subproblems are optimization problems with multiple tours. With heuristics designed for optimization within a single tour, these two subproblems are transformed into the heuristic sequencing optimization problems that optimize the solving sequence of the tours. The typical HNN for the travelling salesman problem is improved, which results in the heuristic sequencing HNN. The energy function is adapted for reflecting the activation states of the energy matrix about the index-sequence pairs. Through exploration into the objective function value of each index-sequence pair, the energy matrix is calculated by a specially designed method combining with a normalization technique. To achieve optimal performance of the HNN-based methods, a multi-start mechanism is employed. The effectiveness and efficiency of the proposed method are finally elucidated by experiments using practical industrial data.
Surface mount technology, usually on the context of Pick-up and Placement, is used on printed circuit boards assembling. In this paper, some aspects and physical parameters related with the pick-up and placement process are analysed in detail throughout the entire work sequence, such as the different variants of these same components among the various suppliers under study. In this process, there are problems of rejection and quality. The aim of this work is to identify and analyse these types of components, as well as their differences and possible causes for their misplacement on the printed circuit boards. Measurements and analyses were performed in lab tests and the study focused more on the capacitors’ assembling details. Experimental tests were carried out on the production line in order to obtain conclusive results regarding the study of nozzles and placement of components. Finally, it was concluded that nozzles 907 present a good behaviour in resistors and nozzles 925 present a good behaviour in capacitors.
Solving a newly defined component allocation problem by the proposed cell division genetic algorithm (CDGA), this paper effectively optimizes all the objectives of the pickup-and-place (PAP) optimization in a multi-functional placer, which remains a formidable challenge till now. The CDGA applies a decoding heuristic that reduces the problem dimension and allocates several components of the same type as one unit, namely a component cell. When a better allocation can no longer be found by allocating the current cells, the cell division operation is performed to divide each cell into two new cells. The new cells are then used in the next round of GA optimization, which may further optimize the allocation. In experiments using the industrial PCB samples, the proposed algorithm provides a significant improvement compared to the built-in optimizer of the widely-used multi-functional placer, Samsung SM482, which demonstrates its effectiveness and superiority.
This article proposes a hierarchical multiobjective heuristic (HMOH) to optimize printed-circuit board assembly (PCBA) in a single beam-head surface mounter. The beam-head surface mounter is the core facility in a high-mix and low-volume PCBA line. However, as a large-scale, complex, and multiobjective combinatorial optimization problem, the PCBA optimization of the beam-head surface mounter is still a challenge. This article provides a framework for optimizing all the interrelated objectives, which has not been achieved in the existing studies. A novel decomposition strategy is applied. This helps to closely model the real-world problem as the head task assignment problem (HTAP) and the pickup-and-place sequencing problem (PAPSP). These two models consider all the factors affecting the assembly time, including the number of pickup-and-place (PAP) cycles, nozzle changes, simultaneous pickups, and the PAP distances. Specifically, HTAP consists of the nozzle assignment and component allocation, while PAPSP comprises place allocation, feeder set assignment, and place sequencing problems. Adhering strictly to the lexicographic method, the HMOH solves these subproblems in a descending order of importance of their involved objectives. Exploiting the expert knowledge, each subproblem is solved by an elaborately designed heuristic. Finally, the proposed HMOH realizes the complete and optimal PCBA decision making in real time. Using industrial PCB datasets, the superiority of HMOH is elucidated through comparison with the built-in optimizer of the widely used Samsung SM482.
The beam-type placement machine is capable of picking up multiple components simultaneously from the feeders in printed circuit board (PCB) assembly. Simultaneous pickup occurs only if the heads in the beam are aligned with the feeders and the nozzle-types on these heads match with the component-types on the feeders. In order to minimise the assembly cycle time, the optimisation problem is decomposed into two sub-problems, the pickup combination and sequencing problem, and the placement cluster and sequencing problem. These two sub-problems are simultaneously solved by the proposed hybrid genetic algorithm (HGA). The pickup combination and sequencing problem is similar to the popular multi-compartment vehicle routing problem (MCVRP); a genetic algorithm (GA) for the MCVRP is therefore modified and applied to solving the pickup combination and sequencing problem. A greedy heuristic algorithm is used to solve the placement cluster and sequencing problem. The numerical experiments reveal that the HGA outperforms the algorithms proposed by previous papers.
Numerically controlled placement machines are often equipped with modular feeder units. These allow the group loading of a large number of component reels in one step. While the loading of individual component reels has been extensively studied in the past, there has not been any algorithmic solutions published for modular feeder loading. The problem in known to be NP-hard even for a fixed job sequence. A mathematical 0-1 formulation, a lower bound on the optimal result, and an efficient heuristics will be given in the present study. The heuristic is evaluated against the lower bound, and the ratio of the heuristic result and lower bound value is reported. We found that for randomly generated problems, this ratio is between 2 and 4, while for some of the large industrial problems we obtain a ratio between 6 and 12.
This research proposes a clustering-based heuristic, named average Chebyshev linkage directed search (ACLDS), to optimize the nozzle and feeder assignments in a single spin-head gantry-type collect-and-place (CAP) surface mount technology machine. The CAP machine is widely used in the printed circuit board assembly (PCBA) of consumer electronic products, but still a challenging application field from an operations research perspective. The PCBA optimization of a single machine is decomposed into interrelated nozzle assignment, feeder assignment and CAP sequence subproblems, which is treated as a special case of the capacitated location routing problem (CLRP). Because of the NP-hard nature of this problem, ACLDS is proposed to solve it efficiently, which is a hierarchical heuristic to obtain the optimal nozzle assignment and then optimize feeder assignment and CAP sequence iteratively. A clustering technique is applied in ACLDS to group components based on their nozzle and component types in the consideration of the optimal CAP sequence. To investigate the efficiency of the proposed algorithm, thirteen industrial PCB samples and 40 artificial samples are used for experiments. Compared to the adaptive simulated annealing (ASA) algorithm [1], the large clusters of operations (LCO) algorithm [2], the hybrid genetic algorithm 2 (HGA2) algorithm [3], industrial package (IP) [4], and the adaptive nearest neighbor tabu search (ANNTS) algorithm [4], the proposed algorithm demonstrates its efficiency by testing through both industrial and artificial PCB samples.
A new mechanism，namely a combination of curve matching method based on the discrete Fréchet distance and evolutionary algorithms，is proposed to solve pick-and-place sequence optimisation problems as a multi-objective optimisation problem. The essence of the mechanism is to accomplish the comparison of objective vectors with curve matching method. The objective vector is mapped into the array of points with a binary mapping operator and the discrete Fréchet distance is utilised to measure the similarity between the reference array of points and the comparison array of points. The genetic algorithm based on the discrete Fréchet distance (FGA) is proposed. To test the new mechanism, together with FGA, three other test algorithms are selected to solve the sequence optimisation problem. The simulation results indicate that FGA outperforms other algorithms. This new mechanism is rational and feasible for multi-objective pick-and-place sequence optimisation problems.
Placement machines are the most critical and expensive pieces of equipment in SMT, which commonly constitute the bottleneck of the assembly line, and hence determine the throughput. Growing production volumes, reducing size of components and complexity of the boards reinforced the usage of full-automated assembly lines. Depending on the placement type, fullautomated placement systems can be observed in two main groups: simultaneous and sequential placement equipment.44
Component pick-and-place technology has been widely used to improve production efficiency and reduce common defects. The vision-driven measurement system of a component pick-and-place machine requires an appropriate positioning algorithm with low computational complexity, high accuracy, and high generalizability. To satisfy these attributes is rather challenging. This paper focuses on the online component positioning problem based on corner points. Thus, we propose a robust, accurate, and efficient universal algorithm that incorporates pre-processing, coarse positioning, and fine positioning stages. Two types of model key points are introduced for interpreting the model component. To enhance positioning accuracy and robustness against illumination changes, the Harris corners and sub-pixel corner points are extracted from the images of real components. In the coarse positioning step, distance and shape feature matching methods are introduced to respectively compute the coarse and correct correspondences between type I model key points and Harris corner points. After the corresponding point pairs have been obtained, the coarse and fine positioning problems are formulated as least squares error problems. The effectiveness of the proposed method was verified by applying the method in several real component positioning experiments.
Flexible production is essential for manufacturers in the face of changing demands for the printed circuited board assembly (PCBA) industry. Machine flexibility is an important factor used to enhance the flexibility of a PCBA system. Configuring the surface mount assembly (SMA) lines is one of the most significant operational decisions of PCBA to cope with variable demands and product variants. Aggregating the flexibility of a chip-placer group is conducive to evaluate the SMA line flexibility, so that decision-makers can develop better production strategy. In this research, a flexibility measuring framework was developed using an entropy-based method and the Taguchi quality loss function to assess SMA line configurations with different chip-placer groups. Based on the resulting flexibility measurements, a neural network model is adopted to estimate the flexibilities of possible chip-placer combinations and suggest the most appropriate line configurations for the subject company. Some findings and managerial implications are also provided.
Printed circuit board assembly (PCBA) is a process of connecting various electronic components through printed circuit boards (PCBs). Due to the need to assemble a lot of components and PCBs at the same time, the PCBA process tends to become the bottleneck in an assembly line. Many assembly firms have thus introduced automated PCBA machines to expedite this process. However, to best operate these machines, effective PCBA planning is still required. Some nature-inspired metaheuristics such as simulated annealing and genetic algorithm (GA) have been increasingly used for the PCBA planning. Also, we find that particle swarm optimization (PSO) has never been employed to deal with the feeder assignment problem (FAP) and component sequencing problem (CSP) at the same time, though it has been regarded as a good competitor to GAs. In this paper, we developed two PSO-based approaches to deal with the two problems simultaneously for a chip shooter machine. In addition, we have conducted experiments to compare the two PSO-based approaches with two GA-based approaches. The experimental results showed that PSO2, the PSO-based approach with sigmoid functions, outperformed others in terms of assembly cycle time. The comparison with an exact approach further shows that PSO2 has a high rate to find the optimal/near-optimal solution.
This paper proposes a heuristic multi-phase approach to minimize the moving distance of gantries by balancing the workload of a dual-delivery surface mount technology (SMT) placement machine. The SMT placement machine under study is a rotary-head dual-gantry machine. Several practical factors are considered, such as the component-nozzle compatibility and the machine structure. The machine has two stations with a symmetric layout. Each station has a printed circuit board (PCB) conveyor belt, a fixed camera, an auto nozzle changer, a feeder base, and a movable gantry with several nozzle heads. In the pick-and-place assembly operation, two independent gantries alternately mount on one PCB. Most research in literature considers three main decisions in the SMT placement machine optimization: nozzle setup, feeder arrangement, and pick-and-place sequence. In this research, two more decisions are introduced into the dual-gantry problem: workload balance between gantries and gantry cycle scheduling. A hierarchical strategy is developed to solve the workload balance problem, including nozzle and component allocations. The other decisions, such as the feeder arrangement and the pick-and-place sequence, are made using existing heuristics. The experimental results show that this heuristic approach has advantages compared to other algorithms proposed in literature.
The assembly of electronic components on printed circuit boards is performed in a line of automated placement machines, each equipped with a feeder unit that contains the component reels required for a product type. Assembling multiple product types by a single machine requires the replacement of certain components in the feeder unit. Increasingly, assembly machines are equipped with modular feeder units, enabling the replacement of a larger group of component reels. To minimize the machine setup time, component reel modules can be preassigned with the necessary component types, thus requiring only the loading of a suitable module set for each product. This work introduces and analyses the problem of constructing the minimum number of component reel modules, with the objective that a set of jobs can be manufactured without individual component reel changes. We show that the problem is NP-hard and provide an integer programming formulation for it. We also introduce two heuristics based on job grouping, and analyze the results.
This paper proposes the development of a mechanism to minimise the assembly time for a multi-headed gantry and high-speed surface mounting technology machine by determining the component assignment to feeder slots. Since a gantry moves long distances in order to pick components, place them on the board and then return them to the feeder slots, we classified the overall assembly time according to the different movements of a gantry. The overall assembly time is then minimised by presenting a new heuristic for the feeder assignment, consisting of Nearest Component Allocation (NCA) and Globally Updated Assignment (GUA). NCA contains information about how each component type locates closely to others on the board. Using the solution from NCA, the component distance function calculates the most representative distance between component types. Then, GUA is applied to improve the NCA solution. The experiments consist of several printed circuit boards with numbers of component types and points to be placed. Highlights of this paper are that: a classification of the gantry movements is proposed based on the average speed; a heuristic NCA-GUA for feeder assignment is developed by considering the placements on the board; the computational time is greatly reduced by NCA-GUA without degrading the solution quality; and a decision process for nozzle assignment is proposed to minimise the overall assembly time. The results show how NCA and GUA affect the final results, and how this mechanism leads to better performance than a genetic algorithms or 2-opt swap search. This comparison proves that our method provides competitive and effective solutions in terms of minimising the overall assembly time.
This paper focuses on an operation optimisation problem for a class of multi-head surface mounting machines in printed circuit board assembly lines. The problem involves five interrelated sub-problems: assigning nozzle types as well as components to heads, assigning feeders to slots and determining component pickup and placement sequences. According to the depth of making decisions, the sub-problems are first classified into two layers. Based on the classification, a two-stage mixed-integer linear programming (MILP) is developed to describe it and a two-stage problem-solving frame with a hybrid evolutionary algorithm (HEA) is proposed. In the first stage, a constructive heuristic is developed to determine the set of nozzle types assigned to each head and the total number of assembly cycles; in the second stage, constructive heuristics, an evolutionary algorithm with two evolutionary operators and a tabu search (TS) with multiple neighbourhoods are combined to solve all the sub-problems simultaneously, where the results obtained in the first stage are taken as constraints. Computational experiments show that the HEA can obtain good near-optimal solutions for small size instances when compared with an optimal solver, Cplex, and can provide better results when compared with a TS and an EA for actual instances.
This paper deals with the PCB assembly time minimization problem that the PAP (pick-and-placement) machine pickup the K-weighted group of N-components, loading, and place into the PCB placement location. This problem considers the rotational turret velocity according to component weight group and moving velocity of distance in two component placement locations in PCB. This paper suggest heavy-weight component group first pick-and-place strategy that the feeder sequence fit to the placement location Hamiltonean cycle sequence. This algorithm applies the quadratic assignment problem (QAP) that considers feeder sequence and location sequence, and the linear assignment problem (LAP) that considers only feeder sequence. The proposed algorithm shorten the assembly time than iATMA for QAP, and same result as iATMA that shorten the assembly time than ATMA.
The hardware restrictions of surface mount placement machines, such as height, pick and place restrictions, and simultaneous pickup are often in printed circuit board (PCB)-related studies. This study proposes an efficient hybrid genetic algorithm (HGA) for solving the nozzle assignment problem and the component pick and place sequence problem. First, the proposed method obtains the sequence of the automatic nozzle changer (ANC) with the maximum number of simultaneous pickups and the minimum number of picks as the solution of the nozzle setup problem. Then, the proposed method uses the nearest neighbor search (NNS), 2-optimization, and a genetic algorithm (GA) with the known ANC sequences to obtain the PCB assembly time with the optimal component pick and place sequence. Experiments are conducted on the PCB of the EVEST EM-780 surface mount placement machine. Results show that the proposed HGA gives the lowest total number of picks, the shortest total head movement distance, and the minimum total PCB assembly time compared to those of other methods.
The operation optimization problem considered in this paper arises on a multi-head surface mounting machine with over-head gantry when it mounts electronic components on the surface of a printed circuit board (PCB) in PCB assembly. The aim of the problem is to minimize the time that a machine takes to mount all the required components. It is a complex optimization problem involving three inner-related sub-problems: (i) the assignment of nozzle types to heads, (ii) the assignment of feeders to slots, and (iii) the component placement optimization, specifying for each component on which head it is grasped and in which mount cycle it is processed, and in which orders the components are picked and mounted. A mathematical model with two stages is presented for it in this paper. In the first stage, nozzle assignment is formulated to a Mixed Integer Linear Programming (MILP). In the second stage, the latter two sub-problems are firstly integrated and formulated as a MILP model. The model could be solved to optimality only for very small size of problem instances.
This study presents development of an automated lead defect inspection system by using Visual Mechanical Inspection Scanner (VMIS) in semiconductor industry. In any device seated out of cavity, VMIS detects misplacement error (ME), a quality defect in surface mount technology (SMT). ME causes a lifted lead defect on lead packages. MEs that can be analyzed are of two kinds: i) device seated out of cavity; and ii) double devices imbedded in the same cavity. The system was successfully tested on devices with 90% accuracy of inspection. Thus VMIS can inspect device seated out of cavity and hence prevents lifted lead from occurring.
The main task of printed wiring board (PWB) assembly is to mount electronic components on a PWB. The generation of efficient insertion and placement sequences will lead to significant time saving in assembly and thus save production cost. When generating insertion sequences, the first consideration is to avoid potential collision problems. This research is aimed at finding the minimum assembly time for each assembly machine through the generation of machine-head sequences and component sequences. Mathematical programming may be used to solve the sequence problem; however, the solution is computationally explosive and is impractical to implement. The proposed collision-free and closest-distance heuristic approach is based on the various characteristics of printed wiring assembly, such as insertion heads and component feeding types. This approach reduces the complexity of the problem and detects potential collisions before the generation of machine-head sequences and component sequences. Not only can the algorithm generate machine head sequence and component sequences effectively, it also guarantees no conflict between these two levels.
Component placement sequencing is a challenging problem that arises in automated assembly of printed circuit boards. While for some placement machines all placement sequences are acceptable, in other cases some sequences are not allowed because of the shape of the placement head. In such cases, while the head moves down to perform a placement, it might damage a previously placed component, and the problem of determining a minimum cost and at the same time acceptable sequence leads to a Precedence Constrained Travelling Salesman Problem formulation. In this study, a solution procedure to such a formulation is developed and its implementation in a real PCB assembly environment is discussed.
Products assembled by robots are typical in present day manufacturing. The traditional type of automatic assembly is Fixed Picked and Place (FPP) mode. The development of the Dynamic Picked-and-Place (DPP) model is an important issue in robotics travel. Until now, to route robotics travel, the authors usually have utilized the fixed coordinate of insertion points and magazine of the Travelling Salesman Problems (TSP) method to sequence the insertion points. However, robotics travel routing should be based on a relative coordinate because the coordinates of insertion point and magazine are constantly changing. That is, the robotics, board and magazine are simultaneously moved at different speeds. This study presents a Simulated Annealing (SA)-based algorithm that can arrange the insertion sequence and assign the magazine slots to obtain a performance better than in the traditional approach.
This work focuses on optimising the hybrid pick and place machine which is a new surface mount device placement machine. We present an on-line constructive heuristic to schedule the component pick and place operations. The machine begins a pickup and placement operation once the first placement point is scheduled. While the machine is moving, picking or placing other components, the scheduler concurrently schedules the subsequent placement points. Since a nozzle change operation is very expensive (it significantly adds to the overall assembly time), the constructive heuristic gives highest priority to minimising the number of nozzle changes, then maximising simultaneous vision operations, simultaneous pickup and same tour pickup operations. Finally, when all the available placement points, which have components available on the feeder slots, have been scheduled by the constructive heuristic, we then reoptimise the schedule by minimising the nozzles changes. Computational results are presented.
Robotic assembly cells consist principally of an assembly table, a supply magazine, and a Cartesian robot where the robot picks up assigned components from the magazine and places them in prearranged locations on the assembly table. The major concern in industry is to optimize robot traveling time so that a shorter assembly cycle time can be achieved. Three factors directly affecting assembly efficiency are: (1) robot motion control, (2) the sequence for placing the individual component on the assembly board, and (3) the corresponding magazine slot location from which the components must be selected. This paper proposes a magazine assignment heuristic coupled with dynamic pick-and-place (DPP) robot motion control to improve assembly efficiency. Simulation results indicate that our magazine assignment heuristic, with DPP robot motion control, always surpasses the same magazine assignment heuristic applied to the traditional fixed pick-and-place (FPP) robot motion control.
In PCB assembly planning, most of the current works solved the assembly sequence and feeder assignment problem directly. They have not decomposed the problem into subproblems. Consequently, the problem remains very complex and, therefore, it is hard to solve. Few research works considered about the detail on how to determine the optimal picking points (or placement points), but results are still limited. The extension of these works is necessary. This paper extends the point specification problem based on the Dynamic Pick and Place (DPP) model, namely, the Extended Dynamic Pick and Place (EDPP0 model. The EDPP determined the picking/placement point coordinates from global consideration of point relationship in the system. The whole system is analysed to establish the new model. From this guideline the system is modelled in a systematic scheme based on the objectives of each object in the systems (robot arm, feeder rack, board table). These objectives should be satisfied together to reach the global objective of the system. Numerical experiment shows that the EDPP model is better than the DPP model in terms of total assembly time.
This work focuses on improving the throughput of a pick-and-place surface mount device placement machine. These machines are designed to place electronic components onto a printed circuit board. The machines considered in this work are economical and medium speed machines that have four fixed feeder carriers, a fixed printed circuit board table, two vision cameras, a tool bank, a trash bin and a positioning arm head (i.e. a head that is moveable in both X and Y axes simultaneously) that is equipped with two pipettes. As nozzle change operations are very time consuming, the constructive heuristic presented in this paper gives priority to reducing the number of nozzle change operations in order to schedule the component pick-and-place operations when assembling printed circuit boards. Based on the average machine operation time, provided by the machine manufacturer, we compute the effectiveness of each pick-and-place operation type and assign a weighted value for each type of the operation. The nozzle pairs are ranked based on their effectiveness that indicates how many good pick-and-place operations can be performed by the nozzle pair. The heuristic begins by choosing the best nozzle pair to be applied. Next, we schedule the pickup-and-placement of all points that are expecting components from the chosen nozzle pair. Based on the availability of component feeders and the remaining placement points to be scheduled, we then re-rank the nozzle pairs and the procedure is repeated. Computational results show that, on average, a weighted nozzle rank heuristic is superior to an Ordered heuristic that was presented in our previous work.
This paper is concerned with the hybridization of two graph coloring heuristics (Saturation Degree and Largest Degree), and their application within a hyperheuristic for exam timetabling problems. Hyper-heuristics can be seen as algorithms which intelligently select appropriate algorithms/heuristics for solving a problem. We developed a Tabu Search based hyper-heuristic to search for heuristic lists (of graph heuristics) for solving problems and investigated the heuristic lists found by employing knowledge discovery
techniques. Two hybrid approaches (involving Saturation Degree and Largest Degree) including one which employs Case Based Reasoning are presented and discussed. Both the Tabu Search based hyper-heuristic and the hybrid approaches are tested on random and real-world exam timetabling problems. Experimental results are comparable with the best state-of-the-art approaches (as measured against established benchmark problems). The results also demonstrate an increased level of generality in our approach.
In this paper we introduce a Monte Carlo based hyper-heuristic. The Monte Carlo hyper-heuristic manages a set of low level heuristics (in this case just simple 2-opt swaps but they could be any other heuristics). Each of the low level heuristics is responsible for creating a unique neighbour that may be impossible to create by the other low level heuristics. On each iteration, the Monte Carlo hyper heuristic randomly calls a low level heuristic. The new solution returned by the low level heuristic will be accepted based on the Monte Carlo acceptance criteria. The Monte Carlo acceptance criteria always accept an improved solution. Worse solutions will be accepted with a certain probability, which decreases with worse solutions, in order to escape local minima. We develop three hyper-heuristics based on a Monte Carlo method, these being Linear Monte Carlo Exponential Monte Carlo and Exponential Monte Carlo with counter. We also investigate four other hyper- heuristics to examine their performance and for comparative purposes. To demonstrate our approach we employ these hyper-heuristics to optimise component placement sequencing in order to improve the efficiency of the multi head placement machine. Experimental results show that the Exponential Monte Carlo hyper- heuristic is superior to the other hyper-heuristics and is superior to a choice function hyper-heuristic reported in earlier work.
The feeder assignment and assembly sequence problem in printed circuit board (PCB) assembly with the twin objectives of minimizing magazine travel time and minimizing board travel time is presented in this study. The problem uses Dynamic Pick-and-Place (DPP) model where robot arm, board and magazine move together with different speeds based on relative coordinates between consecutive assembled points. The difficulty of the problem is that the feeder assignment depends on assembly sequence and vice versa. A new approach is proposed to improve the existing approaches. The trade-off between two strategies, assembly by area and assembly by component types, can give better results. The numerical experiments proved the efficiency of the new algorithm.
Hyperheuristics can be defined to be heuristics which choose between heuristics in order to solve a given optimisation problem. The main motivation behind the development of such approaches is the goal of developing automated scheduling methods which are not restricted to one problem. In this paper we report the investigation of a hyperheuristic approach and evaluate it on various instances of two distinct timetabling and rostering problems. In the framework of our hyperheuristic approach, heuristics compete using rules based on the principles of reinforcement learning. A tabu list of heuristics is also maintained which prevents certain heuristics from being chosen at certain times during the search. We demonstrate that this tabu-search hyperheuristic is an easily re-usable method which can produce solutions of at least acceptable quality across a variety of problems and instances. In effect the proposed method is capable of producing solutions that are competitive with those obtained using state-of-the-art problem-specific techniques for the problems studied here, but is fundamentally more general than those techniques.
In this article, we analyze numerical control problems arising in a component insertion line for printed circuit board mounting. Such a line consists of a number of fully automated placement machines, connected by an automated, carrierless conveyor system. At each machine, the placement device consists of an arm equipped with a number of placement heads. Each head may serve certain component types; there is some freedom in the choice of equipment for each head. Components are supplied to each machine by tape feeders (each containing components of only one type) which are placed at certain feeder positions along the machine. Before actually operating such a line, a careful production preparation phase has to be completed, specifying for each printed circuit board type the exact way in which such a board should be mounted. Problems arising in this production preparation phase include: the choice of heads to be mounted on the placement arm of each machine, the choice of components to be placed at each machine (workload balancing), an assignment of feeders to feeder positions on each machine, clustering of components to be placed in one pick-and-place move, and the sequencing of component insertions at one machine. Formulations and solutions for all these problems are given and numerical results for some industrial examples are given. The numerical control system developed has been tested and implemented and has resulted in software, which is in use at several sites of Philips' Electronics.
This paper presents a hybrid genetic algorithm to optimize the sequence of component placements on a printed circuit board and the arrangement of component types to feeders simultaneously for a pick-and-place machine with multiple stationary feeders, a fixed board table and a movable placement head. The objective of the problem is to minimize the total traveling distance, or the traveling time, of the placement head. The genetic algorithm developed in the paper hybridizes different search heuristics including the nearest neighbor heuristic, the 2-opt heuristic, and an iterated swap procedure, which is a new improving heuristic. Compared with the results obtained by other researchers, the performance of the hybrid genetic algorithm is superior to others in terms of the distance traveled by the placement head.
This chapter introduces and overviews an emerging methodology in search and optimisation. One of the key aims of these new approaches, which have been termed hyperheuristics, is to raise the level of generality at which optimisation systems can operate. An objective is that hyper-heuristics will lead to more general systems that are able to handle a wide range of problem domains rather than current meta-heuristic technology which tends to be customised to a particular problem or a narrow class of problems. Hyper-heuristics are broadly concerned with intelligently choosing the right heuristic or algorithm in a given situation. Of course, a hyper-heuristic can be (often is) a (meta-)heuristic and it can operate on (meta-)heuristics. In a certain sense, a hyper-heuristic works at a higher level when compared with the typical application of meta-heuristics to optimisation problems, i.e., a hyper-heuristic could be thought of as a (meta)-heuristic which operates on lower level (meta-)heuristics. In this chapter we will introduce the idea and give a brief history of this emerging area. In addition, we will review some of the latest work to be published in the field.
Populating printed circuit boards is one of the most costly and time-consuming steps in electronics assembly. At the beginning of each work order, three decisions are required: (1) a sequence must be specified for placing the individual components on the board; (2) tape reels must be assigned to positions on the magazine rack; and (3) a retrieval plan must be determined should the same component type be assigned to more than one magazine slot. Collectively, these problems can be modeled as a nonlinear integer program. In this paper, we develop a series of algorithms for solving each using an iterative two step approach.
Initially, a placement sequence is generated with a weighted, nearest neighbor traveling salesman problem (TSP) heuristic; the two remaining problems are then formulated as a quadratic integer program and solved with a Lagrangian relaxation scheme. As a final step, the current magazine assignments are used to update the placement sequence, and the entire process is repeated.
Our ability to deal, at least in part, with simultaneous machine operations represents the major contribution of this work. The methodology was simulated for a set of boards obtained from Texas Instruments and theoretically compared with a heuristic currently in use.
The competitive nature of the electronic industry has greatly intensified in recent years. The capital investment in this segment of industry constitutes a large portion of current industrial investments. Printed Circuit Boards (PCBs) are an important module of electronic parts, and consequently, highly automated manufacturing systems have been designed to produce the required circuit cards at the desired volume. The design, planning, scheduling, and control problems which arise in this environment are challenging and multi-faceted.
This paper proposes a methodology for efficient process planning of concurrent machines in electronics assembly. The particular machine type under consideration is the High Speed Chip Shooter (HSCS) for surface mount assembly. Currently, most surface mount assembly operations are modeled in a cyclic manner. The model that is proposed herein is an asynchronous (acyclic) model that augments the benefits of the unique features of this assembly machine. A heuristic algorithm is developed, referred to as the Acyclic Assembly Time (AAT) algorithm, which is based on the asynchronous model. The algorithm is thoroughly tested with orthogonal arrays, compared against previously published problems, and applied to a real life example. The AAT algorithm produced excellent results throughout the test process. By increasing the utilization of the individual mechanisms, the efficiency of the overall system naturally improves and the ultimate goal of reducing the total assembly time is achieved.
Surface Mount Technology (SMT) is a popular method of Printed Circuit Board (PCB) assembly in which high speed automated assembly machines are capable of placing in excess of 40,000 components per hour. In order to achieve these impressive assembly rates, complex placement machines must be programmed efficiently. Intrinsic to the configuration of these machines and the assembly process are some well established Operations Research problems. This paper addresses the feeder sequencing problem for an assembly machine with a sliding feeder rack in conjunction with a X-Y positioning table and a turret placement mechanism. This problem is a Quadratic Assignment Problem, and is proven to be NP-complete.1 Two different heuristic methods are proposed, each with unique characteristics that have the potential to be beneficial to an assembly operation dependent upon the restrictions of the planning task. One method is to assign feeder slots based on the transition between component types that naturally occur in the board placement path. The second method begins with an initial slot assignment and identifies exchanges between pairs of slots that generate improvements in the objective function. Minimizing the feeder travel distance over an assembly is the goal of each heuristic. A comparative analysis between the two heuristics is performed. Examples are presented and the attributes of each method are discussed. Arguments are presented to support "near-optimal" solutions to the problem. Given the complexities of the system, proper planning of the assembly process can take advantage of the independent control of each mechanism to create a natural relaxation of specific constraints.
The placement of surface-mounted components is an essential stage in printed circuit board assembly (PCBA). A reduction in production time of placement through efficient process planning will significantly increase the total yield of the whole line. A new approach to solving this problem is presented. This is based on a knowledge-based component placement system (CPS), which incorporates ready optimization algorithms. This approach is particularly suited to sophisticated but popular multi-head concurrent operation assembly machines. A case for going beyond just achieving an overall shortest travel distance in placement is also argued. A case study of this approach is presented.
Some of the major enhancements are eliminating head contention, reducing or eliminating nozzle changes, supporting user-defined nozzles, supporting large nozzles for holders 2 and 3, and being able to define multiple part data for a given part number. The cycle time improvement exceeds the original goal of 5%, and the result at one surface mount center was more than 16% over hand-created and optimized recipes. The solution helps both the high-volume and the high-mix centers. Reduction of placement cycle time in an assembly line is one of the major goals in a surface mount shop. It is more important in a high-volume shop than in a high-mix shop because most of the assembly time is spent in part placement. The reduction of placement cycle time at high-volume centers would have a higher impact than at our high-mix centers. HP owns many Fuji IP2 machines at our surface mount centers, one on each line. The Fuji IP2 machine is a fine-pitch pick-and-place machine capable of placing parts from reel, stick, and waffle feeders. It is considered a general-purpose pick-and-place machine because of its ability to place a wide range of parts. It has two heads, which alternately pick up parts from the feeders and place them on the panel. Each head has two holders, one with a fixed nozzle and one with an automatic nozzle. A fixed nozzle must be installed into the fixed holder before the machine starts placing parts. An automatic nozzle of size S, M, L, or LL can be picked up by the automatic holder from a nozzle station. The nozzle station has six nozzles: one S nozzle, one M nozzle, two L nozzles, and two LL nozzles. The S and M nozzles are shared between the two automatic holders of the two heads. Each automatic holder has its own L and LL nozzles; they are not shared between the two automatic holders.
Manufacturability of printed circuit boards is a fertile area for operations researchers to aid in productivity improvements for the electronics industry. A class of such problem is described, and a particular problem that arises from an application to a middle sized electronics firm is modeled and solved. The specific problem to determine the best sequence of insertion operations is formulated as a type of directed postman problem. An algorithm is developed for the problem that yields an optimal solution under certain conditions and approximate solutions, with a constant performance bound, when these conditions are relaxed.
Consider a set L of potential locations for p facilities and a set U of locations of given users. The p-median problem is to locate simultaneously the p facilities at locations of L in order to minimize the total transportation cost for satisfying the demand of the users, each supplied from its closest facility. This model is a basic one in location theory and can also be interpreted in terms of cluster analysis where locations of users are then replaced by points in a given space. We propose several new Variable Neighborhood Search heuristics for the p-median problem and compare them with Greedy plus Interchange, and two Tabu Search heuristics.
This paper proposes a methodology to improve the process time required for the component placement process of the printed circuit board assembly with an X-Y positioning table. The methodology is applied to a previously published subproblem as well as a real-life working board configuration. Even with high speed assembly machines placing in excess of 40000 components per hour (cph), process improvements are possible. Concentrating on the path planning portion is a valid method to increase efficiency, but as the problem approaches optimality, the planning process essentially becomes counterproductive due to the time and effort required. This paper presents an algorithm for system time improvement for use after a board placement path is established. In order to take advantage of the machine's capability to move the positioning table along each axis simultaneously, the board is physically rotated with respect to the positioning table. This paper steps through the theoretical development of a method to determine the proper angle of rotation, first for a regular 'rectangular' board configuration, and then for a more applicable 'general' configuration.
Collect-and-place machines represent one of the most popular types of placement machines in automated printed circuit board (PCB) assembly. For scheduling the operations of this type of machinery, a three-stage heuristic solution approach is presented. In the first stage, the feeders (component types) are assigned to locations in the magazine of the placement machine. In the second stage, based on the assignment of component feeders to magazine positions, the component placement sequence is determined. Apparently, for a collect-and-place machine, this problem is similar to the well-known vehicle-routing problem. Therefore, we adapt standard methods for vehicle-routing problems, namely savings heuristics introduced by Clark and Wright [Clark, G., & Wright, J. W. (1964). Scheduling vehicles from a central delivery depot to a number of delivery points. Operations Research Quarterly, 12, 568–581]. Finally, local search principles are applied in order to improve the feeder assignment and the component placement sequence obtained. Numerical experiments are performed in order to compare the performance of the various savings-based heuristics under different experimental settings.
This paper focuses on optimization problems faced in automated assembly of Printed Circuit Board (PCB). In order to optimize the throughput rate of these automated machines, the time taken for the pick and place operation for each board has to be minimized. In this paper, the component placement sequence problem is modeled as a Traveling Salesman Problem (TSP) and is optimized by Genetic Algorithms (GAs). In this study, components are placed on PCB where the process of pick-up and placement occurs starting from an empty multi-headed placement machine moving to pick up the components from the feeder magazine. The number of components to be picked and placed can range from a minimum of one to a maximum of four, depending on its contribution to minimize tour distance. The difference in size of components is handled by the tool change process, which brings the optimization problem closer to real machine situation. The paper suggests GA as a better alternative to other heuristic solution approaches such as Variable Neighborhood Search (VNS) and local optimum search. GAs are more promising as a global and robust method of solution and it permits a simpler mathematical model to solve a component assembly problem. The tool change factor, which was not incorporated in previous studies have been included in the present paper for the first time.
Consider computer numerically controlled placement machines which populate printed circuit boards with surface mounted components. These highly concurrent systems require a hierarchy of decision models to determine efficient machine setups and operational sequences so as to achieve effective throughput rates. The Feeder Assignment models developed here can be used to determine the particular stations in which each component fixture is to be attached to the carrier. Noninterference and space constraints may also need to be addressed. Several nonlinear objectives are developed to minimize "excess delay" due to carrier movements. These nonlinear formulations are then transformed to achieve equivalent Linear Mixed Integer Programming formulations. Carrier movements are often the slowest of the concurrent processes and therefore can cause significant deterioration in the overall system performance, if not adequately addressed and properly integrated into a hierarchical decision process. The methodology is illustrated by developing detailed assignment models for a dual delivery system. This system is highly illustrative of the difficulties and advantages arising in the modelling of these complex, concurrent systems. Adapting the general methodology to other machine designs and different manufacturing environments is also discussed.
This paper proposes a sequencing approach to develop a competent path for the printed circuit board assembly process. An efficient heuristic is developed that determines the component placement sequence, also referred to as the placement path. This NP-complete problem best resembles a Traveling Salesman Problem.(1) Thus, it is inherently difficult. The heuristic approach is tested against a previously published subproblem as well as a real-life working board configuration. This heuristic is intended to provide a good, feasible component placement sequence for the assembly of a batch of printed circuit boards with a machine configuration consisting of a moveable X-Y positioning table and a tape-and-reel sliding feeder rack. Even with high speed assembly machines placing in excess of 40000 components per hour (cph), process improvements are possible by increasing the efficiency of the planned placement sequence. This heuristic is developed to identify an improved component placement sequence in a reasonable computation time to allow for future implementation of the methodology in applied situations where time constraints are unavoidable.
In a previous paper, we studied printed circuit board (PCB) insertion problems when the number of different types of components are less than the number of reels in the feeder bank. In this paper, we consider a solution technique based on the clustering approach for PCB insertion problems with the limited capacity of the feeder bank. Simulation results are reported to illustrate the effectiveness of our method.
A new application of the genetic algorithm approach is introduced to solve printed circuit board assembly planning problems. The developed genetic algorithm finds the sequence of component placement/insertion and the arrangement of feeders simultaneously, for achieving the shortest assembly time, for three main types of assembly machines. The algorithm uses links (parents) to represent possible solutions and it applies genetic operators to generate new links (offspring) in an iterative procedure to obtain nearly optimal solutions. Examples are provided to illustrate solutions generated by the algorithm.
IntroductionIn multiobjective optimisation the aim is to find solutions that represent a compromise betweenthe various (sometimes conflicting) criteria used to evaluate the quality of solutions. A solutionx is said to be non-dominated with respect to a set of solutions S if there is no other solution in Sthat is, as good as x in all the criteria and better than x in at least one of the criteria. In Paretooptimisation the goal is to find a set of solutions that is representative of the...
The electronics industry relies heavily on numerically controlled machines for the placement of electronic components on the surface of printed circuit boards (PCB). This paper proposes a heuristic hiearchical approach to the problem of optimizing the throughput rate of a line of several of such machines, devoted to the assembly of a single type of PCB. A number of well-known NP-hard problems emerge, for which mathematical models and heuristic solution methods are developed. The approach is tested on a real-life problem, for which it is shown to perform well.
This paper considers the problem of positioning component fixtures on the carriers of computer, numerically controlled dual delivery machines used for populating printed circuit boards with surface mounted technology. This reel positioning problem (RPP) is one of a series of optimization problems that are critical for improving system productivity and realizing the full potential of concurrent operations. We formulate the RPP as a mathematical program and establish its complexity. Since the problem is NP-complete we focus on the development of heuristics. Our solution procedure was prompted by engineering considerations that included concerns for minimizing the changes in the carrier direction and total movement. We also present encouraging results with test problems. The method has been implemented and achieved 7 to 8% reductions in cycle time.
We consider the problem of minimizing the time needed to assemble a PCB using an automatic surface mounting machine equipped with a multihead turret. We solved the problem by using the problem with one head as an approximation to the multihead case. We devised a heuristic algorithm to solve the problem with one head and used it to solve the multihead problem. Computational experiences on some real world and randomly generated problems show that the algorithm for the one head problem also solves the problem with a multihead as well.
Printed circuit card assemblies form the core of a vast array of contemporary manufactured products. The technologies for assembling printed circuit cards require a hierarchy of complex decisions for grouping card types and processes, staging components at assembly machines, arranging feeders, and sequencing placement operations. This paper is motivated by the largely unmet needs of industrial process planners for computer aids. Our objective is to develop a framework for the printed circuit card assembly process planning problem and to assess the current state of the research on appropriate models and solution methods. We first provide an overview of the essential elements of printed circuit card terminology, assembly technologies, and assembly system operations. Then we propose a decision hierarchy, survey the published literature, and identify needs for future research.
Consider a computer numerically controlled placement machine for populating printed circuit cards with surface mounted components, which features two carriers for the delivery of components to the placement heads. The allocation models maximize the number of board completions available by a single allocation of components to the two carriers. This reduces the demand on the automated material handling system and the machine's operators for component replenishment. We consider the case where all components allocated are accessible and the case of a 'static pick sequence. ' The partitioning model minimizes the 'dead time' with respect to operation balance, excess rotation and the number of required nozzle changes, so as to support a high throughput rate. The utilization of vibratory, ski slope type fixtures for the delivery of components is also addressed.
This work considers the optimisation of component placement sequencing to improve the efficiency of theoretical multi-head surface mount device placement machines in printed circuit board assembly. We develop a Variable Neighbourhood Monte Carlo Search (VNMS), which employs a variable neighbourhood search technique with an Exponential Monte Carlo acceptance criterion. VNMS is a descent-ascent heuristic that operates on three sets of neighbourhood structures that are based on three different local search operators. The first two sets use a steepest descent and Exponential Monte Carlo local search, respectively whilst the third set uses a random 3-opt operator. The solution returned by a local search after exploring a neighbourhood structure will be accepted based on the EMCQ (Exponential Monte Carlo with counter) acceptance criterion. The novelties of the VNMS approach (in the context of VNS) are the concept of three stages of neighbourhood search and using an EMCQ acceptance criterion at the VNS level. The shaking procedure is only applied when the local searchers cannot find an improved solution. Results show that the VNMS consistently produces a good quality solution.
A printed circuit board (PCB) assembly consists of a circuit board and a variety of components in different shapes and sizes placed at specific locations on the board. They are used extensively in a variety of products by many industries today. These products include, for example, computer terminals, televisions, electronic instruments, and process controllers. There are many types and models of automatic machines available for placing components on the boards. The component placement operation consists of all steps necessary to remove a component from its packaging materials and mount it onto the PCB. The components are supplied either from a set of feeders, magazines or matrix trays. Because of the extreme accuracy required, automatic equipment is mandatory for all but the smallest production volumes.
In order to handle high and rapid production demands, printed circuit board (PCB) manufacturers have employed high-speed surface mount machines into their assembly lines. These machines have abilities of fast component placements, but provide challenges for process engineers to optimise the component placement sequences and feeder arrangements via effective planning. A computer program was developed based on operating concepts using genetic algorithm, to solve for various component placement sequencing planning of the high-speed chipshooter. Genetic algorithms are a class of general purpose search methods based on the concepts of genetic evolution and survival of the fittest. The program provides information on component placement sequences and feeder arrangements for optimal assembly times. Initial tests have shown that the size of the parent space affects the convergence of the solutions during iterations. Finally, comparisons of results have shown improvement over those previously obtained by other researchers.
This paper studies the operation of a surface mount technology (SMT) machine which basically consists of three main movable parts: an XY table containing a printed circuit board (PCB), ten rotating pick-and-place heads and a carriage feeder of reels. The machine inserts electronic components into defined positions on a PCB and the components are supplied from a set of reels each containing a tape of identical components. In the current production setup, the assembly plan comprising both the insertion sequence of components and the placement orders of the reels in the feeder is by human experience. Our study suggests that the problem is computationally difficult for its mathematical optimum with the insertion problem alone being NP-complete. We propose a heuristic solution technique of low computational complexity to find a better assembly plan comprising of the assembly sequence of electronic components and the placement order of the reels in the feeder. The algorithm developed combines the physical constraints of the SMT machine and a grouping concept that takes advantage of the natural structure of a PCB. Using multiple reels in the PCB insertion problem are also considered. Simulated results are reported on a set of illustrative data.
Reducing the time it lakes to place components on to printed circuit boards (PCBs) is a major robotic assembly objective. This paper explores a robot control approach featuring dynamic choice of pick-and-place points for retrieving and inserting components. In this concept, the component magazine and PCB tray both move to calculated points that minimize the overall robotic assembly time. Compared with that of another approach which employs fixed positions for retrieval and insertion, the new approach avoids robot waiting time. The same assembly sequence and component magazine assignment was used to test the difference between these two approaches. In both models, the PCB worktables and magazine are assumed to be mobile and to move at constant velocity between points. Experimental results showed that the proposed dynamic pick-and-place (DPP) approach is superior to the fixed pick-and-place (FPP) approach in nearly all cases.
Variable neighborhood search (VNS) is a recent metaheuristic for solving combinatorial and global optimization problems whose
basic idea is systematic change of neighborhood within a local search. In this survey paper we present basic rules of VNS
and some of its extensions. Moreover, applications are briefly summarized. They comprise heuristic solution of a variety of
optimization problems, ways to accelerate exact algorithms and to analyze heuristic solution processes, as well as computer-assisted
discovery of conjectures in graph theory.
Combinatorial optimization represents a wide range of real-life manufacturing optimization problems. Due to the high computational
complexity, and the usually high number of variables, the solution of these problems imposes considerable challenges.
This paper presents a tabu search approach to a combinatorial optimization problem, in which the objective is to maximize
the production throughput of a high-speed automated placement machine. Tabu search is a modern heuristic technique widely
employed to cope with large search spaces, for which classical search methods would not provide satisfactory solutions in
a reasonable amount of time. The developed TS strategies are tailored to address the different issues caused by the modular
structure of the machine.
Printed circuit board (PCB) assembly forms the core of a vast array of contemporary manufactured products. The requirements for higher component densities on PCBs, rigid functional specifications, smaller packages and greater reliability, move the electronics manufacturing industry towards automating PCB assembly. Owing to the complexity of PCBs, it becomes impractical to plan the assembly sequence manually. This paper presents a prototype genetic algorithms (GAs) enhanced planning system for surface mount PCB assembly. The prototype system uses GAs to generate the component placement sequence and the component-feeder arrangement for a rotary disk turret, concurrent pick and place SMD machine equipped with a time-delay function. The sequencing process is formulated as a multi-objective optimisation problem under constraints. A framework of the prototype system and the derivation of the multi-objective function are described. The prototype system was validated using examples gleaned from literature. Details of the validation are reported.
This paper addresses design to manufacturing (DTM) for electronics assembly from several different perspectives. First, a working definition for DTM is proposed, and the distinction is made between DTM and the more commonly known design for manufacturability. Following an overview of surface mount technology assembly processes, DTM information management is introduced in terms of its data requirements and underlying decision and planning problems. Evaluation criteria are discussed, and specific requirements for a state-of-the-art DTM system are highlighted. The experiences of one Motorola factory are presented in a brief case study, which covers process mapping, system design and benchmarking, and installation and configuration activities. Benefits of an efficient DTM sytem are discussed in terms of the improvements in production time, engineering time, and product or process quality. Finally, a summary of future trends for DTM is given.
Component placement is a critical and time consuming task in the assembly of surface mount printed circuit boards (PCBs). The past decade has witnessed the need for high speed, accurate, and repeatable placement procedures in the PCB assembly domain. At the same time, manufacturing engineers are faced with demands to reduce flow-time and increase throughput rates in order to increase productivity. A consequence of these trends has been the need to identify acceptable (possibly optimal) placement sequences during surface mount PCB assembly.The focus of this research was the identification of near optimal solutions for the placement sequence identification problem while considering machine and process constraints in a manufacturing environment. Expert (or knowledge-based) systems were used as the solution method for this problem. PROLOG, a popular language for artificial intelligence applications, was used in this research. The prototype knowledge-based system developed in this research identifies solutions in (almost) real-time.
The placement or onsertion of surface mounted components is an essential stage in printed circuit board assembly (PCBA). A reduction in production time of placement through efficient process planning will significantly increase total yield of the whole line. Addressed in this paper is the task of achieving high yield through determination of an optimal placement sequence given the constraints of feeder arrangement and machine design. A knowledge-based component placement system (CPS) which incorporates optimization algorithms is presented for a sophisticated but popular multi-head concurrent assembly machine. CPS has proven, in comparison to the machine proprietary algorithm, to be more practical and effective. CPS, a hybrid, which uniquely couples mathematical algorithms with a knowledge base, is a powerful tool in process PCB assembly.
The aim of this research is to develop a rule-based frame system for printed circuit board (PCB) assembly to generate the component feeder arrangement and placement sequence for concurrent chip placement machines. A knowledge base of frames, assertions and rules are used in the methodology to solve the PCB assembly process of SMT components. The system has been implemented using an AI programming environment, GOLDWORKS. A heuristic approach is used to minimize placement cycle time in PCB assembly. The objective of the solution method is to reduce theX-Y table displacement, movement and component feeder translation movement. Such a system is aimed at obtaining good solutions to the problem as illustrated by an example.