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In pulp and paper the modelling and simulation of the pulp production processes was the first major application. Since then several other applications have been realised though papermaking has never been on the lead concerning the use of computer-based modelling and simulation. The complex nature of the materials is one of the most demanding challenges and the biggest hurdle for any electronic description of the papermaking process or paper itself. So other industries took the lead and it is now for the paper industry to learn from these industries what can be done with the help of computers to control or optimise processes or to design new grades. The application of results gained with the use of modelling and simulation techniques in pulp and paper manufacturing processes has helped the industry to, for example, reduce emissions and increase the productivity and cost-efficiency of the processes. Still there are many important tasks open. A better understanding of the mechanisms of the processes and their control loops has to be achieved in order to further improve the paper quality, stabilise the wet-end chemistry, and enhance the runnability. Important features to be developed are new process designs, efficient process monitoring and systems that offer decision support during operation. In this paper a review of the state of the art on modelling and simulation in the pulp and paper industry is presented as well as further research needs. [ABSTRACT FROM AUTHOR]

The critical role that numerical simulation plays in additive manufacturing has stimulated research on the effectiveness and potential applications of mesh-free, particle-based discretisation techniques. These methods excel at handling fluid flows and are viable alternatives to the mesh-based techniques typically used in commercial simulation software. In this paper, we review recent advances in developing computational models for metal additive manufacturing (MAM) processes using particle methods, in the theoretical understanding of the fundamental mechanisms that control such processes at the powder (or melt pool) scale, and in the predictability of physics-based modelling approaches. The paper explores the applicability and performance of particle-based methods in simulating powder bed fusion, directed energy deposition, and binder jetting processes. Since the progress of MAM relies on systematic material-process-structure realisations which are often impossible to sense or observe experimentally, developing efficient particle-based and multiscale simulation tools can be essential to achieving this objective through in-situ process control and optimisation. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) technology has the potential to significantly improve supply chain dynamics. The purpose of this paper is to investigate the impact of AM on spare parts supply chain. Three supply chain scenarios are investigated in this paper, namely conventional supply chain, centralised AM-based supply chain and distributed AM-based supply chain. Based on system dynamics simulations, this paper specifically compares three supply chain scenarios, in terms of total variable cost and carbon emission. The results show the spare part supply chain utilising AM is indeed superior to the traditional one in sustainable performance. It is also expected that AM can facilitate the spare parts supply chain to achieve more economic benefits along with its development. To our knowledge, this paper is one of the early studies that explores the impact of AM on supply chain performance and quantitatively examines the superiority of utilising AM in spare parts supply chain. Some suggestions are also provided to help managers adopting AM in their spare parts supply chains. [ABSTRACT FROM AUTHOR]

Nowadays, batch wise processing industry operates on a very dynamic market. To a certain extent, batch production plants have the desired flexibility to respond to these dynamics as uncertainties in product demand or new ecological targets. However, because of this flexibility, the complexity of the management and manufacturing operation increases considerably. The management of the operation is so complex, that to guarantee the continuity of the plant on the longer term, well-structured information and clear decision-making focussed on continuous improvement are absolute requisites. In this paper, a decision support framework (DSF) will be discussed aimed at giving more insights in the connection between operational activities and objectives of the plant and supporting the continuous search for improvements in operational and managerial tasks in such a way that the continuity of the batch plant can be better guaranteed. The different parts of the framework are illustrated on the basis of a continuous case study in a paper plant. The DSF includes two models, a generic objective model and a generic activity model, that can easily be adapted to the specific situation in which they are used and that are very valuable to obtain a better overview of all relations among operational objectives and activities. Moreover, the management team is supported to select from the large set of operational objectives, the ones that can really contribute to a better overall performance of the plant. This method for selecting promising objectives is based on AHP (analytic hierarchy process). [ABSTRACT FROM AUTHOR]

Large manufacturers have been using simulation to support decision-making for design and production. However, with the advancement of technologies and the emergence of big data, simulation can be utilised to perform and support data analytics for associated performance gains. This requires not only significant model development expertise, but also huge data collection and analysis efforts. This paper presents an approach within the frameworks of Design Science Research Methodology and prototyping to address the challenge of increasing the use of modelling, simulation and data analytics in manufacturing via reduction of the development effort. The use of manufacturing simulation models is presented as data analytics applications themselves and for supporting other data analytics applications by serving as data generators and as a tool for validation. The virtual factory concept is presented as the vehicle for manufacturing modelling and simulation. Virtual factory goes beyond traditional simulation models of factories to include multi-resolution modelling capabilities and thus allowing analysis at varying levels of detail. A path is proposed for implementation of the virtual factory concept that builds on developments in technologies and standards. A virtual machine prototype is provided as a demonstration of the use of a virtual representation for manufacturing data analytics. [ABSTRACT FROM PUBLISHER]

Flow control policies, such as clear the largest buffer first, have been used extensively in mediating server access between multiple job-arrival processes within manufacturing systems requiring significant set-up times between job types. Although the stability and performance characteristics of clearing policies have been studied, how these clearing policies affect the growth in arrival-to-departure sequence disorder across a machine or workcell is still an area for further research. In this paper, a closed-form model is formulated that characterises the steady-state average arrival-to-departure sequence disorder experienced by jobs processed through a stable flow controlled manufacturing system. Specifically addressed are the effects of upstream sequence disorder on the work-in-process of a downstream assembly process. A simulation study is used to validate the model’s accuracy and applicability in predicting steady-state average arrival-to-departure sequence disorder. A simulation study of an assembly process shows that by balancing upstream steady-state average sequence disorder, downstream work-in-process can be minimised while under a logical component grouping constraint. [ABSTRACT FROM PUBLISHER]

Additive manufacturing technologies are increasingly used in the development of new products. However, variations in part quality in terms of material properties, dimensional tolerances, surface roughness and defects limit its broader acceptance. Process control today based on heuristics and experimental data yields limited improvement in part quality. In an effort to identify the needed measurement science for real-time closed-loop control of additive manufacturing (AM) processes, this paper presents a literature review on the current AM control schemes, process measurements and modelling and simulation methods as it applies to the powder bed fusion process, though results from other processes are reviewed where applicable. We present our research findings to identify the correlations between process parameters, process signatures and product quality. We also present research recommendations on the key control issues to serve as a technical basis for standards development in this area. Complimentary details to this paper with summary tables, range of values, preliminary correlations and correlation figures can be accessed from a National Institute of Standards and Technology Report (http://nvlpubs.nist.gov/nistpubs/ir/2015/NIST.IR.8036.pdf). This paper is developed based on the report. [ABSTRACT FROM AUTHOR]

The computer simulation of manufacturing systems is commonly carried out using discrete event simulation (DES). Indeed, there appears to be a lack of applications of continuous simulation methods, particularly system dynamics (SD), despite evidence that this technique is suitable for industrial modelling. This paper investigates whether this is due to a decline in the general popularity of SD, or whether modelling of manufacturing systems represents a missed opportunity for SD. On this basis, the paper first gives a review of the concept of SD and fully describes the modelling technique. Following on, a survey of the published applications of SD in the 1990s is made by developing and using a structured classification approach. From this review, observations are made about the application of the SD method and opportunities for future research are suggested. [ABSTRACT FROM AUTHOR]

This paper deals with controlling flexible manufacturing systems (FMS) operating in volatile production environments. Shnits et al. (Shnits, B., Rubinovitz, J., and Sinreich, D., 2004. Multicriteria dynamic scheduling methodology for controlling a flexible manufacturing system. International Journal of Production Research, 42 (17), 3457-3472.) and Shnits and Sinreich (Shnits, B. and Sinreich, D., 2006. Controlling flexible manufacturing systems based on a dynamic selection of an appropriate operational criteria and scheduling policy. International Journal of Flexible Manufacturing Systems, 18 (1), 1-27.) developed a multi-criteria dynamic scheduling mechanism for controlling an FMS that can cope with such environments. An important part of this mechanism functioning, which impinges directly on its performance, is the activation of its decision-making process. This study continues the research presented in the above-mentioned papers and proposes different triggering methods for activating the control system decision-making process. The operational conditions for each suggested triggering method were analysed and a comparative analysis between these methods was performed. It was revealed that the highly dynamic triggering method, which activates the decision-making process right before a resource becomes available, outperformed the triggering methods that use a predefined scheduling period. [ABSTRACT FROM AUTHOR]

In this paper, we explore the effect of cross-training workers in Dual Resource Constrained (DRC) systems with machines having different mean processing times. By means of queuing and simulation analysis, we show that the detrimental effects of pooling (cross-training) previously found in single resource constrained (SRC) heterogeneous systems are also apparent in DRC heterogeneous systems. Fully cross-training workers in DRC heterogeneous systems is only beneficial if the differences between mean processing times are not too large, otherwise cross-training should be pursued within homogeneous subgroups of machines. Due to the limited machine availability, DRC systems are unable to use some of the potential assignment flexibility from cross-trained workers (pooled queues) that can be used in SRC systems. However, it appears that this restriction in the DRC system may even improve the system mean flow (waiting) time performance compared to the SRC system for relatively large differences in processing time. Finally, in fully flexible multiple server queuing systems, restricting the assignment flexibility by applying a decentral when-rule (i.e. a commonly used labour assignment rule in practice and research) instead of a central when-rule also seems to improve the mean flow time performance under processing time differences. [ABSTRACT FROM AUTHOR]

The computational simulation of human intelligent behaviour has been one of the main research topics in the artificial intelligence (AI) domain. Therefore, a great number of behavioural models were proposed considering emotional, cognitive and psychological factors to simulate the human behaviour in different domains such as military or manufacturing systems. In addition to psychological factors, the social state of a group of workers plays a critical role in rational decision-making, perception, human interaction, and human intelligence. Thus, it is judicious to analyse the workers' behaviour at work and to integrate their needs and requirements in manufacturing systems models in order to improve the simulation accuracy. In this context, this paper suggests a graphical and a mathematical representation model of workers' behaviours as well as the ties that can exist among them. The model is also extended to consider inter-worker social relations that can influence the individual performance. [ABSTRACT FROM AUTHOR]

In this paper, the control problem of multiple-load automated guided vehicles (AGVs) is studied. A control process that identifies four problems faced by multiple-load AGVs is proposed. The first problem is the task-determination problem, in which a multiple-load AGV determines whether its next task is a pickup task or a delivery task. The second problem is the delivery-dispatching problem, in which a multiple-load AGV determines which delivery point it should visit next if its next task is a delivery task. The third problem is the pickup-dispatching problem, in which a multiple-load AGV determines which pickup point it should visit next if its next task is a pickup task. Finally, the fourth problem is the load-selection problem, which requires a multiple-load AGV to determine which load it should pick up from the output queue of a pickup point. This paper focuses on the first and second problems. Different task-determination rules and delivery-dispatching rules are proposed for these two problems. For the problems that are not the main focus of this study, rules found in the literature or real systems are adopted in this study. The objective of this study is twofold. First, we need to understand how well the proposed rules will perform in different performance measures, e.g. the system's throughput and the mean lateness of parts. Second, we need to understand the mutual effects that different types of rules have on each other, so that the best combination of rules can be identified. Computer simulations were conducted to test the performance of the proposed rules. It is hoped the knowledge learned from this study can be beneficial to real multiple-load AGV systems similar to the one studied here. [ABSTRACT FROM AUTHOR]

This paper presents the results of a conceptual study and simulation experimentation aimed at understanding the underlying mechanisms of sequencing flexibility-enabled manufacturing lead-time reduction. In spite of a large body of literature on flexibility, the exact mechanism that enables flexibility to reduce the lead time is not fully understood. As a part of our research efforts on the proactive application of flexibility for the performance enhancement of manufacturing systems, we are motivated to study how flexibility can be employed in a proactive manner to reduce the manufacturing lead time and to develop an understanding of the underlying mechanisms. Towards this end, we have developed simulation models of simple flexible manufacturing systems and studied the effect of sequencing flexibility on the lead-time performance under different conditions of part load and machine load balancing. The studies indicated that sequencing flexibility has a significant effect on the lead-time performance of the manufacturing system, and the effect of flexibility varies under different conditions of load balancing. Further studies indicate the existence of complex interactions between the sequencing flexibility, process concurrency, processor load balancing, and manufacturing lead time. This paper intends to discuss some of the interesting results of these studies with a focus on the inherent mechanisms of sequencing flexibility-enabled lead-time reduction. [ABSTRACT FROM AUTHOR]

The two additional rotational motions of five-axis machining make the determination of the optimal feed direction and tool orientation a challenging task. A new model to find the optimal feed direction and tool orientation maximising the machining width and avoiding local gouging at a cutter contact (CC) point with a flat-end cutter considering the tool path smoothness requirement is developed in this paper. The machining error is characterised by a signed distance function defined from a point on the bottom tool circle of the cutter to the design surface. With the help of the differential evolution approach, the optimisation model can be resolved to determine the optimal tool orientation and feed direction at a given CC point, and generate the smooth tool paths following the optimal feed direction. Simulation examples demonstrate the developed techniques can improve the tool orientation and feed direction at a CC point to increase the machining width, improving the efficiency of freeform surface machining. [ABSTRACT FROM PUBLISHER]

Global competition and increasing customer expectations are forcing automobile manufacturers to improve their operations. Maintenance, being one of the most critical components in many industries, has a direct impact on the improvement of the overall production performance. In this paper, we introduce an anticipative plant-level maintenance decision support system (APMDSS) that provides guidance on corrective and preventive maintenance priorities based on the equipment bottleneck ranks with the objective of improving daily plant throughput. APMDSS anticipates the plant dynamics (i.e. bottlenecks, hourly buffer levels and likelihood of machine breakdowns) for upcoming shifts using starting state information of the production shift (e.g. equipment maintenance history, operational status of machines, buffer levels and scheduled production model mix). We also evaluate the performance of APMDSS using real data from an automotive body shop experiencing routine throughput difficulties due to frequent machine breakdowns. The results are compared with other methods from the literature and found to be superior in many settings. [ABSTRACT FROM PUBLISHER]

The literature is replete with models that examine various aspects of cellular manufacturing (CM), such as optimisation of cell layouts. However, many firms may realise zero to marginal returns from CM. Given this uncertainty, the manager should first determine the value of CM to the firm before deploying it. Although traditional valuation models employing discounted cash flow analysis allow for uncertainty, they treat future investments as fixed when computing the investment’s present value. The real options (RO) logic of valuation allows the manager to exercise the option to invest in or abandon a project based on expected outcomes. Future investments are thus options. This paper presents an RO model for CM migration that addresses whether a firm should migrate to CM; and it prescribes thesequenceof cell deployment, which has not been addressed in the literature. Our model is also much more transparent and accessible to practitioners, with an accompanying software tool for prospective users. Finally, we use simulation extensively to discover the drivers of the optimal cell deployment sequence. Our results show that there is a complex interplay between net present value, speed of cellularisation, inter-cell learning and volatility in terms of their influence on the cell sequence. [ABSTRACT FROM AUTHOR]

This paper studies the performance of constant work-in-process (CONWIP) assembly system with multi-loop in mass production, multi-products and low volume and one-of-a-kind production (OKP) environments using simulation. We propose five basic design patterns of CONWIP loop and develop eight control policies of CONWIP loop based on the design pattern for standard assembly system. The performance of developed loop policies is evaluated in three production environments. In particular, control policies of CONWIP loop in OKP environment provide a valuable reference for OKP shop floor controlling. A heuristic algorithm of searching work-in-process (WIP) upper bound, the deadlock phenomenon in CONWIP assembly system and suggestion are introduced specifically. The summary of CONWIP installation guidelines in the mixed assembly system can apply CONWIP theory to practise. [ABSTRACT FROM AUTHOR]

The design of logistics distribution system for an assembly line with given layout is usually constrained by various factors such as the vehicles for the distribution of assembly components and the paths on the shop floor for the vehicle movement. Since design optimisation of these production systems with such constraints is hard to solve by mathematic approaches, simulation-based approach is mostly used. In this paper, simulation-based analysis and optimisation of a logistic distribution system is performed combined with a heuristic algorithm to obtain a solution that most suits the practical requirements of an assembly line. The proposed simulation-based method builds a model that satisfied various complicated real-world problems at the work site of an investigated factory. Meanwhile, a dynamic dispatching method for vehicle movement is also presented which can adjust the control strategy and decision parameters dynamically in the process of simulation and contributes significantly to form a more fruitful design scheme. Experimental results show that proposed method performs better than the analytical model-based approach and some other methods, and the dynamic vehicle dispatching method presented performs better than some existing common strategies used in literature. [ABSTRACT FROM AUTHOR]

Traditional simulation modelling focuses upon the analysis of steady-state data. This focus may not be appropriate, however, for the study of transient responses – data reflecting some form of disruption or change in the system norms. Transient responses are often encountered when dealing with new product introductions, changes in production systems, or supply chain disruptions. In these situations, it is the transient response, how the system responds to these changes as well as the tactics and strategies used to deal with these changes, that tend to be of the greatest interest. Unfortunately, current approaches that focus on analysing such responses are limited. This paper introduces a new approach for analysing transient responses – one that merges outlier detection, a time series analysis tool, with simulation modelling. This combined approach allows the researcher to identify those factors that have the greatest impact upon operations during these transient conditions. Using a simulated supply chain disruption to illustrate the potential of the approach, it is shown that the new approach expands the applicability of simulation and enables certain types of problems to be investigated with confidence not previously provided. [ABSTRACT FROM PUBLISHER]

Automated manufacturing systems have been studied widely in terms of scheduling. As technology evolves, the behaviour of tools in automated manufacturing systems has become complicated. Therefore, mathematical approaches to the analysis of complex schedules no longer reflect reality. In this paper, we propose a systematic way of conducting simulation experiments to evaluate the complex operating schedules of automated manufacturing systems. A simulation model is based on a timed Petri net to take advantage of its mathematical strength. Since a Petri net cannot itself have token firing rules, we introduce additional states called operational states. Operational states are not directly related to a Petri net, and are only used for decision making. In addition, a decision function that is responsible for the conflict resolution of a Petri net model and an operational state transition function are introduced. The parallel simulation concept is also suggested by dividing a Petri net into several independent decision sub-nets. A multi-cluster tool system for semiconductor manufacturing is analysed as an application. [ABSTRACT FROM PUBLISHER]

The characteristic of layered manufacturing is the incremental build-up which inevitably leads to the staircase effect. One method to reduce this effect is to optimise part orientation and to apply adaptive slicing procedures. Although layer thickness will be decreased in some regions, process efficiency can be kept to a reasonable level. This paper presents different approaches of adaptive slicing for laser-based applications in consideration of limited range of thickness variation to ensure the mechanical part properties. In contradiction to previous work, the number of applied layer thicknesses is limited due to the associated process parameters. In order to optimise the slicing process and to obtain the best results, this paper presents a practicable approach based on existing work to simulate adaptive slicing. To underline the potential of non-uniform slicing, illustrative examples will show possible improvements in the case of replacing the uniform slicing procedure. [ABSTRACT FROM AUTHOR]

This paper provides an executable design framework for modelling and controlling holonic manufacturing processes and systems. This framework is based on reconfigurable manufacturing holonic modules. These holonic modules consist of holons represented using parameterised Petri Net modules. As the suggested modelling framework shares advantages of IEC 61499 and FCPN-std, it supports the design of complex holonic manufacturing processes/system and allows simulation and analysis under general manufacturing uncertainties. Self-organisation activity in a holonic manufacturing system is explained using an evolution concept. A holon's inner evolution is executed through cascading parameterised Petri Net modules. This evolution is used for capturing the dynamic characteristics of a manufacturing environment. Routeing and reconfiguration is fulfilled through configuration evolution. It is achieved using the suggested constraint-based fuzzy Q-learning algorithm. The provided framework and two evolution algorithms are considered an executable design framework for modelling and controlling holonic manufacturing system. [ABSTRACT FROM AUTHOR]

This paper presents a non-rigid part variation simulation method for fulfilling functional requirements on compliant assemblies. This method is based on the propagation of different geometrical deviations (manufacturing and assembly process defects) using the method of influence coefficient. Tolerance analysis of compliant assemblies is also achieved very early in the design stage. As a consequence, designers and manufacturing engineers can efficiently analyse the assembly design principles both in terms of installed stresses and geometric variation clearance. They can also set optimised sequences that enable ridding of geometric variations. [ABSTRACT FROM AUTHOR]

Low-volume high-complexity printed circuit board manufacturing is a highly dynamic domain because of prevailing global pressures. In such an evolving environment, quality issues caused by manufacturing defects are the major concern. The generation, detection and elimination of those defects further impact customer requirements and demands. Current practices in terms of identification and solution of quality issues have three major drawbacks: (i) the metrics used are not meaningful; (ii) several manual operations are involved; and (iii) there is no significant decision support. A novel integrated simulation tool for quality support in low-volume electronics manufacturing that overcomes these weaknesses is presented in this paper. The simulation tool supports current needs in the domain, i.e. knowledge capitalisation, waste reduction, right-first-time performance and agility, as well as the domain customer requirements, i.e. lead time, cost, quality and reliability. Quantitative results from a case study are presented as evidence of the usefulness of the tool in a real context. The results show that the approximately 80% non-value-added cost for the product studied is due to just two types of manufacturing defects. This outcome is key for root cause analysis based not only on defect quantity. [ABSTRACT FROM AUTHOR]

This paper addresses the generic problem of production planning in a divergent timber production environment. It aims at analysing the performance of various demand-driven production strategies of a timber production system. This analysis is performed using a simulation platform built on an agent-based advanced planning system. Nine production strategies configurations are evaluated under six scenarios in order to carry out a complete mixed level design of 54 simulation runs. Each of these configurations is a combination of a decoupling point position and a level of capacity that is committed to contracts with customers. Accordingly, the six scenarios are designed as a combination of supply type (i.e. log diameter distribution) and timber market prices. Production processes and co-production yields are based on a real manufacturing system from eastern Canada. Performance is evaluated from the logistic and economic points of view. Results demonstrate that demand-driven planning approaches that propagate demand information upstream the supply chain have the potential to improve planned customer service and reduce planned inventories. Results also show that timber companies need to receive a premium from their customers in order to compensate from the loss of potential value resulting from a more constrained planning environment. [ABSTRACT FROM AUTHOR]

In this paper, we consider a rescheduling problem where a set of jobs has already been assigned to unrelated parallel machines. When a disruption occurs on one of the machines, the affected jobs are rescheduled, considering the efficiency and stability measures. Our efficiency measure is the total flow time and stability measure is the total reassignment cost caused by the differences in the machine allocations in the initial and new schedules. We propose a branch and bound algorithm to generate all efficient solutions with respect to our efficiency and stability measures. We improve the efficiency of the algorithm by incorporating powerful reduction and bounding mechanisms. Our computational tests on large sized problem instances have revealed the satisfactory behaviour of our algorithm. [ABSTRACT FROM AUTHOR]

Process analysis is recognized as a major stage in business process reengineering that has developed over the last two decades. Manufacturing process analysis (MPA) is defined as performance analysis of the production process. A manufacturing process analysis framework is outlined with emphasis on linking a company's strategy to operational process. Two issues, namely process modelling and simulation based analysis, are investigated. A compound workflow model (CWM) is proposed to provide graphic presentation of the production process that can be easily understood. Also it can be used directly by simulation to study the impacts of scheduling policy and analyse the process performance. A two-stage simulation analysis method is provided to quantitatively and efficiently define cause-and-effect relations to identify drivers for improvement. The manufacturing environment, PSC (production planning, scheduling and control) factors and the process structure are three main concerns considered in the simulation. An example is discussed in the final part of the paper. [ABSTRACT FROM AUTHOR]

This paper presents a new job release methodology: WIPLOAD Control (WIPLCtrl), which is a workload limited release methodology for the overall shop floor. The behaviour of WIPLCtrl is analyzed using the Markov process model of a transfer line system to observe the potential advantage of WIPLCtrl relative to the conventional measure of system workload using the WIP level. A simulation experiment is then conducted considering a simplified semiconductor wafer fabrication system. The performance of WIPLCtrl is compared with that of an open-loop release methodology and three other closed-loop workload limited release methodologies. A case study is also carried out by simulating a real-life wafer fabrication, considering the complexities and the distinguishing features of semiconductor manufacturing. The experimental results indicate that WIPLCtrl is an efficient job release methodology, capable of reducing both the mean and the standard deviation of the cycle time for a given throughput level. The performance of WIPLCtrl appears to be reliable with the increase of system congestion level and the increase of system variability caused by stochastic factors such as machine unreliability and processing time variability. [ABSTRACT FROM AUTHOR]

Modern flexible manufacturing systems (FMS) are highly automated and flexible in which raw parts of various types are processed concurrently. Deadlock issue arises easily in these systems due to shared equipment usage and high production flexibility. It was indicated in Wysk et al. (Wysk, R., Yang, N. and Joshi, S., Detection of deadlocks in flexible manufacturing cells. IEEE Trans. Rob. Auto., 1991, 7, 853-859.) that when a manufacturing system is modelled by a digraph, existence of circuits in such a graph is a necessary condition for deadlock. Deadlock avoidance for systems with free choice in part routing has been well studied in the Petri net formalism, however, we have not found that it has been studied systematically in the digraph formalism. Because of choices introduced, part flow dynamics become much more complex. Based on our previous work Zhang et al. (Zhang, W., Judd, R.P. and Paul P., Evaluating order of circuits for deadlock avoidance in a flexible manufacturing system. Int. J. Prod. Res., 2006, 44, 5247-5259.), this paper presents a deadlock avoidance algorithm for FMS, which allows free choices in part routing by calculation of effective free space of circuits of the digraph model. The algorithm is highly permissive since the effective free space calculation captures more parts flow dynamics, especially when there exist multiple knots in the digraph model. And it runs in polynomial time once the set of circuits of the digraph is computed offline. Simulation results on selected examples are given. [ABSTRACT FROM AUTHOR]

The double exponentially weighted moving average (EWMA) controller is a popular algorithm for on-line quality control of semiconductor manufacturing processes. The performance of the closed-loop system hinges on the adequacy of the two weight parameters of the double EWMA equations. In 2004, Su and Hsu presented an approach based on the neural technique for 'on-line' tuning the weight of the single EWMA equation in the single-input single-output (SISO) system. The present paper extends the neural network on-line tuning scheme to the double EWMA controller for the non-squared multiple-input multiple-output (MIMO) system, and validates the control performance by means of a simulated chemical-mechanical planarization (CMP) process in semiconductor manufacturing. Both linear and non-linear equipment models are considered to evaluate the proposed controller, coupling with the deterministic drift, the Gaussian noise and the first-order integrated moving average (IMA) disturbance. It has been shown from a variety of simulation studies that the proposed method exhibits quite competitive control performance as compared with the previous control system. The other merit of the proposed approach is that the tuning system, if sufficient training in a neural network is available, can be practicably applied to complex semiconductor processes without undue difficulty. [ABSTRACT FROM AUTHOR]

This paper presents the results of a simulation-based performance comparison between dynamic cellular (DC) manufacturing systems and two other well-known systems, namely classical cells (CC) and job shop systems (JS). The performance comparison is made at different levels of turbulence. The experiment contains 13 independent variables, most of them related to demand turbulence, and 17 dependant variables related to performance measure. A stochastic simulation model developed on Microsoft Visual FoxPro 5.0 was used in combination with LINDO (a linear/integer programming software) to obtain the initial results. In view of the large number of variables and the time required to run each experiment, a Taguchi plan was used to optimize the model. The results obtained from the analysis of variance indicate that dynamic cellular manufacturing systems are generally more efficient than classical cellular systems or job shop systems, especially with respect to the average and maximum throughput time, mean and maximum work-in-process, mean and maximum tardiness, and the total marginal cost for a given horizon. [ABSTRACT FROM AUTHOR]

Value stream mapping (VSM) has become a popular implementation method for Lean manufacturing in recent years. However, its limitations such as being time-consuming, its inability to detail dynamic behaviour of production processes and to encompass their complexity, have spurred us to turn to simulation. This paper introduces two new elements to the value stream mapping method. First, it describes how the value stream mapping paradigm (VSMP) can be adapted for use in simulation, introducing specially designed VSM objects. Secondly, based on the VSMP and these objects, it presents a formal modelling method and its related database structure, that drives a generator which automatically yields a simulation model of the value stream map. In this way, a model generator, using the set of objects and the model database, can generate simulation models of Current and Future VSM scenarios quickly and automatically. Additionally, algorithms for converting raw ERP data and information from a VSM drawing into tables of the structured database are developed. Finally, the formal modelling method is applied to a real company case. A Current State model of the manufacturing system and three scenarios of Future States are generated to see the effects of Lean when transforming part of the system from push to pull. [ABSTRACT FROM AUTHOR]

The selection process of a machine tool has been a critical issue for companies for years, because the improper selection of a machine tool might cause many problems having a negative effect on productivity, precision, flexibility, and a company's responsive manufacturing capabilities. Therefore, in this paper, to determine the best machine tool satisfying the needs and expectations of a manufacturing organization among a set of possible alternatives in the market, a hybrid approach is proposed, which integrates an analytic hierarchy process (AHP) with simulation techniques. The AHP as one of the most commonly used multiple criteria decision-making methods is used to narrow down all possible machine tool alternatives in the market by eliminating those whose scores (or weights) are smaller than a determined value obtained under certain circumstances. Then, a simulation generator is used first to automatically model a manufacturing organization, where the ultimate machine tool will be used, and second to try each alternative remaining from the AHP as a scenario on the generated model. Finally, the final alternative is selected by using the unit investment cost ratio, which is calculated by dividing the investment cost per year of each alternative by the additional number of produced units obtained from the simulation experiment of the relevant alternative. [ABSTRACT FROM AUTHOR]

The paper describes a simulation-based optimization system for manufacturing processes. The principle suitability of simple Threshold Accepting and Great Deluge Algorithms for optimizing practical manufacturing systems is shown, as well as the possibility of parallelizing of these algorithms. A special IP Multicast architecture is introduced which allows the simulation model to be extended to multiple clients and so the efficiency of the optimization algorithms to be increased by concurrent simulation. Each client can log on or log out at an optimization server at any time so that it should be possible to use the idle computer capacity of a single production department or a whole company. The optimization server is implemented as an experimental option in the simulation system simcron MODELLER®, which is particularly used in electronics and semiconductor manufacturing. [ABSTRACT FROM AUTHOR]

To meet the rapidly changing customer needs in the manufacturing environment, future manufacturing systems must be dynamically and flexibly reconfigured. The fractal manufacturing system (FrMS) is one of the new manufacturing paradigms that can meet such requirements. The basic component of the FrMS is referred to as a fractal. Consisting of self-similar agents, each fractal autonomously cooperates and negotiates with others to coordinate its tasks. Dynamic restructuring process (DRP) supports reorganization of the system configurations so that the FrMS can be adapted to dynamically changing environments. Although traditional approaches have endeavoured to demonstrate reconfigurability of a manufacturing system, they are not accurate enough to meet the requirements of circumstances such as high-level autonomy in reconfiguring the system architecture. In this paper, therefore, the DRP, which embodies self-reconfigurability of a system, is proposed focusing on the FrMS. To check the effectiveness of the DRP, we have developed the FrMS test bed and conducted the experimentation on the DRP. A simulation study has been conducted to show the effectiveness of the DRP under an illustrative situation. [ABSTRACT FROM AUTHOR]

Simulation metamodelling has captured the attention of various researchers due to its ability to estimate the simulation responses corresponding to a given combination of input variables, and to provide broad insights than simulation models alone. In this paper, the metamodelling approach has been extended by proposing a new methodology that incorporates the aid of two soft computing tools: neurofuzzy network and polynomial neural network. To perform post metamodelling analysis, an artificial immune system (AIS) based optimization algorithm has been used. Unlike in most neural-networks, the number of layers and number of nodes in each layer of the proposed hybrid network are not predetermined but can be generated dynamically through a growth process. AIS based optimization algorithm has been utilized to exploit the solution space much more extensively to generate an optimal configuration. The special features of the proposed methodology are the rate of convergence, computational speed, and quality of solution. To validate the procedures developed here, the authors have considered a well-known case study of a PCB manufacturing plant. The obtained results show that the proposed methodology can be applied to solve complex manufacturing system design problems in a more effective and efficient manner. [ABSTRACT FROM AUTHOR]

Drum–Buffer–Rope (DBR) is an alternative approach to manufacturing planning and control that is not as formally tested as Material Requirements Planning (MRP) systems which have traditionally been around for years. Yet, some reports indicate very good performance for DBR and the associated use of synchronous manufacturing principles. But how do these systems compare and relate to one another? Based on our experiences of studying a Bearing Manufacturing Company that actually made the transition from an MRP system to a DBR system, we conduct simulation-based experiments in this paper with the objective of providing a more formal comparison between these two systems than what has been offered in prior literature. To our knowledge, this is the only study of its kind that uses a real-world setting to evaluate key differences and convergence points between comprehensive MRP and DBR systems. Our results show that even though the MRP and DBR systems position inventory differently and provide different dynamic responses to customer demand, there are several operating policies that can be implemented in either system. While the DBR performance in our simulation model was clearly superior to a nominal MRP implementation, we show that even within the constraints of the structural design of MRP system, policy modification based on DBR principles can significantly reduce these performance differences. This finding has an important implication for practising managers who need not necessarily switch from a MRP system to a DBR type of a system (as was done by our case-study firm) in order to take advantage of attractive features of the DBR system. Future researchers can use our study to understand more fully how these Structural Design and Operating Policy differences can be further exploited to implement unique systems that combine the best features of both DBR and MRP systems. [ABSTRACT FROM AUTHOR]

In the past two decades, simulating workpiece–fixture interactions has remarkably drawn the attention of academia. However, many aspects of the workpiece–fixture system, specifically workpiece–fixture contact condition, still enjoy research effort. For the efficient use of Automated Fixture Design (AFD) systems, verification of their outputs is required. This paper presents a workholding simulation approach that considers assessment of AFD system outputs regarding different workholding parameters. The effect of friction forces on workholding and part rigid body stability is considered. Besides, determining deformation and stress in the workpiece, locators and clamps are modelled and their elastic deformation and stress distribution are computed. A procedure based on the application of contact elements in finite-element method is developed to quantify the status of contact between the workholding elements and the workpiece. Clamping tightness is modelled and its effect on the workpiece–fixture system performance is quantified. The central component of the verification tool is the use of nonlinear finite-element analysis to model the frictional interactions in workpiece–fixture system. [ABSTRACT FROM AUTHOR]

Machine selection during the initial stages of facility planning is critical as most capital costs are incurred in the investment of new machines. This paper presents an approach for optimizing the number of machines acquired for batch processing in a multistage manufacturing system. Machines of the same type differ in their processing capabilities. Four cases of overlap in machine capabilities are examined. For each case, the problem is optimized with and without the time balance constraints between the stages. The output is the optimum number of machines of each type to be purchased for each stage, as well as the optimum time delay between the stages such that the system cost is minimized. The resulting multistage line is then simulated under specified conditions to observe its behaviour over time and to assess the viability of the developed model. [ABSTRACT FROM AUTHOR]

Although simulation is a popular tool for modelling and analysing modern manufacturing systems, to model shop floor control systems (SFCSs) in simulation requires quite costly efforts, since they are responsible for resolving various decision problems, such as deadlock, part dispatching, and resource conflict. The objective of the paper is to address a conceptual framework necessary to generate a WITNESS simulation model automatically from graph-based process plans and resource configurations. A graph-based process plan is used to capture part operations, their related resource requirements, and their temporal precedence relationships. A WITNESS simulation model is a graphical representation of shop floor resources with the part flow logic embedded within each resource element. To generate a WITNESS model, a process plan is automatically converted into a machine-centred part routeing graph (MCPRG) and then a transport-tending part routeing graph (TTPRG). The MCPRG implies part flows among machines, in which a node represents a machine and an edge represents a part route. The TTPRG implies part flows among machines and material handling devices, in which a node represents either machine or material handler, and an edge represents a part route. From the TTPRG, the part's input and output rules for each resource can be automatically extracted and plugged into the WITNESS model. The approach proposed in the paper enables manufacturers to generate a simulation model rapidly and effectively for performance measurement, such as bottleneck identification, work in progress, throughput times, dynamic resource utilization, and deadlock, of the SFCSs. [ABSTRACT FROM AUTHOR]

This paper presents a flow approximation of production networks with finite buffers and unreliable machines. Parts of various types compete for service before a machine, or they may be assembled before service to yield a composite part. Up times and down times of machines have arbitrary but known distributions and service times have gamma distributions, or may be constant quantities. Random service times are approximated by piece wise deterministic variables. Acyclic networks are considered first. The model is a combination of discrete-event simulation and analysis. The simulator keeps track of the buffer and machine states. Between two consecutive state transitions, flow rates remain constant and the model calculates the cumulative flow of each part type. Compared to a conventional simulator, the model is superior in speed and very accurate. An alternative model is developed for nonacyclic production networks where each machine provides service to different parts repetitively. The model is employed to simulate a re-entrant production line under a class of heuristic scheduling policies. The optimal policy is the one that meets demand while maintaining small buffer sizes and short delays of parts. [ABSTRACT FROM AUTHOR]

Economic justification of the use of industrial robots in general-purpose assembly is often necessary prior to implementation. This can only be achieved by realistic analysis and simulation throughout the design and planning of robot-based assembly systems. This paper describes a research project which aims to develop a kinematic and stochastic simulation model to represent the organization and layout of robot-based assembly systems and to evaluate their respective techno-economics viability. It summarizes the various forms of assembly systems, examines the state-of-art in robotic assembly, and identifies alternative organization of robot-based systems. Existing economic models are reviewed and the important role of a model based on analysis and simulation is emphasized. It also states the objective and boundary of the research programme. The paper is concluded by outlining the design methodology adopted by the model and the techniques used in its implementing. [ABSTRACT FROM AUTHOR]

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Friction spot welding (FSJ) process is very complicated in the aspects of material flow, heat generation and joining mechanism. Compared with the friction stir welding (FSW) process for a butt joint, the FSJ process is used to join two pieces of plate in the direction of thickness. Although there are several papers describing simulation models for the FSW process, we cannot find any papers relating to simulation models for the FSJ process. In order to simulate the FSJ process efficiently, an axis-symmetric two-dimensional FEM model with an adaptive re-meshing algorithm is proposed. By using the proposed model, temperature distribution, joining shape of the transverse section including toe flash on the surface and hook on the joining interface, can be simulated. The simulated results agree well with those of the experiment. Furthermore, effects of clamp position and stirring direction on material flow and joining shape are investigated. [ABSTRACT FROM AUTHOR]

Recent developments in supply chain planning have emerged from the field of agent technology and distributed decision making. Although several attempts have been made to exploit agent technology to design supply chain simulation tools, the integration of simulation with distributed supply chain planning tools is still a challenge. This paper aims at investigating this aspect of supply chain planning simulation through the use of theoretical contributions found in the field of simulation, systems theory, distributed decision making and agent-based software engineering. More specifically, this paper first proposes a conceptual framework for modeling “distributed agent-based Advanced Planning and Scheduling” (d-APS). Next, derived from this framework, it proposes some specific methods for understanding and modeling simulation problems at the initial phase of the modeling effort. This early phase is critical because it considerably influences the whole development process and the resulting simulation environment, but it is usually neglected in the concerned literature. Finally, a theoretical illustrative case is presented in the lumber supply chain. [ABSTRACT FROM AUTHOR]

This paper presents approximation methods for the performance analysis of long manufacturing lines, i.e. lines with more than two machines and one buffer, that have both quality and operational failures. We describe three different versions of long flow lines that differ in the locations of the inspection stations and in the sets of machines that each inspection station monitors. We explain a transformation method that approximates long manufacturing lines that have quality and operational failures with long lines that only have operational failures. Such lines can be evaluated by decomposition methods. We introduce other approximations to quantify the effects of the separation of inspections from operations. Comparison with simulation shows that the solution methods provide reliable performance estimates. [ABSTRACT FROM AUTHOR]

This paper presents an investigation into a system of linear walking-worker (WW) assembly lines that have been implemented in a local small and medium enterprise (SME). The work aims to observe the relevant impact on logical interactions and interrelationships between the number of workstations and the number of walking workers against the system performance and to minimize these numbers providing a quick response in re-configuration of the system to meet a given output and cycle time. This has been achieved by developing a simulation model for a theoretical study into the linear WW system using a manufacturing-focused simulation tool. By examination of the results of a series of simulation experiments, a minimization of the numbers of workstations and walking workers for a linear WW line configuration can be quantified. The research concluded that this multiskilled linear WW assembly line is able to sustain a higher flexibility and efficiency as compared with a conventional linear fixed-worker (FW) assembly line under similar conditions. [ABSTRACT FROM AUTHOR]

Injection molding is a very mature technology, but the growth of layer-build, additive, manufacturing technologies (rapid prototyping, RP) has the potential of expanding injection molding into areas not commercially feasible with traditional molds and molding techniques. This integration of injection molding with rapid prototyping has undergone many demonstrations of potential. What is missing is the fundamental understanding of how the modifications to the mold material and RP manufacturing process impact both the mold design and the injection molding process. In addition, numerical simulation techniques have now become helpful tools of mold designers and process engineers for traditional injection molding. But all current simulation packages for conventional injection molding are no longer applicable to this new type of injection molds, mainly because the property of the mold material changes greatly. In this paper, an approach to accomplish numerical simulation of injection molding into rapid-prototyped molds is established and a corresponding simulation system is developed. For verification, an experiment is also been carried out with an RP fabricated SL mold. Stereolithography (SL) is an original and typical rapid-prototyping method, which is chosen as the study object in the paper. [ABSTRACT FROM AUTHOR]

While discrete event simulation technology holds tremendous promise and has a strong and established background, manufacturing industry has been less than successful in the implementation of simulation as a decision support tool. This paper reports on research into developing simulation into a sustainable desktop resource to be used continuously by various manufacturing personnel as a decision support tool. A case study approach was used to carry out the research. The manufacturing system used was a medium-sized facility that could be categorized as a batch flow-shop that produces a large range of products. The simulation software was developed using the object-oriented simulation package eM-Plant®. In designing the simulation model, emphasis was placed on integrating with the manufacturing company's information systems and reducing the resources required to maintain the software. The simulation software was successfully used for both strategic and short-term planning. However, as a sustainable resource within the company, the simulation model developed was only partially successful. The main difficulties identified were in model maintenance and data collection. The main conclusions of the paper are that: (1) simulation places specific requirements on information systems which need to be taken into consideration if simulation is to be successfully implemented as a desktop resource; (2) improvements in simulation software are required to reduce model maintenance resource requirements; and (3) research on socio-technical issues into simulation use within manufacturing is required. [ABSTRACT FROM AUTHOR]

In this paper, a structure and architecture for the rapid realization of a simulation-based real-time shop floor control system for a discrete part manufacturing system is presented. The research focuses on automatic simulation model and execution system generation from a production resource model. An Automatic Execution Model Generator (AEMG) has been designed and implemented for generating a Message-based Part State Graph (MPSG)-based shop level execution model. An Automatic Simulation Model Generator (ASMG) has been designed and implemented for generating an Arena simulation model based on a resource model (MS Access 97) and an MPSG-based shop level execution model. A commercial finite capacity scheduler. Tempo, has been used to provide schedule information for the Arena simulation model. This research has been implemented and tested for six manufacturing systems, including The Pennsylvania State University CIM laboratory. [ABSTRACT FROM AUTHOR]