International Journal of Simulation Modelling

Print ISSN: 1726-4529
Publications
In this paper we presented an overview about modern visualization approaches in the field of telerobotics and interactive robotics simulation. We have made a comparison presenting the advantages and disadvantages between the (binocular) anaglyph and the (monocular) motion stereo methods in our robot simulator application. At this time, our team in the Mobile- and Microrobotics Laboratory is in the very center of experimenting with some of the great amount of available devices supporting advanced monocular and binocular 3D techniques to find one that is the nearest to our requirements. From this aspect we presented the RobotMAX simulator, which is currently under development at our laboratory: it will integrate robotics design (advanced visualization, driving mechanisms- and kinematical structure planning, sensor layout optimalization, etc.) and interactive control with the effective hardware-in-the-loop testing methodology into a modern simulation framework. Our mobile robot simulation project has another objective also: RobotMAX is aimed be a new research and education platform for the next generation of students in the field of mobile robotics and 3D imaging in our department at BUTE. 59
 
The simulation with multi-agent controller, presented in Fig. 11, proves the validity of this approach for minimizing contacts into the ducts, furthermore it can be extended to the case where the ducts are not rigid but elastically, or visco-elastically deformable, as in reality (K?hl, C. 2003) (K?hl, C & Dumont, G. 2005). A sigmoid untwisting, that is a classical examination in coloscopy, has been reproduced for testing the simulator. The main part of this examination is done when the endoscopic device is withdrawed. The medical practitioner try to reach the ileocolic valve: this part is very delicate because the practitioner has to align the endoscope with the colon in order to continue the progression. Furthermore, the colic angles are very difficult to cross. The final point is the crossing of the sigmoid colon. The technique consists in rolling up the endoscopic device into the sigmoid. Then the practitioner unrolls the buckle by rotating the endoscopic device and by withdrawing it. The sigmoid is untwisted and the rest of the inspection is more easily done. An extract of the simulation is presented in Fig. 15, shows that this operation can be reproduced thanks to the developed simulator. We have developed a simulator allowing to compute the progression of a poly-articulated endoscope, based on an under development real prototype, actuated by SMA actuators with identified behaviour model. This simulator is based on a mechanical description of the device and on the interacting environment, specific to the considered patient, through a medical MRI acquisition. As mentioned in the introduction, an experimental work is to 529
 
Tracking blobs in a 9 frame image sequence: (a)-original 1 st frame; (b) to (i)-KF results: search area defined by solid ellipses, the predicted position for each marker is given by +, and the corrected position is represented with x.
Data association time while using the efficient MD or the usual MD on a Mobile AMD Atlhon(tm) 4 at 1.20 GHz with 256 MB RAM.
Relative Frequency of errors in the efficient approximation of MD.
We address the problem of tracking efficiently feature points along image sequences. To estimate the undergoing movement we use an approach based on Kalman filtering which performs the prediction and correction of the features movement in every image frame. In this paper measured data is incorporated by optimizing the global correspondence set based on efficient approximations of the Mahalanobis distances (MD). We analyze the difference between using the MD and its efficient approximation in the tracking results, and also examine the related computational costs. Experimental results which validate our approach are presented.
 
The technical information needed to replicate a prototype is usually concealed when aircraft manufacturers patent new designs. Competitors must face this problem by developing inverse engineering processes that are validated by simulations and design thinking processes to find any patent weaknesses. This paper focuses on a case study for patent analysis, applied to a revolutionary new concept in aircraft design: Patent #US2014/0319274A1 “Aircraft including a passenger cabin extending around a space defined outside the cabin and inside the aircraft”. The computer simulations were performed first by a low computational software, "FlowDesign" (Autodesk), and afterwards, by a professional tool "3DWind tunnel" (MicroCFD). Results revealed that the drag coefficient and the drag force decreased 5.8% and 3.8% respectively at climbing, while the lift force increased up to 47% for a pitch angle of 6 ⁰. The patent weaknesses reside in a wrong seat arrangement and not taking into account the possibility of a "hole" variable to adapt aircraft shape to different flying operations.
 
Automobile panel moulds are assembled pieces with various surface features, making it difficult to predict the machining properties in ball-end milling process. In this paper, Deform 3D finite element analysis software is used to simulate the ball-end milling of multi-hardness assembled moulds, and to analyse the distribution patterns of milling forces, stress fields and temperature fields in the transition regions of the multi-hardness assembled moulds. Subsequently, milling of sine surface moulds is simulated, and the effects of milling parameters on the thermal performance of sine surfaces are analysed. Finally, the multi-hardness assembling and milling experiment and the sine surface mould milling experiments are conducted to verify the effectiveness of the Deform 3D finite element simulation method.
 
The number of work-related musculoskeletal disorders has been increasing in most industries and occupations. Since these injuries impose high costs on employers and society it is important to prevent it through ergonomic assessment and job redesign. The paper presents a research of the workplace ophthalmic nurse regarding strain and stress. In the workplace the Intravenous Fluorescein angiography or fluorescent angiography is made which is a technique for examining the circulation of the retina and choroids using a fluorescent dye and specialized camera. The working procedure is complex and since nurses must assist in several forced positions for longer time ergonomic analyses were made aimed to determine strain and stress at workplace. For assessment of body postures OWAS analysis was performed manually and using computer simulation. The results obtained using computer simulations are comparable to manually performed research for most body positions except for bent and twisted back. Body postures of upper limb, lower limb and neck were exposed as harmful for nurse during working procedure and according to OWAS changes are needed in near future.
 
Interpretation of geometric defects that influences the flatness [15].
In this paper, we present a three-dimensional manufacturing tolerancement model. Several researchers have interested to modelling the machining geometric defects. The most researchers are limited to kinematic and static study. Only some works are evoked the dynamic effects, especially the influence of the chatter phenomenon on the roughness of the machined surface. In this context, the paper presents a contribution for modelling and quantification of the machining geometric defects where the machining dynamic effects are considered. A developed method is established based on Homogeneous Transformation Method in subject to determine the kinematical deviations caused by part locating and relocating. The dynamic displacements due to clamping and machining forces are defined using Finite Element Method. The numerical results are then compared to published experimental results.
 
Selective Laser Melting (SLM) is actually the most attractive technique in an Additive Manufacturing (AM) technology because of the possibility to build layer by layer up nearly full density metallic components without needing for post-processing. One of the main problems in SLM processes is represented by the thermal distortion of the model during forming; the part tends to be deformed and cracked due to the thermal stress. Therefore, it is important to know the effect of the process parameters on the molten zone and consequently on the density of the consolidated material. Great advantage can be obtained from the prediction of temperature evolution and distribution. The aim of this study is to evaluate the influence of the process parameters on the temperature evolution in a 3D model. The developed code evaluates the distribution and evolution of the temperatures in the SLM process and simulates the powder-liquid-solid change by means of a check of the nodes temperature.
 
The fourth industrial revolution, or Industry 4.0 (I4.0), originated in German, englobes many innovative features, in order to bring the concept of “smart factories”. Moreover, discrete-event simulation (DES) is one of the most important areas involved in this goal. With this in mind, the purpose of this paper is to propose a research and development agenda (R&D) for DES researchers and practitioners, in order to comply with the I4.0 agenda. To achieve this, a literature review (LR) was conducted, in which 45 papers were considered relevant for this research. From their analysis, it was found that: the ability to automatically generate simulation models; the automation of data exchange between manufacturing applications and simulation tools; and visualization features, are the most essential DES features for I4.0. Thereafter, the LR focused on analysing the most recent papers in these areas of simulation, in order to propose a list of R&D items for DES researchers and practitioners.
 
Layout of the steel plant company.
DES model.
Production environments worldwide transform themselves in order to take the best advantage of the Industry 4.0 guidelines. Automation, data exchange, cyber-physical systems, the IoT, cloud and cognitive computing represent a step in the unknown to these companies, associated with high risks and also the need to restructure their culture. If the execution route is not clearly defined and understandable to all levels of employees, the renovation is too long. The maturity models can be used for the assessment of current Industry 4.0 maturity level, but the practical use of scores and assessed level often requires the involvement of consulting firms. Companies can avoid the involvement of consulting companies with the use of complementary tools. In this paper, we propose a new methodology that combines the Industry 4.0 maturity model and discrete-event simulation tools in the case of steel production company with the possibility of generalization. The combination of these tools in the first step helps the company to assess its current level of maturity for Industry 4.0, and in the second step helps to consider about strengths and weaknesses of possible scenarios for transition to a higher level of maturity.
 
Schematic illustration of a heat transfer model in orthogonal metal cutting [1].  
Measured and predicted cutting forces in dry and cryogenic turning of AISI 4340.  
Average surface roughness in dry and cryogenic turnings of AISI 4340.  
A localized high temperature area occurring at the tip of the tool during a cutting process can be detrimental and lead to a rapid wear mechanism. This paper presents the effect of a cryogenic application during the machining process on the temperature generated at the tool-chip interface, compared to a dry environment in the turning of the AISI 4340 alloy steel using a coated carbide tool. The cutting temperature was estimated using the Third Wave AdvantEdge software, which then was validated with the turning experiments. A significant reduction of the cutting temperature and the steeper temperature gradients on the cutting edge and the chips were observed in the cryogenic machining, which indicates more effective heat removal from the cutting zone. The sudden cold of-196 ° C caused the chips to become hard and brittle, which enhanced the chip breakability during the machining process.
 
Typical continuous casting process.
Continuously cast product and defects originating from the mould.
Surface crack (off-corner crack) at macro-etched 40 70MnVS4 rolled bar cross-section. In 2014, 175 consecutively batches of 70MnVS4 were cast. The following parameters were gathered:  Average casting temperature [°C] influences thermo-mechanical processes during melt solidification.  The number of constructional steel jackets used in the mould housing. Additionally, stainless steel jackets can be used. Steel jackets assure uniform water distributions all over the copper mould at a water flow rate of 1400 l/min. Note that in Štore Steel Ltd. the gap between the steel jacket and the mould is only 4 mm and that the surface roughness of the corroded steel drastically influences the water flow regime and, consequently, heat removal. Typical mould housing is schematically presented in Fig. 4.  Average casting speed of an individual strand [m/min]. Casting speed is influenced by casting temperature and it is automatically regulated during casting.  Average mould water flow [l/min] for each mould. Water provides intensive mould cooling. During cooling, the input and output water temperature changes.  The average difference between input and output water temperature for each mould [°C].  The ratio between material with surface defects and the examined material after surface examination using automatic control line (i.e. flux leakage method). Note that not all material with surface defects is nonconform (i.e. scrap)-it depends on permissible defect depth. Accordingly, we should distinguish between material with surface defects and scrap. The average values and standard deviations of gathered parameters for 70MnVS4 are presented in Table I.
The mould and its housing.
The influences of individual parameters on the ratio between material with surface defects and examined material using linear regression model.
High-strength steel 70MnVS4 is often used for forging connecting rods in the automotive industry. Connecting rod performance depends also on surface quality. Several defects, including surface defects, originate from the continuous casting process. The paper presents the monitoring of the most influential parameters (casting temperature, type of mould steel jacket, casting speed, water flux in the mould and the difference between input and output water temperature in the mould) during continuous casting of 70MnVS4 steel. Also the results of surface control of the rolled material (automatic control line) were collected. Using the gathered data, the model for predicting the ratio between material with surface defects and the examined material was developed using linear regression and genetic programming. Based on modelling results, only one type of mould steel jacket was used, while casting speed and mould water flow were increased from 1.13 m/min to 1.18 m/min and from 1300 l/min to 1500 l/min, respectively. In the period from January 2015 to October 2018 the scrap rate of 70MnVS4 and overall scrap rate was reduced by 22.29 % and 18.04 %, respectively.
 
Connectionism strategy is widely used by the policymaker to implement the emergency rescue activities in industrial accidents, exploring its mechanism is helpful to deeply understand the mechanism of behavioural change of policymakers during emergency decision-making procedure. In this study, the emergency process and influential factors as well as three types of emergency disposal schemes, when the connectionism strategy was adopted for rescue activities in coal mining accidents, were qualitatively analysed and concluded. Then, an improved simulation model was proposed based on Parallel Constraint Satisfaction (PCS) model. Lastly an algorithm written in MATLAB was employed to model and explore the influential mechanism of the negative emotion and the concern of policymakers as well as the mode of decision-making tasks on decision time and decision confidence. Results demonstrate that, the higher the policymakers' negative emotion, the shorter the decision time and the higher level of decision confidence they have. Under different modes of decision tasks, the more difficult it is to identify the superiority and inferiority of different disposal schemes, the more decision time the policymakers need and the lower level of decision confidence they have, the decision confidence is more sensitive to the mode of decision-making task, meanwhile the negative emotion and the concern of policymakers have different effects on decision time and decision confidence. Compared with the concern on cues, policymakers' decision confidence is much higher when they focus more on schemes. The study reveals the mechanism of connectionism strategy adopted for emergency rescue activities in industrial accidents, which has a profound significance for optimizing emergency decision support systems for industrial accident management and enhancing the quality of emergency decision-making.
 
The gear is one of the most widely used and vital parts having freeform surfaces. Accurate modelling and strength calculation are the basis of gear design and optimization. The traditional gear design and the existing finite element analysis methods cannot effectively solve these problems. Only a simple model can be established and the static strength analysis can be carried out at a certain meshing position. In this study, accurate equations of the tooth surfaces of a spur gear were derived based on the principle of gear shaping. Then, the parametric finite element modelling and simulation of the transient meshing of the spur gear have been realized using ANSYS software, and the stress distribution and variation trends of the gear during the meshing process have been analysed. Finally, the method is verified by simulation and comparison. The analysis results show that the effect of the tooth fillet surface on the strength of the gear is very large, and the bending stress and contact stress of the gear are nonlinear in the meshing process. The proposed method can accurately establish the model including the tooth fillet surface of the spur gear, and accurately analyse the strength of the spur gear pair. This makes up for the shortcomings of the existing method, and can be applied to other gear forms after appropriate modification.
 
Thermal manikins are used for testing the thermal insulation of different types of protective clothing. Data about thermal insulation is required when new protective clothes are designed or for the optimization of the existing ones. Thermal insulation usually plays an important role when researching or developing optimal protective clothing used in hot environmental conditions. The aim is to develop protective clothing that will ensure the lowest possible thermal load for the user. To get accurate information about thermal insulation, the measuring system for its determination should be stable. One of the possibilities is to use a thermal manikin presenting the anatomic shape of the human body. The measurement accuracy and stability of the measuring system based on the thermal manikin are investigated and assessed on the basis of statistical analysis. Accurate measurements can be ensured with statistics. Only accurate data has an application value for the industrial development.
 
This paper proposes a new dispatching rule to achieve the on-time delivery of high priority lots in order-driven fabrications (FABs). Most of conventional dispatching rules can be considered as the variants of classical rules like ODD, EDD, and CR. Although, many of conventional dispatching rules give good performance in terms of the on-time delivery, they do not consider the existence of high priority lots. We classify orders into two types for an order-driven FAB; regular orders and high priority orders. While regular orders are typically characterized by longer cycle times, looser target due dates but lower margins, the high priority orders have shorter cycle times, tighter target due dates and higher margins. If the deliveries of high priority orders are late, the manufacturer may have to pay a significant amount of penalty charges. The proposed dispatching rule employs the concept of reservations of high priority lots, and consists of two major steps; 1) finding a high priority lot for reservation, and 2) finding a tool for reservation. The first step tries to minimize the waiting time of high priority lots, and the second step tries to maximize the utilization of tools. Experimental results show that the proposed dispatching rule is superior over conventional rules with regard to on-time delivery of high priority lots.
 
The newly introduced sweep coverage scheme uses mobile sensors to implement network coverage in wireless sensor networks (WSNs) and has attracted much attention from researchers. However, data buffer and moving speed of the mobile sensor are limited in sweep coverage. Thus, scheduling the minimum number of mobile sensors to efficiently implement dynamical network coverage while considering data delivery is still a challenging problem. To provide steady and efficient data gathering from sensors, an improved ant colony optimization-based sweep coverage (IACOSC) scheme supporting data delivery was proposed. In IACOSC, the artificial ants were used to create the initial coverage routes for points of interest. Then, a novel metric called route coverage efficiency was used to evaluate the routes. Finally, a local search algorithm based on route deletion and node insertion was employed to optimize these routes. Algorithm analysis shows that the time complexity of IACOSC is O(n³). Simulation results show that, compared with existing sweep coverage approaches considering data delivery, IACOSC significantly reduces the computational complexity and decreases the computation time by 50% while reducing the mobile sensors by 16.73% in the same network scenarios. The results obtained in this study can be applied to optimal deployment of WSN using the sweep coverage scheme.
 
For an enterprise to survive the fierce market competition, efficient production scheduling is a must as it improves economic efficiency and reduces cost. As an important branch of production scheduling, the flexible job-shop scheduling problem (FJSP) is a mixed blessing. It accurately reflects the characteristics of the actual production, but adds to the difficulties in problem solving. With the ant colony algorithm as the basic optimization method, this paper proposes the hybrid ant colony algorithm based on the 3D disjunctive graph model by combining the elitist ant system, max-min ant system and the staged parameter control mechanism, optimizes the FJSP problem to minimize the longest completion time, the early/delay penalty cost, the average idle time of the machine, and the production cost, and verifies the effectiveness of the model and algorithm by an example.
 
Drawing on the coevolution between populations, this paper proposes a dynamic multi-population ant colony optimization (ACO) algorithm to solve the blocking flow-shop scheduling problem (FSP). In our algorithm, the ant colony is divided into an elite population, multiple search populations, and a mutation population. In the initial stage, only the elite population and the search populations participate in optimization. After a certain number of iterations, a mutation population is dynamically generated from the worst solution in each search population and that in the elite population. The mutation population is reinitialized before entering the optimization process. The mutated population can jump out of the original search space for another search. Finally, the superiority of our algorithm in solving blocking FSP was proved through comparative simulations.
 
Forklift linked to the system. 
Layout of wide-aisle warehouse (black-picking order, P/D-depot). 
A fragment from constructed plan (left side-the period of suppliers, right side-schematic plan). 
Nowadays the great attention has to be paid to warehouse. Theoretical analysis shows the need to optimise their activities. This encourages the search of more advanced solutions. Aiming to determine possible improvements, the operations of forklifts are examined in warehouses, and detail solutions are presented. For empirical study author created a simulation model and tested different scenarios. First of all, author examined the new routing method and suggested programming algorithm for forklift route optimization. In the first part of the study possible improvements for put-away activity are analysed, in the second part - improvements for replenishment activity are overviewed. Simulation results showed that the reduction of forklift travel distance is equal from 11.1 % to 35.6 %. Finally, the study ends with detail suggestions: author presented new routing method and forklift routing algorithm. Further, the theoretical results have to be tested in practise.
 
Dynamic behaviour of a micro-cantilever beam under periodic electro-thermal loading is studied in this paper. For certain applications the beam is required to vibrate at a particular frequency. Modal analysis using 3D finite element is used in order to find the geometrical parameters that makes fundamental frequency of the beam match the required frequency. Then non-linear dynamic thermoelastic analysis is conducted on the system to analyse the time-history (transient) behaviour of the beam and record its tip displacement. However, due to uncertainties and non-repeatabilities that are inherent properties of the system along with those associated with the manufacturing, final product is likely to have deviations from these estimated values (fundamental frequency and tip displacement). Thus, choosing a nominal (desired) design and studying the deviation in natural frequency and tip displacement via 2k factorial Design-of-Experiments (DOE), effect of uncertainties on the overall performance of the system is investigated. This allows finding the significance of individual parameters on the overall robustness of the design as well as potential interactions between various parameters. Finally, the expected behaviour of the micro-cantilever and its robustness to design and implementation uncertainties are elaborated and statements for robust design of this system are made.
 
The door-opening task is a key step for the indoor rescue and monitoring of a mobile manipulator. However, the contact effect between the gripper and the door handle may produce excessive internal forces to damage mechanical devices because of position errors or the imprecise modelling of the robot and operation environment. To successfully suppress the excessive internal forces and assure the proper posture of the mobile manipulator under holonomic and non-holonomic constraints, a robust adaptive position/force control algorithm was proposed to track the desired posture and force in opening a door to avoid the complexity of compliant mechanism and the unpredictability of the contact stiffness in traditional impedance control. Dynamic simulation studies with MATLAB and RecurDyn were used to verify the dynamic model of the system and obtain the expected positions and forces during door opening. Simulation results and experiments show that the proposed method is robust in modelling errors, joint frictions and environment disturbances and meets the requirement for opening a door with a handle and suppressing excessive internal forces. This study offers reference data and the control method for future real-world door-opening operation in different environments. (Received in August 2015, accepted in March 2016. This paper was with the authors 3 months for 2 revisions.)
 
The relationship between marginal rates of substitution of the cost of effort into the project control objectives and the project value-adding sharing coefficient. 
The relationship between marginal rates of substitution of the cost of effort into the project control objectives and the level of effort into the duration objective. 
The relationship between δ and β 1 under different γ 1. Substituting related data into 
On the basis of equal cooperation between project-based enterprises, the project-based supply chain cross-organizational dynamic reputation incentives model was established in consideration of the implicit reputation factors to the contractor’s incentive influence, and the impaction between control objective effect level, bargaining power and project value-adding was detailed analysed, especially the effective equilibrium condition for reputation incentive effects. Thus compared the analysis conclusions with project-based supply chain incentive model which single considering explicit benefit incentive, and verified the rationality and applicability of the project-based supply chain cross-organizational dynamic reputation incentives model through related digital simulation. The results reflects that, whether the linear relationship between duration and quality exists or not, the project management enterprise resorting to adjust project object objective incentive intensity and implementing reputation incentive strategy could not only achieve project value-adding maximization, but also realize net earnings Pareto improvement.
 
This work simulated several alternatives for the dynamic allocation of additional human resources in a company that produces a group of specific products. The goal was to increase the average amount of the margin of the total contribution through a hybrid application of a discrete event simulation (DES) and an agent-based modelling simulation (ABMS). Two different decision-making forms were proposed to determine which workstation should receive an additional operator. The first proposal was based on the occupancy level of the operators, while the second one was based on the intermediate queue size. The computational model was operationally validated by comparing the results with actual production data from the company. Twelve scenarios were analysed using a margin of the established contribution. Based on the occupancy rate, the ratio improved on average by 27.68 %, with an additional operator in the workstation. According to the second criterion, this improvement raised to 117.51 %.
 
The inflow of the side pump sump is not smooth enough during the operation of a pumping station, resulting in an asymmetric adherent vortex that endangers the station’s normal operation and safety. To solve this problem, flow field and vorticity distribution charts of different flow layers were created through the establishment of a numerical model of the pumping station inflow by means of the fluid simulation software. The formation mechanism of the asymmetric adherent vortex in the side pump sump was analysed by combining Reynolds shear stress distribution, the simplified Navier–Stokes equation, and the transport equation of turbulent kinetic energy. Furthermore, the accuracy of the numerical simulation results was verified using flow field data collected via particle image velocimetry at the junction of the forebay and pump sumps of the station. Results show that the distribution of inflow velocity is uneven due to the asymmetric friction of the inflow in the side pump sump. The transverse velocity formed from it generates the asymmetric vortex in the side pump sump and creates an inspiratory vortex.
 
Dispersion and flow of air in passenger compartments of vehicles are important to assure a comfortable environment for passengers, driver concentration and safe driving conditions. The article describe numerical adiabatic flow simulations for "mute", an electric car. Air streams in its passenger compartment were simulated; air velocities were compared while using different turbulence models. The turbulence models were selected upon being screened for best-suiting characteristics. The eddy-viscosity standard, RNG k-epsilon and SST k-omega models were used. Near-wall approaches (standard wall functions, scalable wall functions and enhanced wall treatment) were checked against a test case from "European Research Community on Flow, Turbulence and Combustion" to determine the best choice for "mute" passenger compartment air velocity simulations.
 
On the present, a considerable reduction of the greenhouse gas emissions is one of the most important challenges in construction of the motorcars and their driving units. Application of the biofuels essentially contributes to reduction of air pollution caused by the exhaust gases. However, application of the bioethanol as a fuel in the spark ignition engines requires to perform some important constructional adjustments of these engines in order to ensure their proper functioning and to eliminate the potential operational risks. The scientific publication is focused on creation of a simulation model describing the advanced system, which is developed for application of the sustainable fuels. The scientific contribution of this work consists in original system of the cooling channel, which is applicable in all the highperformance sport applications. There were obtained very good results during testing of this system in real operation, especially in the case of the E85 fuel. Combustion of this fuel, using the above-mentioned system, significantly eliminated thermal loading of the whole drive unit. The authors of this scientific publication also obtained a patent for this system. (Received in April 2022, accepted in May 2022. This paper was with the authors 1 week for 1 revision.).
 
Personalized bone grafts are one of the best examples of the latest achievements in the biomedical engineering. In the area of maxillofacial bone tissue reconstruction or jaw bone augmentation, their application has for some time been on the rise, and its ever increasing significance is driven by the growing technical support. One of the key segments is the bone graft modelling customized to suit patient's specific needs, since it greatly determines not only the future anatomic functionality but also the acceptance probability of the graft by the bone tissue. With the graft geometry importance in mind, presented in this paper is an approach to personalized bone graft modelling. The approach is based on application of modern computer-aided systems and methods, and enables efficient geometric design while minimizing the risk of errors during modelling and placement stages. Verification is based on a case study of a personalized bone graft designed for a patient requiring mandible augmentation.
 
This paper demonstrates a new methodology for designing a virtual factory model and model execution on the basis of a real schedule plan. The main characteristic of the developed method is that the inputs are regarded as one of the main parameters of the production process, and the main objective is to create a low-cost production process model. The methodology is adjusted for use in SMEs (Small and Medium-Sized Enterprises) with individual or unique type of production. For such companies, the method represents an ability to optimize existing production processes through detecting and eliminating possible errors and disturbances before the real production process is executed at an acceptable cost. The applicability and suitability of the developed method for virtual production performance has been proven with the verification process, where the input data for the simulation was obtained from a real company. The simulation results have shown that the presented methodology is a useful tool for the optimization of the production process. (Received in June 2013, accepted in September 2013. This paper was with the authors 1 month for 1 revision.).
 
The optimizing layout of charging stations. 
The optimizing layout of charging stations. Eventually, we can obtain the coordinates of all charging stations: Datun station (-10, 182), Beitucheng station (-47, 228), Wanquanhe station (-223, 224), Xizhimen station (-120, 310), Hangtianqiao station (-200, 360), Yuejialou station (-240, 430), Lianfangqiao station (-340, 420), Fengbeiqiao station (-250, 490), Majialou station (-130, 560), Siyuanxiqiao station (70, 240), Hujialou station (60, 350), Hongyanqiao station (110, 500), the station with ID 14 (-265, 575), the station with ID 15 (-27, 462),the station with ID 16 (-144, 429), the station with ID 17 (-28, 632),and the station with ID 18 (94, 605). 
In this study, we aim to find the key factors affecting the location of electric vehicle charging stations. We first developed a Non-deterministic Polynomial (NP) model that aims to minimize the total travel distance of cars. Second, we applied an agent-based simulation algorithm to determine the optimized location for charging stations. Finally, we conducted multi-simulation and statistical analysis of passenger priority, car mileage, electric vehicle distribution and passenger distribution using a one-way analysis of variance (ANOVA). The results of this study show that priority is not a factor affecting the location of electric vehicle (EV) charging stations and that mileage, the EV distribution and the passenger distribution are factors affecting the location of EV charging stations, with exogenous variables such as the type of circuit and the voltage drawn as constants. The proposed model can help provide a reference for the location of charging stations in urban areas.
 
Despite the wideness of the literature on technological innovation, the diffusion of the supply chain collaborative technology innovation has not still received much attention. This paper is an attempt to answer the question that how the supply chain collaborative technological innovations emerge and diffuse. An agent-based model of collaborative supply chain technological innovation including the supplier agents, manufacture agents and customer agents is established in this paper, and the simulation experiments are conducted in terms of two kinds of the competitive technology innovation diffusion process under four scenarios. The results show that the supply chain collaborative supply chain technological innovation diffusion is different from the traditional technology innovation diffusion, and the relationship between suppliers and manufacturers has important influence on diffusion speed and efficiency.
 
This study introduces the mainstream theory of crowd evacuation based on multi-agent. Then a simulation model is developed based on Agent and Pathfinder to simulate the evacuation of three subway space types, including platform, station hall and stair. In addition, simulation is also carried out on the situation of the reverse running of the firefighters walking ladder and the different distribution of the crowd density. Finally, the simulation parameters are adjusted respectively to observe and compare the simulation results under different circumstances. Through the simulation of the situation of crowd evacuation under different conditions and parameters, key data such as crowd speed, number of people passing through space and remaining number, number of people passing through exit and evacuation path are recorded. These key data and the above simulation test results are vital for constructive suggestions that can be put forward for subway space design and fire control scheme.
 
This study investigates electric vehicles battery recycling problem. In this study, based on Agent theory and Anylogic platform, Agent model of battery recycling is built. We have done simulation for electric vehicle batteries recycling: this paper analyses the influence that factors (battery renovation rate, quantities of electric vehicles, electric vehicle lifetime, battery lifetime, battery renovation time) have on recycling (quantities of wasted batteries, quantities of reused batteries, optimal quantities of batteries). Through simulation, this study shows that factors' influence on recycling depends on the relative life RL greatly. When renovation rate changes in the interval [0.7, 0.8], the results fluctuate greatly, such as optimal quantities of batteries will decrease about 10 %, quantities of reused batteries can increase about 30 %, and quantities of wasted batteries will have a sharp decline by about 40 %; the model is optimal until battery renovation times are increased to three. (Received, processed and accepted by the Chinese Representative Office.).
 
The number of tourists to recreation areas has increased dramatically, leading to a growing concern about the congestion phenomena in these areas. Since the information provision has been introduced to reduce the congestion, its potential benefits as well as its drawbacks have been discussed controversially. In this work, we address a basic recreation area scenario with different patterns of information sharing and study the impact of them using agent-based simulation, where the tourists are modelled as agents. Three evaluation indicators are proposed to evaluate the performance of the strategies and both of the positive and negative of information sharing patterns are described.
 
New product development is a high-risk decision-making problem in which similar products compete with each other to expand their market shares. Brand-level diffusion predictions can help product design managers to analyse how product attribute specifications impact total market shares, which can, in turn, aid managers in choosing the designs that yield maximum profits. In this paper, we develop a product attribute design method in which an artificial market consisting of consumer agents in an interaction network is created to simulate the diffusion process of products, and a genetic algorithm is integrated with the artificial market to support the product design decision-making process. The contribution of this research is that the predicted market response to product alternatives is incorporated into the product design optimisation. Two empirical experiments were conducted on the Korean laptop computer market to demonstrate the potential of this integrated method. Preliminary experiment showed that our prediction diffusion curves had an average error of 3.04%. In the primary experiment, five designs were recommended, and a comparison with the 31 best-selling laptop computers resulted in an average error of less than 8% when the "Price" attribute was excluded.
 
To deal with the complex structure and difficulty in precise expression of the interaction between entities in the steel production logistics system, this paper uses complex network theory and multiagent system engineering to simulate the complex steel production logistics system, and thereby calculate related parameters, gather statistics, and optimize the steel production logistics system. According to the analysis, the processing of logistics is low in efficiency because 19 pieces of equipment are involved from the beginning of the logistics subject processing to the final formation of steel, while only a few processes are required for about half of the auxiliary material or auxiliary process. The system logistics is not compact because most of the equipment used in steel production has only a single function and a limited service area, whereas a higher degree distribution indicates a higher importance in a piece of equipment in the network. This is a must to guarantee the normal operation of the equipment with a higher degree distribution. The simulation results are basically the same with the actual production results, and the error is within the acceptable range, which proves that the simulation system is correct and effective.
 
To reveal the damage evolution and energy dissipation characteristics of lightweight aggregate concrete (LWAC) under impact loading, some simulations of lightweight shale ceramsite concrete under high strain rate impact with a 3D meso-scale model were carried out. After the meso-scale model considering the randomness of the shape and distribution of lightweight aggregates being established and the material parameters of each component being determined by test results, the damage evolution and energy dissipation characteristics of the model under different strain rates were analysed. Results show that the damage evolution of LWAC can be divided into four stages from the perspective of energy. The large deformation and stress concentration firstly occur on the lightweight aggregates, which leads to the generation of micro-cracks. There is an upper limit of the strain energy density of the lightweight aggregate component. The energy absorption efficiency of the specimen first increases and then decreases with the increase of strain rates. The obtained conclusions can provide a reference for understanding the dynamic performances and damage mechanism of LWAC. (Received in January 2021, accepted in April 2021. This paper was with the authors 1 month for 1 revision.).
 
Sump cleaning machine is important coal mine equipment designed to reduce the labour intensity of underground workers, and its front end usually uses a spiral aggregate device. However, the traditional empirical design methods cannot accurately obtain the optimal parameters and defects in design of the spiral aggregate device due to the complex structure. To improve the design approach, the discrete element numerical model of the working process of the spiral aggregate device was constructed to conduct simulation research and design three key parameters, namely, screw shaft speed, roof inclination angle of the feeding port, and number of throwing plates. Results demonstrate that the aggregate rate increases first and then decreases with the increase in the rotating speed of screw shaft. In addition, the increase in the number of throwing plates is beneficial to improve the stability of the axial movement of slime water. The roof inclination angle of the feeding port has no significant influence on the aggregate effect. The results provide guidance for improving the structure of the spiral aggregate device and a reference for optimizing the design of complex screw mechanisms.
 
Product and information flow in a two-echelon supply chain [based on [23]].  
Change in costs elements with respect to α.  
Relationship between total costs and total emissions for different  values.  
Effect of changing excess percentage () on service level.  
Relationship between total costs, emissions, and service level for different  values.  
Food supply, safety and quality have become major concerns worldwide. Agri-food supply chains (ASC) possess special characteristics due to the perishability of their products and the high uncertainty of supply and demand. Furthermore, different sources of CO2 emissions exist in an ASC due to storage, transportation, and disposal of fresh produce. Thus to ensure the sustainability of the supply chain, planning decisions have to be made with consideration of both economic and environmental aspects. This work studies the effect of changing the order quantity in a two-echelon agri-food supply chain on costs, emissions, and service level. A discrete-event simulation model is developed to include stochastic demand and lead-time, the amount of CO2 emissions along the supply chain, service levels, and product lifetime effects. Simulation results show that reducing the order quantities can reduce costs and emissions by 27.42 % and 18.21 %; respectively, without sacrificing high service levels. Also, relying on costs or service level as sole objectives of the supply chain without consideration of emissions can result in greater economic and environmental inefficiencies in management of inventory levels.
 
Scheduling harvesting operations is very important for the agricultural machinery centres and the farmers in order to finish the harvesting work effectively. Most machinery owners schedule their farm machinery according to their own experiences, resulting in a big waste of agriculture resources. This paper attempts to schedule the use of agricultural machinery from the machinery resource centres under multi-farmland, multi-type situations considering time, spatial and weather factors as well as road factors in order to maximize efficiency of resource utilization. A modified fuzzy hybrid genetic algorithm is proposed to establish this scheduling model. An empirical study of an agricultural machinery association in Anhui province in China is illustrated and the results show that the models and the scheduling algorithm proposed in this study can improve the efficiency of utilization of the agricultural machinery resource centres and reduce the costs of agricultural machinery usage.
 
An automated guided vehicle (AGV) is a mobile robot with remarkable industrial applicability for transporting materials within a manufacturing facility or a warehouse. AGV scheduling refers to the process of allocating AGVs to tasks, taking into account the cost and time of operations. Multiobjective scheduling is adopted in this study to acquire a more complex and combinatorial model in contrast with single objective practices. The model objectives are the makespan and number of AGVs minimization while considering the AGVs battery charge. A fuzzy hybrid GA-PSO (genetic algorithm – particle swarm optimization) algorithm was developed to optimize the model. Results have been compared with GA, PSO, and hybrid GA-PSO algorithms to explore the applicability of the algorithm developed. Model’s feasibility and the algorithms’ performance were investigated through a numerical example before and after the optimization. The model evaluation and validation was conducted through simulation via Flexsim software. The fuzzy hybrid GA-PSO surpassed the other methods, although obtaining less mean computational time was the only significant improvement over hybrid GA-PSO.
 
Top-cited authors
Iztok Palcic
  • University of Maribor
Borut Buchmeister
  • University of Maribor
Martin Straka
  • Technical University of Kosice - Technicka univerzita v Kosiciach
Mohamed Haddar
  • Ecole Nationale d'Ingénieurs de Sfax
Primoz Ternik
  • AVL LIST GMBH