Production Planning and Control

Published by Taylor & Francis
Online ISSN: 1366-5871
Print ISSN: 0953-7287
Publications
Wafer fabrication plants (FABs) are arranged in a two-dimension (2D) layout, usually in a single floor. These layouts imply various constraints on the work-in-process (WIP) and the material handling systems. In contrast, automated storage/retrieval systems (AS/RS) arranged in a three-dimension (3D) layout aisle, where each aisle is served by a robotic arm that moves back and forth between the aisle's entrance point and its storage locations. This paper offers an AS/RS-based 3D layout for FABs. First, we formulate the general 3D layout design problem and develop a heuristic algorithm to solve it. Then, we evaluate the proposed layout comparative to its 2D counterpart. Finally, we test the proposed layout by simulating an actual data taken from the semiconductor industry and comparing the performance of 2D and 3D layouts, 30% throughput time reduction observed.
 
Membership functions of the set of the criteria ratings of food safety risk  
The food industry is under pressure to improve food product safety, implement efficient risk management and manage quality 'from farm to fork'. In this paper, a new risk assessment approach is proposed to perform structured analysis of aggregative food safety risk in the food supply chain by using the concepts of fuzzy set theory and analytical hierarchy process. It can function as a part of practical food safety management tool and help managers to understand how the risk changes and transfers in a supply chain. The methodology is tested in a British medium-sized cooked meat producer.
 
Flow chart for the procedure.
A simulation-based methodology is proposed to map the mean of steady-state cycle time as a function of throughput and product mix for manufacturing systems. Nonlinear regression models motivated by queueing analysis are assumed for the underlying response surface. To insure efficiency and control estimation error, simulation experiments are built up sequentially using a multistage procedure to collect data for the fitting of the models. The resulting response surface is able to provide a cycle-time estimate for any throughput and any product mix, and thus allows the decision maker to instantly investigate options and trade offs regarding their production planning.
 
Mixed-model assembly lines are of great practical relevance and are widely used in a range of industries, such as the final assembly of the automotive and electronics industries. Prior research mainly selected and discussed isolated problems rather than considering the whole planning process. In this article mixed-model production planning is decomposed into five steps: initial configuration of the line, master scheduling, reconfiguration planning, sequencing and resequencing. The paper reviews and discusses all relevant planning steps and proposes general planning instruments as well as formalized decision models for those steps, which have not been thoroughly investigated in the literature thus far.
 
CLASS is a production scheduling system, that is designed to function in either a stand-alone manner, or in conjunction with an MRP system. MRP systems innately do not have 'closed loop' capability in the sense of being able to produce master schedules and order releases that are consistent and that respect capacity constraints. True closed loop performance requires detailed scheduling. In addition to interfacing with MRP systems, CLASS in designed to produce schedules that can be used in conventional shops or can be downloaded to automated facilities. The design goals for the system, its internal architecture, and its role in manufacturing control systems are described. The modelling and decision capabilities of the system are briefly discussed. The system has been used to produce a schedule for an automated facility, and is under test or implementation at other sites.
 
-Indicators of collaboration
Collaborative networks are typically assumed to bring clear benefits and competitive advantage to the participating members. However, the identification and characterisation of objective and measurable collaboration benefits is an important element for the wide adoption of this paradigm. Departing from a brief categorisation of the intuitive advantages of collaboration, this paper introduces an approach for the analysis of benefits in collaborative processes, introducing a number of performance indicators. The potential application of the indicators derived from this analysis is then discussed in the context of a virtual organisation's breeding environment. Finally, experimental results based on data from two existing collaborative networks are presented and discussed.
 
An attempt is made in this paper to study the available literature in FMS and structure them in a synoptic framework. The purpose of this study is to capture the varied perspectives of the industries and researchers and to provide some conceptual directions for integrating into the planning, design and implementation aspects of such systmes.
 
Three levels of autonomy levels  
System Configuration
Common Dispatching Rules
Expected Utility Values for Four Chosen Jobs for Machine y
System Utility Calculations for Machine y
Planning and control systems for highly dynamic and uncertain manufacturing environments require adaptive flexibility and decision-making capabilities. Modern distributed manufacturing systems assess the utility of planning and executing solutions for both system goals (e.g. minimize manufacturing production time for all parts or minimize WIP), and local goals (e.g. expedite part A production schedule or maximize machine X utilization). Sensible Agents have the ability to alter their autonomy levels to choose among a set of decision models in order to handle the differences between local and system goals. In this paper, Sensible Agents are applied to a production planning and control problem in the context of job shop scheduling and decision model theory. Sensible Agents provide for trade-off reasoning mechanisms among system and local utilities that are flexible and responsive to an agent's abilities, situational context, and position in the organizational structure of the system. Co...
 
General architecture of a holon [4] 
Additional Production Planning and Control Needs [66] 
Typical Manufacturing Control Hierarchy
Holonic Control Implemented in Conventional Infrastructure [81]
The field of Holonic Manufacturing was initiated in the early 1990's to address the upcoming challenges for manufacturing operations in the 21 century. It is intended to support for highly responsive organisations by providing a modular building-block or "plug and play" capability for developing and operating a manufacturing production system in order to support a more responsive organisation. The holonic approach can be viewed as an alternative to more hierarchical operations management methods such as those based on Computer Integrated Manufacturing (CIM). Since 1990, an increasing amount of research has been conducted in holonic manufacturing over a diverse range of industries and applications, with a strong emphasis on how holonic systems will perform the different planning and control functions required to manage a production operation. The planning and control work to date has, however, been focussed on specific problem formulations and solution strategies. The intention of this paper is to provide an overview of the use of holonic manufacturing concepts in production planning and control which is accessible to both practitioners and researchers in the area. The aims of the paper are: . To clearly define what is meant by a holonic manufacturing system and to demonstrate the relevance of its development to production planning and control.
 
This paper aims to explore the purchasing function on behalf of the provider, when the purchasing takes the form of a request for proposals (RfP) from the client. A methodology for handling the bidding process is presented, illustrated by a case study from the IT sector. The proposed methodology places risk as a factor for the selection of the best and final offer of the provider in addition to the traditional decision factors: delivery time, product cost and performance. The method is supported by a structured corporate memory and a decision support system based on the analytical hierarchy process.
 
The performance controllability principle of the ECOGRAI approach.  
The control structure and the physical system modelling for building 25.
Coherence panel.  
The specification sheet.  
The requirement for a performance measurement system is essential in order to know the status of the production system and then to improve its control. Focused on research on the control of production systems for 20 years with the development of GRAI methodology, the LAPS/GRAI of University Bordeaux 1 worked for more than 10 years on the definition and the implementation of performance indicator systems through the development of ECOGRAI method and on the aggregation of performance. This paper presents an application of the ECOGRAI method to a workshop inside an aeronautical subcontracting company close to Bordeaux. The first part of the paper will be dedicated to a short presentation of the ECOGRAI method. In particular, we will present six phases of the structured approach and the main tools which are used in the method: the GRAI grid, the coherence panel and the specification sheet and the identity card of the indicators. In the second part, we will present a test case. First, we will present the context of the test case and the objectives that we had to meet. Then we will present the models of the control system and of the physical system through the GRAI grid and actigrams. We will show how we proposed to model the global control of the company and the detailed control of each workshop. Then, we will focus particularly on the way we have identified the performance indicators, based on the objectives and decision variables of the GRAI grid. We will also show how we solved the problem of aggregation of performance in relation to the coordination of decision-making. In the third part, we will detail how we ensured that these indicators were adapted to the control of the workshop and how we ensured their consistency. Finally, we will show to what extent the implementation of the coherent performance indicator system had an impact on the organization and the running of the workshop.
 
Time sequence for actions under the social perspective 
Time sequence for actions under the organizational perspective 
Ageing societies face tough challenges namely in terms of their ageing workforce and finding new models to accommodate current demographic trends. The application of the collaborative networks paradigm, and a new generation of collaboration-support platforms and tools, is a promising approach to supporting active ageing, and facilitating better use of the talents and potential of retired or retiring senior professionals. As such, collaborative networks can contribute to demographic sustainability. In this context, the results of a roadmapping initiative addressing the implementation of a new vision for extending professional active life are introduced. To support the aimed vision, a strategic research plan for the development of a new digital ecosystem, covering the social, organisational, and technological perspectives, is proposed. A large number of stakeholders coming from different backgrounds contributed to the design and validation of this roadmap.
 
To manage the emerging problems of companies in today's economical surroundings a new thinking in control is required. On the level of field control a step to distributed systems based on distributed intelligence is the state of the art. But on the above levels of control, central and therefore inflexible systems are predominant. This leads to rigid control structures unable to react on system changes with respect to machinery and product programme in a fast and cost-saving way. The PABADIS approach aims in solving the mentioned problems by introduction of horizontal as well as vertical flexibility into the control structure. This flexibility is reached by using mobile and residential agents to establish distributed intelligence on the level of manufacturing execution systems and integration of distributed intelligence on the field control level.
 
During the realization of the CAESAR planning games, which has been supported by the European Leonardo da Vinci Programme, the use of modular planning games within a global scenario has shown to be very effective in concisely relaying educational content from the area of production management. In particular the close-to-reality situations have proven, time and again, to be highly motivating for seminar participants. In order to improve the transferability of acquired knowledge into practise, the ifab-Institute of Human and Industrial Engineering of the University of Karlsruhe has further developed the INSIGHTS-PPC planning game for production planning and control, in such a way that the planning tasks to be tackled are set in direct relation to market similar repercussions. This is realized in a new market share model. The market share model will be explained, paying particular attention to the practical consequences which come along with the implementation of such a model. Despite the potential of the developed market share model and the positive feedback from seminar participants there is a risk of the participants being diverted from the intended educational content, that of production logistic fundamentals and techniques, and of them perceiving the focus of the seminar as a relaying of market mechanisms.
 
AIn this paper, a genetic algorithm model for scheduling manufacturing resources is developed for the case when there is only one process plan available per job, hence there is no routeing flexibility. The scheduling objectives considered are minimizing the makespan and mean flow time. Genetic algorithms design issues are discussed and the working of the employed genetic operators is explained in detail. Parameters for the genetic algorithms used for single process plan scheduling SPPS problems are set through extensive experimentation. Finally, the genetic algorithms approach is compared with several other approaches in terms of optimality of solution and computAuthors: ing time. It was observed that in most cases the genetic algorithms approach performed better than other approaches both in terms of finding an optimal or near optimal solution as well as computing time.
 
In the current global business environment, it is very important to know how to allocate products from the producer to buyers (or distributors). If products are not appropriately distributed due to absence of an effective allocation policy, the producer and buyers cannot expect to increase customer satisfaction and financial profit. Sometimes some buyers can order more than the actual demand due to inappropriately forecasting customer orders. This is the big obstacle to the effective allocation of products. If the producer can become aware of buyers' actual demands, it is possible to realise high-level order fulfilment through the effective allocation of products. In this study, new allocation policies are proposed considering buyers' demands. The back propagation algorithm, one of the learning algorithms in neural network theory, is used to recognise actual demands from the previous buyers' orders. After excluding surplus demands included in buyers' demands, products are allocated to buyers according to one of the existing allocation policies depending on the company's decision. In the numerical examples, new allocation policies reducing buyers' surplus demands outperform previous allocation policies with respect to average amount of backorder.
 
In a previous work (Chandrashekar, A., and Gopalakrishnan, M., Purchase cards and inventory control - an analytical framework. Prod. Plan. & Cont., 2005, 16(5), 437-443) we developed a framework for comparing the use of 'purchase cards' (P-cards) to order merchandise directly from a supplier versus obtaining direct credit from the supplier. We illustrated for the single-item case, that there exists a critical ordering cost such that the P-card can be used if and only if the actual cost of ordering using P-card is less than this critical value. In this paper we extend this framework for determining the optimal replenishment quantity for multi-item ordering under the conditions of permissible delay in payment, a budget constraint, and permissible partial payment at a penalty. The analysis indicates that it is more economical for the purchaser to make entire payments even when the interest earned is greater than the interest charged. This note reflects reality more accurately.
 
A participatory and integrative approach was applied to improve the productivity and ergonomics of the assembly lines in two factories, producing magnetic stop valves and office furniture, respectively. Main elements of the approach are the active participation of the company and the integration of two disciplines: assembly engineering and ergonomics. The aims were the analysis of bottlenecks and the definition of solutions. To analyse the main bottlenecks, the assembly process scheme was analysed in close cooperation with company representatives, specific observations were performed on the work floor, and the body postures and the forces on the body measured. To evaluate promising solutions a gaming technique (Ergomix) was applied mixing CAD-drawings of work places with real workers. The approach proved to be successful in the determination of bottlenecks in productivity and ergonomics (regarding the supply of components, the accumulation of materials, body postures, pushing and lifting forces), and the definition of promising solutions (e.g. new assembly concepts, height adjustable working tables, new organization of tasks, and new product design). The potential effects were estimated to be significant: e.g. gains in productivity of 15-20% and substantial reductions of time spent in risky body postures.
 
In sequencing problems for mixed-model assembly line in JIT production system, the Goal Chasing method (GC) is widely used for parts used leveling goal. The difference in assembly time of each product is not taken into consideration in the Goal Chasing method. Assembly time usually varies with product types. In recent years, the Time-Based Goal Chasing method (TBGC) has been proposed. The advantage of TBGC is to consider the influence of different assembly time of each product and idle time in production period. TBGC, however, has been only applied to single work station problems. In this paper, TBGC is applied to an assembly line problem with multiple work stations. Furthermore, the sequencing method and use of Simulated Annealing (SA) or Local Search (LS) for this problem are proposed.
 
Remanufacturing control problem
a and b. Evolution of the Multi Hedging Point Policy (z 1 *, z 1 *) and of the corresponding cost J* for different availability case.  
a.  
We consider the control of a remanufacturing system executing capital assets repair and remanufacturing in a single system. It is assumed that the production system responds to planned demand at the end of the expected life cycle of each individual piece of equipment and unplanned demand triggered by a major equipment failure. The difficulty of controlling this type of production resides in the variable nature of the remanufacturing process, the possibility of using different replacement and repair strategies, and the probabilistic availability of spare parts. We formulate this problem as a multi-level control policy based on inventory thresholds triggering the use of different execution modes and propose a suboptimal policy. Determination of the control policy parameters is based on parameter optimisation of analytical expressions and a simulation approach was used to validate our analytical results. Hence, we show that we can provide a feasible control policy for repair and overhaul systems under probabilistic replacement parts availability.
 
In this paper, we study the problem of selecting the optimum production batch size in multistage manufacturing facilities with scrap and determining the optimal amount of investment. We analyse the effect of investment for quality improvement on the reduction of the proportion of defectives, and the effect of this reduction on processing cost, setup cost, holding cost, and profit loss. The quality characteristic of the product manufactured is assumed to be normally distributed with a mean equal to the target value. The purpose of the investment is to reduce the variance of the quality characteristic and hence the proportion of defectives. The model assumes known demand, which must be satisfied completely, scrappage at each stage and profit loss due to scrap. Using this model, the optimal values of the production quantity and the proportion of defectives for minimizing the total cost are obtained. The optimal investment is then obtained using the relationship between the investment and the proportion of defectives.
 
There are several ways for a manufacturer to cope with demand uncertainty, e.g. inventories, capacity and cash. Among these, this study focuses on the second one, the capacity, especially on the problem of investing in flexible facilities and enhancing their utilization via demand management. In a supply chain, demands that an upstream firm (supplier) faces are the purchase orders from the downstream members (buyers). We analyse the impacts of buyers' order batching on the supplier's demand correlation and capacity utilization in a simple branching supply chain, where a supplier does business with two buyers whose market demands are correlated. Our results show that: (i) a supplier whofacesa smaller demand correlation coefficient (i.e. closer to-1) would invest more in flexible facilities; (ii) an increase in order lot size mitigates the correlation of purchase orders; and (iii) a supplier whose facilities are flexible would prefer frequent orders with smaller lots only when market demands are highly negatively correlated. This means that even suppliers whose facilities are flexible would rather prefer infrequent orders with larger lots in the presence of positively correlated demands. Additionally, some managerial implications are discussed.
 
Collaboration in supply chain networks has been one of the major fields of work in global logistics since the late 1990s. The concept of Supply Chain Management is thus emerging as the main focus of research and education at universities as well as in industry. However, the crucial hurdle when starting a logistics partnership with several partners is creation of the necessary common understanding of the inter-company relations and interdependencies in logistics systems, whether for mere single customer order fulfilment or even integrated collaborative planning processes. The 'Beer Game,' a training exercise developed at MIT in the early 1960s, offers an easy-to-use tool for creating a common awareness of the fundamental issues in a supply chain. One of the great benefits as well as one of the pitfalls of the original Beer Game is its very simplicity. Mostly only the 'Bullwhip Effect' can be demonstrated, while the effects of supply chain optimization strategies and the possible impacts of new strategies cannot be shown. For this reason, the idea of simultaneously playing the game using simulation software was conceived. Various supply chain scenarios, modelled and applied in simulation software, will be presented. In summary, the paper gives an overview of the model, the approach, and experience gained in using the simulation model in training sessions.
 
The study presents a comprehensive analysis of the efficiency over time of five steel plants pertaining to one of the largest private groups in Italy. In particular, the paper proposes a new technique for plant performance measurement that is able to help the management in formulating manufacturing strategies according to the performance measurements usually available in industrial environments. The analysis is carried out by the methodology of Data Envelopment Analysis (DEA), taking advantage of several improved solutions proposed in the literature adopted to augment the discriminating resolution. Results obtained are summed up by means of suitable cluster analysis. Finally, thanks to the dual formulation of DEA, a technical and economic analysis is proposed with reference to the productive units identified as inefficient. The technique proposed was successfully applied to the industrial case of reference and it can be easily extended to every manufacturing context.
 
This paper presents an approach to the modelling and control phases involved in a cooperative process of design and management of the manufacturing systems. Modelling the evolution of the production flow, in the different sections of the system, is based upon the use of the bondgraph methodology in order to reach the state formalism which constitutes one of the modern representations of automation. The class of the systems studied ranges from continuous systems to discrete systems, which can be represented by a continuous approach according to the level of approximation required. The first part of this paper is dedicated to the development of generic models associated with the various basic entities of the manufacturing systems. Then, the bondgraph model of any system is obtained by assembling generic models in relation to the implementation of the means of the studied system, thus guaranteeing a representation which is quite close to the engineering sketches. Finally, switching to the state equation is performed systematically with the easiness provided by this formalism while taking into account the causality principle. An application, involving most of the elementary models developed, concludes the paper.
 
Re-engineering global business processes requires innovative methods for inter-organizational learning. This article describes and analyses an experimental telepresence process simulation that was applied to develop and train the cross-site New Product Introduction process of a global telecommunication company. Interactive, real-time audio and video connections over the Internet supported the process-oriented discussion between two groups in distant locations. Identical visual process charts and other information, projected on the walls of the two auditoriums, helped the two teams to discuss and understand the process. Audibility of the discussion was crucial for learning, but the visual 'talking heads' of the participants distorted concentration. Facilitation at both ends and local simulation periods smoothed the interaction and the imbalances between the locations. The simulation achieved positive effects in immediate learning and in motivation for change, although the telepresence caused some limitations. The ultimate goal, the feeling of real presence, was not reached. But when time gets more expensive, and travelling less preferable, telepresence simulation can be a feasible group-mode e-learning method for inter-organizational learning.
 
Capacity planning is a critical element of any successful production planning and control system. A method of rough-cut capacity planning is developed, based on the bill-of-resources approach, that can be used to plan for capacity required for firms in a remanufacturing including overhaul repair operations environment. The modified bill-of-resources approach developed takes into account two major stochastic elements inherent in this environment; probabilistic material replacement factors and probabilistic routing files. A detailed example from an actual repair overhaul operation is presented to illustrate the technique.
 
The ability of a company to finance viable projects depends on the availability of funds, and this too is a function of time, interest rate and risk factors among others. Factors such as these would lead to limited fund availability, which would necessitate capital rationing. Linear/integer programming and profitability index are often used to tackle this problem for optimal solution. A third approach utilizing a modified internal rate of return (IRR) is proposed. To overcome the difficulty usually encountered in calculating IRR, a small program coded in BASIC is presented. Even though discounting the cash outflows beyond the initial year should have been ideal in the linear programming formulation, this paper casts doubts as to the validity of the solution derived from it, as different discount rates seem to produce very conflicting results from the same set of investment options. This is also applicable to profitability index. While efforts are being made to correct these lapses, the modified IRR model has been found useful in arriving at an optimum solution both for the single-period as well as for the multi-stage situation.
 
Past research has shown that it is possible to simultaneously achieve the setup efficiencies of traditional cellular manufacturing systems and the routeing flexibility of a job shop by viewing cells not as permanent, physical structures, but as temporary, 'virtual' entities. This research demonstrates that the advantages of virtual manufacturing cells can be obtained over a range of part family configurations. In particular, virtual cellular manufacturing is robust to changes in the number and size of families being processed. Further, the research shows that the benefits can be obtained under setup conditions impartial to a family-oriented part environment.
 
The modularization characteristic curve. 
Comparisons of different supply-chain structures. 
The effects of mass customization. 
This paper focuses on three interrelated and complementary strategies for managing supply-chain integration: mass customization, postponement and modularization. While the goal of mass customization is to produce customized goods at low costs, postponement strategy focuses on delaying customization as close to the customers as possible. The extent of customization and postponement of products is rooted in modularization of product architecture designs. Product customization can take place either based on a common platform with additional options or based on combining and mixing-and-matching modules to achieve different product characteristics. It also requires a supply-chain strategy to facilitate assembly, logistics and outsourcing decisions. We analyse mass customization, postponement and modularization strategies through a 'modularization characteristic curve', which is shaped by two variables: opportunities for modularization and interface constraints, which represent the aggregate effect from interface compatibility effects, component customization, value inputs and supplier-buyer interdependence. Managerial implications of these strategies are also discussed.
 
This paper addresses the issue of parts and materials commonality when scheduling disassembly. In a disassembly environment, inventory management is complex due to the presence of multiple demand sources at the component level of the product structure. Commonality introduces a new layer of complexity by creating alternative procurement sources for the common component items. A novel scheduling algorithm is presented, followed by an example.
 
It is a hard process to modify master production schedule in a firm having various types of products and final assembly groups. Therefore, the system should automatically make the needed and proper modifications when they are input. Besides, it is of great importance to the firm to remove the errors of demand forecasting so as not to reject customer orders. In this study, a rule-based system for an electromechanical manufacturing company, which is able to rearrange the master production schedule, is presented. This system will provide considerableeasinessofusein themaster production scheduling activities.
 
Different views on the goodness of varying approaches to and concepts of planning and control in logistics have led, and continue to lead, to highly charged debates. Through argumentation that is often polemic, one concept is played off against the other. Moreover, the introduction and implementation of software supporting the concepts (so-called PPS packages or logistics software) is often judged to be costly, tediously time consuming and restrictive with regard to business processes. In an effort to contribute to more objective discussion, this paper shows that four classes of concepts on planning and control have become established over recent decades: the MRPII (ERP) concept, the just-in-time/kanban concepts, variant-oriented concepts and process-oriented concepts. These varying concepts are then examined dependent upon characteristic features of planning and control, and dependent upon the branch of industry. This paper shows that, as a consequence of practice, several concepts of planning and control may and have to be applied in an enterprise.
 
Date-related system failure for many organizations may become reality at Year 2000. No matter how hard a company has been trying to fix the system errors, there is no guarantee for problem free systems. Y2K-induced failures may cause loss of business, legal and safety issues. A contingency plan therefore is necessary. This paper discusses a contingency planning process, including planning principles, methodology and plan management.
 
DEWIP is a manufacturing control system for job shop environments aiming at achieving short and reliable lead times by establishing WIP control loops between the manufacturing work centres. The paper describes the mode of function, the setting of parameters and simulation results of the new manufacturing control system. The setting of parameters is done with the aid of the funnel model and the theory of logistic operating curves, both developed at the Institute of Production Systems at the University of Hanover. The simulation is conducted using industrial data and makes it possible to assess DEWIP with regard to lead times, WIP level, performance and schedule reliability. DEWIP is compared both with an uncontrolled process and with the manufacturing control systems Load oriented order release (LOOR), Conwip and Polca. The results suggest that DEWIP and the models employed for the setting of parameters are suitable for job shop production and therefore offer a valuable alternative to prevailing centralized manufacturing control systems.
 
In the last decade, the potential of mobile business for a great variety of areas within production and operations management, for instance supply chain management, has been widely discussed. However, the integration of mobile business and maintenance has been neglected so far. In the course of the evolved mobile business era, the question how maintenance can be supported by mobile devices in order to generate competitive advantages is an important issue since maintenance plays a strategic role in manufacturing companies. This paper deals with the question of how maintenance-in particular the improvement of maintenance by total productive maintenance-can be supported by mobile business. The five pillars of total productive maintenance are used as a basis for the application areas of mobile devices. The paper discusses the potential of mobile devices in the different pillars. The main conclusion is that mobile devices can be used to improve total productive maintenance in different ways in order to increase the overall equipment effectiveness. Additionally, the functionality of a maintenance hub is briefly shown.
 
A recent article in this journal outlined strategies for the replacement of components and sub-assemblies when considering hazard rates and for capital intensive equipment when considering influences such as increasing maintenance costs, inflation, discount rates, and depreciation. We expand upon this second analysis, concerning the replacement of capital intensive equipment with net present value (NPV) analysis, by guaranteeing that all feasible options are evaluated when determining the optimal strategy. This requires assumptions about future challengers (potential replacement equipment over time) and the time horizon for analysis. We illustrate different solution approaches based on the given assumptions.
 
The complexity of modern semiconductor manufacturing processes and the need for realistic considerations when modelling their short term availability and reliability make it very difficult to use analytic methods. In this paper, we review the process of preventive maintenance planning and shop level maintenance scheduling in semiconductor fabrication facilities (fabs). We show that the use of Monte Carlo continuous time simulation modelling to improve preventive maintenance scheduling allows the assessment of alternative scheduling policies that could be implemented dynamically on the shop floor. Using a simulation model, we compare and discuss the benefits of different scheduling policies on the status of current manufacturing tools and several operating conditions of the wafers production flow. To do so, we estimate measures of performance by treating simulation results as a series of realistic experiments and using statistical inference to identify reasonable confidence intervals.
 
The problem of scheduling in a flowshop, where setup, processing and removal times are separable, is considered with the objective of minimizing makespan. Heuristic algorithms are developed by the introduction of simplifying assumptions into the scheduling problem under study. An improvement method is incorporated in the heuristics to enhance the quality of their solutions. The proposed heuristics and an existing heuristic are evaluated by a large number of randomly generated problems. The results of an extensive computational investigation for various values of parameters are presented.
 
The operational characteristics and management logic of repetitive production greatly differ from those of intermittent manufacturing. Notwithstanding this, there are still few packages specifically developed for manufacturing planning and control in repetitive contexts, and often those that are available have been derived from adaptations and or extensions of packages originally designed for intermittent manufacturing. Starting from an in-depth examination of three cases, a framework for the analysis of the characteristics of manufacturing planning and control MPC systems utilized in repetitive contexts has been developed. The proposed framework includes all three basic production control sub-systems, i.e. planning, inventory control and shop floor control. Based upon this framework the main functions that characterise production planning and control systems for repetitive manufacturing are examined. Among the most important functions described are: production planning with 'control orders' and 'flow orders' versus 'work orders', picking lists for 'floor stocks by daily rate' versus 'work centre by work order', resources and materials consumption by 'backflushing' versus 'work order'.
 
This paper presents a heuristic algorithm for finding a good solution for the sequence-dependent lot scheduling problem. Unlike available methods, the algorithm eliminates the need for creating new artificial problems and implementing feasibility tests. It also eliminates the tedious task of translating setup relationships into a mathematical programming formulation. The result is a conceptually simple solution technique that is practically motivated and easily implemented for use on the shop floor. Comparison of algorithm performance with published results demonstrates the efficacy of the approach.
 
Example process structure.
Shortage correction pseudocode.
Sample menu from automated production planning tool.
Product structure diagram for antenna remanufacturing case study.
This paper presents a methodology for production planning within facilities involved in the remanufacture of products. Remanufacturing refers to the process of accepting inoperable units, salvaging good and repairable components from those units, and then re-assembling good units to be re-issued into service. These types of facilities are common, yet many suffer from the unpredictability of good and repairable component yields, as well as processing time variation. These problems combine to make it extremely difficult to predict whether overall production output will be sufficient to meet demand. Low yields of key components can lead to shortages which require the facility to purchase new components for legacy systems, often with long lead times, thus causing overall delays. The approach developed here is a probabilistic form of standard material requirements planning (MRP), which considers variable yield rates of good, bad, and repairable components that are harvested from incoming units, and probabilistic processing times and yields at each stage of the remanufacturing process. The approach provides estimates of the expected number of remanufactured units to be completed in each future period. In addition, we propose a procedure for generating a component purchase schedule to avoid shortages in periods with a low probability of meeting demand. The proposed methodology is applied to an antenna remanufacturing process at the Naval Surface Warfare Center (NSWC). In this case study the proposed methodology identifies a potential shortage of a key component and suggests a corrective action to avoid significant delay in the delivery of remanufactured units.
 
Measurement model 
Baseline comparisons
Hypothesised structured model 
The purpose of this article is to examine the role of the alignment between technological innovation effectiveness and operational effectiveness after the implementation of enterprise information systems, and the impact of this alignment on the improvement in operational performance. Confirmatory factor analysis was used to examine structural relationships between the set of observed variables and the set of continuous latent variables. The findings from this research suggest that the dimensions stemming from technological innovation effectiveness such as system quality, information quality, service quality, user satisfaction and the performance objectives stemming from operational effectiveness such as cost, quality, reliability, flexibility and speed are important and significantly well-correlated factors. These factors promote the alignment between technological innovation effectiveness and operational effectiveness and should be the focus for managers in achieving effective implementation of technological innovations. In addition, there is a significant and direct influence of this alignment on the improvement of operational performance. The principal limitation of this study is that the findings are based on investigation of small sample size.
 
Demand forecasting consists of using data of the past demand to obtain an approximation of the future demand. Mathematical approaches can lead to reliable forecasts in deterministic context through extrapolating regular patterns in time-series. However, unpredictable events that do not appear in the historical data can make the forecasts obsolete. Since forecasters have a partial knowledge of the context and of the future events (such as strikes, promotions) with some probability, the idea presented in this work is on structuring the implicit and the explicit knowledge in order to easily and fully integrate it in final forecasts. This article presents a judgemental-based approach in forecasting where mathematical forecasts are considered as a basis and the structured knowledge of the experts is provided to adjust the initial forecasts. This is achieved using the identification and classification of four factors characterising events that could not be considered in the initial forecasts. Validation of the approach is provided with two case studies developed with forecasters from a plastic bag manufacturer and a distributor acting in the food market. The results show that structuring the expert knowledge through the identification of factor-related events leads to high improvements of forecast accuracy.
 
Whilst there is little doubt that the adoption of Internet technology can provide manufacturing companies with unprecedented commercial opportunities, evidence to date suggests that the majority of the manufacturing industry and in particular the small- to medium-sized enterprises, are not embracing the technology as quickly as they perhaps should. This paper draws on the findings from a number of published surveys to ascertain why smaller manufacturing organizations are failing to adopt Internet technology. A further analysis of the growing body of literature documenting the e-commerce experiences of organizations in a variety of industries suggests that many of the issues identified are not unique to a particular sector and contrary to expectations, the manufacturing sector is better positioned than most to adopt and exploit Internet technology. The paper concludes with recommendations for those in manufacturing concerned with developing an e-capability.
 
Scheduling Coordination in a supply chain with a of Push/Pull system mechanism
Modeling supplier processes (case A and B)-Kanban and Periodic Replenishment Policies
Results in a Stochastic Universe for case A: Evolution of inventory levels
In an environment of mass customization where demand information can be placed in advance with sequencing orders, the question of the best use of this information arises in a supply chain. This situation led the authors to analyze the efficiency of current mechanisms of scheduling coordination when suppliers' processes are not completely reliable. Policies such as periodic replenishment or the kanban system, characterized by a replacement of the items to consume, cannot be exploited effectively with the current rules. This paper presents and justifies new scheduling coordination rules allowing synchronous production in an unreliable environment. This new approach has been benchmarked in the automotive industry as an appropriate method to avoid stockouts and decrease the safety stock. oui
 
Multi-agent architecture for integrating steel casting and milling.
Contract Net Protocol for inter-agent cooperation.
Agents interface. 
No This paper presents a case study on the use of multi-agents for integrated dynamic scheduling of steel milling and casting. Steel production is an extremely complex problem requiring the consideration of several different constraints and objectives of a range of processes in a dynamic environment. Most research in steel production scheduling considers static scheduling of processes in isolation. In contrast to earlier approaches, the multi-agent architecture proposed consists of a set of heterogeneous agents which integrate and optimize a range of scheduling objectives related to different processes of steel production, and can adapt to changes in the environment while still achieving overall system goals. Each agent embodies its own scheduling model and realizes its local predictive-reactive schedule taking into account local objectives, real-time information and information received from other agents. Agents cooperate in order to find a globally good schedule, which is able to effectively react to real-time disruptions, and to optimize the original production goals whilst minimising disruption carried by unexpected events occurring in real-time. The inter-agent cooperation is based on the Contract Net Protocol with commitment
 
Partner selection is a fundamental issue in supply chain management as it contributes significantly to overall supply chain performance. However, such decision-making is problematic due to the need to consider both tangible and intangible factors, which cause vagueness, ambiguity and complexity. This paper proposes a new fuzzy intelligent approach for partner selection in agile supply chains by using fuzzy set theory in combination with radial basis function artificial neural network. Using these two approaches in combination enables the model to classify potential partners in the qualification phase of partner selection efficiently and effectively using very large amounts of both qualitative and quantitative data. The paper includes a worked empirical application of the model with data from 84 representative companies within the Chinese electrical components and equipment industry, to demonstrate its suitability for helping organisational decision-makers in partner selection.
 
Generalized flexible flow line (GFFL) is a scheduling environment comprising several machine banks which the products visit in the same order but can skip some machine banks. The type of machines in a bank can differ but they are suitable for performing the same manufacturing tasks. To change one product to another demands a set-up operation of the machine. This paper describes several scheduling algorithms for the GFFL problem. The overall structure of these algorithms is similar, consisting of machine allocation and sequencing phases. The algorithms have been integrated into an interactive production scheduling system for electronics assembly. Sample cases are used to illustrate the operation of the system in practice.
 
In this paper an approach to model-based batch process quality control and optimization using flexible production recipes is presented. Unlike the fixed recipes traditionally used in process industries, a flexible recipe depends on externally provided data from the process as well as the market. In order to manipulate a flexible recipe in a proper and convenient way, the information system FRIS—containing modules for experiment design, recipe initialization and correction, on-line process and off-line experiment evaluation, model development and recipe improvement—is being developed. Each of these functions will be discussed further.
 
Top-cited authors
Marco Taisch
  • Politecnico di Milano
Marco Garetti
  • Politecnico di Milano
Vikas Kumar
  • University of the West of England, Bristol
Arturo Molina
  • Tecnológico de Monterrey
David Romero
  • Tecnológico de Monterrey