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The main problem treated in this paper is that if we want to optimize a network of manufacturing systems design using discrete material flow management we need a new algorithm different from the one used for a single manufacturing system. For a single manufacturing system we usually use discrete material flow simulation to identify and eliminate bottlenecks where the flow is slowed down or blocked in order to increase the productivity. For a network of manufacturing systems material flow concentrators could be the bottlenecks found in one of the manufacturing systems using this classical discrete material flow simulation but it also could be a new different one. We focus in this paper on the algorithm we propose to solve this problem of identifying and eliminating not the bottlenecks of each manufacturing system but of the entire network. A case study of multipolar synchronous simulation (as we named our proposed algorithm) is presented in order to illustrate across a tree nodes manufacturing network how this new algorithm works. [ABSTRACT FROM AUTHOR]

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Process manufacturing industries are complex and dynamic systems composed of several processes, subject to many operations and unexpected events that can compromise overall system performance. Therefore, the use of technologies and methods that can transform traditional process industries into smart factories is necessary. In this paper, a smart industrial process based on intelligent software agents is presented with the aim of providing a technological solution to the specific needs of the process industry. An event-driven agent-based simulation model composed of eight reactive agents was designed to simulate and control the operations of a generic industrial process. The agents were modeled using the actor approach and the communication mechanism was based on the publish–subscribe paradigm. The overall system was tested in different scenarios, such as faults, changing operating conditions and off-spec productions. The proposed agent-based simulation model proved to be very efficient in promptly reacting to different dynamic scenarios and in suitably handling different situations. Furthermore, the usability and the practicality of the proposed software tool facilitate its deployment and customization to different production chains, and provide a practical example of the use of multi-agent systems and artificial intelligence in the context of industry 4.0. [ABSTRACT FROM AUTHOR]

The present paper aims to describe the development of a FEM model for the simulation of a die-sinking micro-EDM process. A commercial FEM code specific for the simulation of thermo-mechanical forming processes was used. The developed model was based on the capacity of the code to simulate the removal process or the separation of the material through the mesh element deletion. The electrical discharges were simulated through a proper heat flux and the material melting temperature was set as a trigger for the element deletion. The heat flux was related to the EDM process parameters by means of mathematical models selected from the literature. In the first part of the present work, a model based on a single discharge analysis was developed; then, the model was extended to a sink EDM process characterised by repeated discharges. The model was validated in terms of machining time, top diameter and MRR by the execution of experimental tests. [ABSTRACT FROM AUTHOR]

This paper presents an agent-based construction supply chain simulator (CS2) that leverages computer agents technology for modeling a virtual construction supply chain. Although construction managers and contractors do not consciously consider a supply chain and its management, they all interact with the members of a supply chain and make related decisions. Having real-time information available at any time can increase information transparency, which in turn makes it easier for project managers to identify potential risks. CS2 is a modified version of the beer game that has been widely used for illustrating the importance of real-time information in the manufacturing process. Two different types of simulations are presented in this paper, namely human-to-human and computer-to-human interactive simulation. In the simulations, a group of people play different roles, as does the current practice in construction. Results of this simulation test and verify the significance of real-time information sharing in construction. In addition, how the quantity of information affects the value of real-time information using the concept of illusion in cognitive science is investigated. The developed CS2 can be further used for educational purposes as well as for addressing the valuable lesson of real-time information sharing to practitioners. [ABSTRACT FROM AUTHOR]

In this paper, a platform based on the composite-IC concept that is optimized for high-frequency (HF) applications will be presented. Surface-micromachined microsprings are used for temporary connection and testing. This provides the system with an individual compensation of different contact heights due to production tolerances. In addition, self-alignment structures have been added to compensate lateral tolerances. The presented self-alignment structures were designed to compensate rising precision requirements in contrary to commonly used placing machines. Key elements of the HF platform are coplanar waveguides and microsprings that are processed using microelectromechanical-system technologies on alumina ceramic. Microsprings with outer dimensions between 2000 and 125 μm with different beamwidths, beam thicknesses, and beam lengths were designed, simulated, and fabricated. All structures were tested mechanically and electrically. As a further development, spiral microsprings are presented. These combine minimal space requirement with no preferred orientation. Positioning in an individual array is possible. Due to the design and the integration of the spiral microsprings as part of the flip-chip connection, the scattering parameters show excellent HF performance up to frequencies of 9 GHz. The same microsprings could also be used for onboard testing on multichip modules (MCMs). This provides the MCM with cheap and powerful testability and reworkability. This paper covers the mechanical and electrical design, simulation, optimization, production, and characterization of suitable microsprings. [ABSTRACT FROM AUTHOR]

The concurrent design of materials and products provides designers with flexibility to achieve design objectives that were not previously accessible. However, the improved flexibility comes at a cost of increased complexity of the design process chains and the materials simulation models used for executing the design chains. Efforts to reduce the complexity generally result in increased uncertainty. We contend that a systems based approach is essential for managing both the complexity and the uncertainty in design process chains and simulation models in concurrent material and product design. Our approach is based on simplifying the design process chains systematically such that the resulting uncertainty does not significantly affect the overall system performance. Similarly, instead of striving for accurate models for multiscale systems (that are inherently complex), we rely on making design decisions that are robust to uncertainties in the models. Accordingly, we pursue hierarchical modeling in the context of design of multiscale systems. In this paper our focus is on design process chains. We present a systems based approach, premised on the assumption that complex systems can be designed efficiently by managing the complexity of design process chains. The approach relies on (a) the use of reusable interaction patterns to model design process chains, and (b) consideration of design process decisions using value-of-information based metrics. The approach is illustrated using a Multifunctional Energetic Structural Material (MESM) design example. Energetic materials store considerable energy which can be released through shock-induced detonation; conventionally, they are not engineered for strength properties. The design objectives for the MESM in this paper include both sufficient strength and energy release characteristics. The design is carried out by using models at different length and time scales that simulate different aspects of the system. Finally, by applying the method to the MESM design problem, we show that the integrated design of materials and products can be carried out more efficiently by explicitly accounting for design process decisions with the hierarchy of models. [ABSTRACT FROM AUTHOR]

Over the past quarter century, much effort has been devoted to the design and development of simulation modeling languages, and to methods for the development of simulation models themselves. Less effort, however, has been expended on the design of the experimental models upon which simulation studies are based. This paper describes a methodology for the determination of near optimal solutions considering experimental design and simulation modeling. Using this methodology, simulation scenarios are created and analyzed using an analysis of variance (ANOVA)-based experimental design. This paper also presents an application of this method in analyzing a manufacturing system design problem. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of periodic disturbance rejection arising from rotational plants following periodic trajectories. Repetitive control is a method usually employed in solving such a problem. The reported analysis results give sufficient conditions for stability of the controlled systems in the frequency domain. In this paper, discrete-time variable-structure repetitive control (VSRC) is proposed, where the periodicity features are taken into account and no disturbance estimate is involved explicitly. The presented VSRC control scheme ensures robust stability of the resultant quasi-sliding-mode dynamics to parameter variations and exogenous disturbances. The complete rejection of periodic disturbances and the perfect tracking of periodic trajectories are achieved. Time-domain sufficient conditions for the robust stability are presented by which the controller parameters can be chosen. A numerical simulation is conducted to illustrate the validity of the developed method. [ABSTRACT FROM AUTHOR]

Purpose - Most manufacturing processes tend to involve more than one level of detail at the design phase. These often consist of a higher level that represents the building-blocks of the firm and a lower level that represents a more detailed structure of the process. When designing such processes, this type of structure is difficult to capture without some form of modelling. In such cases simulation can be used to help overcome this problem. This paper presents an investigation of simulation packages. Design/methodology/approach - These simulation packages were investigated regarding their abilities to model business processes related to manufacturing systems. Findings - The research findings suggest that no one simulation package currently available can alone offer sufficiently flexible facilities for the variable detailed modelling of manufacturing systems design. Originality/value - The paper relates to one specific design framework called manufacturing system design (MSD). It defines the higher level of detail as the conceptual modelling level and the lower level as the detailed design level. A four-step framework is proposed, and it is argued that this may better deal with problems of detail variability. [ABSTRACT FROM AUTHOR]

A manufactured home is completely built in a controlled factory environment. Despite a large share of the market, the manufactured housing industry has a long way to go towards streamlining its production process. The objective of this paper is to map the production process of a manufactured housing factory and to demonstrate via simulation how the process can be improved. The production process including assembly, feeder, and storage stations were mapped using data from several manufactured housing plants and in-depth case studies at two plants in northern Indiana. The case study plants were also used for collecting cycle-time data for developing the simulation model for the roofing process. Subsequently, four “what if” scenarios were conducted to illustrate potential improvements to the production process. The efforts presented in this paper are part of on-going research sponsored by the National Science Foundation under the Partnership for Advancement of Technology in Housing (PATH) initiative. [ABSTRACT FROM AUTHOR]

CdTe and CdTe-based Cd1-xZnxTe (CZT) alloys are important semiconductor compounds that are used in a variety of technologies including solar cells, radiation detectors, and medical imaging devices. Performance of such systems, however, is limited due to the propensity of nano- and micro-scale defects that form during crystal growth and manufacturing processes. Molecular dynamics simulations offer an effective approach to study the formation and interaction of atomic scale defects in these crystals, and provide insight on how to minimize their concentrations. The success of such a modeling effort relies on the accuracy and transferability of the underlying interatomic potential used in simulations. Such a potential must not only predict a correct trend of structures and energies of a variety of elemental and compound lattices, defects, and surfaces but also capture correct melting behavior and should be capable of simulating crystalline growth during vapor deposition as these processes sample a variety of local configurations. In this paper, we perform a detailed evaluation of the performance of two literature potentials for CdTe, one having the Stillinger-Weber form and the other possessing the Tersoff form. We examine simulations of structures and the corresponding energies of a variety of elemental and compound lattices, defects, and surfaces compared to those obtained from ab initio calculations and experiments. We also perform melting temperature calculations and vapor deposition simulations. Our calculations show that the Stillinger-Weber parameterization produces the correct lowest energy structure. This potential, however, is not sufficiently transferrable for defect studies. Origins of the problems of these potentials are discussed and insights leading to the development of a more transferrable potential suitable for molecular dynamics simulations of defects in CdTe crystals are provided. [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]

Simulation modeling results for powder mixtures comprised of saponite and stainless steel powders are presented. A literature review focusing on methods for modeling the filling and production of powder materials in technological processes was conducted. Computer modeling employed to examine the behavior of particulate mixtures in two-dimensional and three-dimensional planes, considering their volumetric characteristics, was studied theoretically. The properties of AISI430 steel and saponite powders, such as grain-size composition and sphericity factors, were studied experimentally. The density of workpieces made from steel and saponite powders for modified and unmodified powder particles was calculated as percentage. A method for calculating the distribution of particles and determining the density of workpiece layers using the ImageJ2x software was proposed. Image stacks were generated and image series were analyzed using object mask functions and threshold and image inverter brightness threshold functions. The processed microscopy data enabled the determination of void percentage within the visible areas of the samples. A simulation model was proposed to describe the formation of powder materials with varying geometries and sphericity. The process of filling a cylindrical container with the powder mixture was simulated. A 3D computer model was developed to visualize the formation of a two-component powder mixture using the Blender 3D application software. Maps depicting the distribution of powder particles in selected planes were constructed. [ABSTRACT FROM AUTHOR]

This paper stablishes the model of the integrated batch planning process, and proposes an improved algorithm for this problem. The simulation results of a computerized scheduling system are given to prove the fitness of the model. The steel making casting production process scheduling problem is very difficult to get a good performance solution in practice. The scheduling of steelmaking casting production is a complicated problem of combinational optimization in the hybrid flow shop, which is an NP-Hard problem, and determining the polynomial time algorithm to arrive at the accurate optimal solution has proved to be a difficult task. An improved fuzzy genetic optimization and improved algorithm strategy are proposed. The results show that the method is very efficient in solving the steel casting production scheduling problem. [ABSTRACT FROM AUTHOR]

The manufacturing of components requires several manufacturing process steps that are performed in a sequence, during which the raw material is progressively converted into finished parts. The aim with simulation of manufacturing sequences is to replicate the aggregate effects of the process steps on key features of the finished product and manufacturing features. With the support of a successful simulation methodology, it will thereby be possible for process planners to evaluate virtually and select process steps to be included in the manufacturing sequence and to optimize process parameters. The motivation to implement sequential simulation in industry is therefore strong and will reduce time and cost in process planning. The modelling and simulation of complete manufacturing sequences is, however, a challenge which may lead to unrealistic and time-consuming modelling efforts and extensive computational requirements. This is due to the often complex material transformations through several consecutive process steps. In order to adapt sequential simulation into an industrial environment, simplifications are therefore necessary. This paper proposes a method for simplified metamodelling of manufacturing sequences, using upstream selection of process steps and definition of interconnected models. The method is presented as an algorithm and will improve the efficiency in the modelling of manufacturing sequences. The usability of the algorithm is demonstrated with two industrial cases: a bevel gear pinion and a steering arm. [ABSTRACT FROM AUTHOR]

One of the goals of Industry 4.0 is to increase the transparency of the value chain through modern tools in production processes. This article aims to discuss the possibility of increasing the efficiency of a production system by modernizing it with the use of computer modelling tools. This article describes a method for the simulation modelling of a selected production system using the specialized FlexSim 2023 software in a 3D environment. The results and benefits of the practical application of the object-oriented modelling are presented, as well as the possibilities of collecting simulation data used to optimize production processes. The analyses were conducted at a selected production plant in a case study. The research assessed the effectiveness of the existing system and determined the impact of process changes in the event of the introduction of a new design solution. The simulation identified bottlenecks in the material flow. The basis for creating the simulation model was the analysis of the technological process. A simulation model for a real situation was created, and a simulation model was designed to identify and indicate a solution to eliminate the detection of the bottleneck. The problem area identified using visualization in the technological process slowed down the entire production process and contributed to time and economic losses. Thus, the authors confirmed the thesis that the simulation modelling of production systems using the FlexSim program can help eliminate bottlenecks and increase the efficiency of human resource use. At the same time, the use of this tool can lead to increased efficiency, reduced costs and improved sustainability and other performance indicators important for modern production environments as part of the promoted Industry 4.0 idea. A noticeable result of these changes was an increase in production from about 80–90 units. In addition, it was noticed that the condition of the machines preceding the stand changed. [ABSTRACT FROM AUTHOR]

A common manufacturing environment in many industries (such as the glass, steel, paper, costume jewelry, and textile industries) is a hybrid flow shop. This system has continuous-process machinery in the first stage of manufacturing and repetitive-batch equipment in the second. Little research has investigated this type of system. Scheduling managers of hybrid flow shops tend either to use existing job-shop rules or to devise their own rules. These approaches often are less than adequate for efficient scheduling. In this paper we extend the rule presented by Narasimhan and Panwalkar to include a general class of hybrid flow shops. This extension, called the generalized cumulative minimum-deviation (GCMD) rule, is compared under various operating conditions to three other sequencing rules: shortest processing time, longest processing time, and minimum deviation. The operating conditions are determined by the number of machines at both stages. The results of 7200 simulation runs demonstrate that the GCMD rule is better than the other rules in minimizing each of five chosen criteria. Thus, the GCMD rule can help managers to schedule hybrid flow shops efficiently to achieve various corporate objectives. [ABSTRACT FROM AUTHOR]

In an industrial production process, the leakage of continuous objects poses a serious threat to production safety. In this paper, a diffusion distance-based predictive tracking algorithm is proposed for industrial wireless sensor networks (IWSNs), aiming to timely track the boundary of a continuous object after the occurrence of a leak. Based on the assumption that the motion of the continuous object follows an appropriate diffusion model, sensor nodes are able to capture environmental parameters for establishing the mathematical expression of the model locally. Through building up the relation of diffusion radius with time, each node predicts diffusion scope of the continuous object at different times and makes a judgment about whether it is suitable to be a boundary node. Moreover, to achieve high energy-efficiency, a sleep/wake cycle is introduced to involve a small number of nodes in the process of tracking, while the rest of nodes stay idle until an object approaches. Finally, a cluster-based competitive mechanism is proposed for reporting the location of boundary nodes. Simulation results demonstrated that our proposal is able to track the diffusion of continuous objects with high energy-efficiency. [ABSTRACT FROM AUTHOR]

Investment decision dilemmas were since late 60's of previous century interesting for research from the perspective of financial dilemmas, while later, with arising uncertainty and dynamic of business environments, stochastic decisions problems needed more in-depth and complex considerations. High technology flexibility and multiple variation production process with significant losses related to resetting machine on one hand and great investment costs for new technology on the other hand, makes technology investment decisions in contemporary business environment multifarious. In this paper, we are presenting the case of optimizing investment decision dilemma in multiple variation production process. Using a discrete event simulation model we test two alternatives regarding the impact on predefined production indicators: 1) optimal grouping of the different products on an existing machine, 2) additional identical machine and optimal sorting of products between the existing and additional machine. In the paper, we determine indicators that should be monitored in investment decision dilemmas and design simulation model that can be used to calculate aforementioned indicators. [ABSTRACT FROM AUTHOR]

Production systems are composed of increasingly complex components with unique specifications. Therefore, since holding safety stocks of each component would be prohibitive, maintenance activities rely on the proper delivery of spare parts, making it available at the right time and place. Equipments monitored by sensors as well as the transmission of sensors data to the spare part supply chain represent an interesting venue for dealing with this contemporaneous industrial challenge. In this direction, this paper applies a simulation model derived from a real world scenario to analyze the performance of the collaboration between condition-based maintenance – also known as intelligent maintenance systems – and spare parts supply chains, in comparison with existing maintenance approaches. Obtained results substantiate the potential of monitoring, treating and transmitting equipment condition data to ensure cost-effective maintenance and production systems availability. [ABSTRACT FROM AUTHOR]

Additive manufacturing of polymers is transitioning from rapid prototyping to a true industrial production technique. While it brings valuable opportunities to the automotive industry, such as drastically facilitating the spare part supply chain or allowing multi-material and multi-functional designs, it also comes with a series of challenges for the engineers. The reliability of the mechanical properties of the final part still has some uncertainty and is not fully supported by standard engineering tools. Dimensional accuracy is not always met and cannot be predicted prior to printing. To support this transition, the engineering workflow which is daily applied for traditional manufacturing processes needs to be replicated and adapted to the additive manufacturing. Printer manufacturers, material suppliers and end-users need predictive simulation tools to bring the additive manufacturing efficiency and performance to the next level required by the industry. This paper presents a holistic simulation approach for additive manufacturing of plastics and composites, covering material engineering, process simulation and structural engineering of both SLS and FDM. [ABSTRACT FROM AUTHOR]

The aim of our study was to verify if rule-based reasoning systems could be successfully applied for integration of different models and tools which are used for solving complex decision problems in technological design. Engineering problems are unique and differ from typical problems in the domain of management. To solve those problems, an iterative search of the most suitable solutions must be carried out. This puts a pressure on researchers to utilize optimization techniques in connection with simulation methods. Our research is focused on the usage of rule-based reasoning systems for solving simple decision problems, and their integration with highly-specialized tools. This research has been conducted at one of metal foundries, within the scope of supporting technological decisions. A dedicated platform was used in the research, which is tailored for such applications, i.e., Business and Technological Rules Management System REBIT. REBIT system has been developed at the Faculty of Management at the AGH University of Science and Technology in Cracow. In this paper, we prove that the rule-based approach could provide means to integrate all stages of technological design. This kind of approach has been successfully applied in the Business Rules Management Systems. [ABSTRACT FROM AUTHOR]

Nowadays, computerized dimensional inspection is included in most manufacturing processes. Industrial vision systems, laser triangulation sensors (LTS) in particular, are responsible for ensuring dimensional and geometrical tolerance compliance. Computer-aided design / computer-aided engineering (CAD/CAE) plays an important role in the manufacturing process. However, in the design and engineering of LTS, there is no equivalent computer-aided tool to provide assistance to the process definition. This paper presents a simulation environment to assist with this issue. Based on the CAD files of the parts, all the parameters of an LTS sensor and its scanning strategy can be simulated in a virtual Direct3D environment. This simulation provides a re-creation of the camera acquisition, allowing collision and occlusion detection and ensures complete and effective digitalization. Furthermore, the capability of the process of tolerance compliance evaluation can be verified. Once the effectiveness of the process is proven, the simulation can be employed for continuous performance improvement and the incorporation of new parts. [ABSTRACT FROM AUTHOR]

5-axis hybrid additive-subtractive manufacturing is a new and promising technology for many industrial applications. Because of its complexity, the machining simulation is very important to verify the effectiveness of tool path. However, most simulation methods are proposed for subtractive manufacturing and additive manufacturing separately. This paper presents a novel geometric simulation technique for the 5-axis hybrid additive-subtractive manufacturing, which is based on Laser Engineered Net Shaping (LENS) and milling. In the proposed method, 5-axis additive swept volume elements are represented with Tri-dexel models and then converted into triangular meshes for visualization. Workpiece after additive manufacturing can be then used as a workblank for subtractive manufacturing simulation. Finally, a geometric simulation module is developed based on SIEMENS NX software to demonstrate the feasibility of the proposed simulation method. [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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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]

SUMMARY In this paper, we apply a stochastic differential equation (SDE) as a mathematical model that describes the manufacturing process from input of materials to the end of the process. We utilize the risk-neutral principle in stochastic calculus based on the SDE. We extend the mathematical model to allow for objective evaluation. In order to improve the lead time in a manufacturing process, we introduce an evaluation equation that satisfies a certain compatibility constraint with respect to the lead time; this compatibility constraint with lead time refers to a strategy that eliminates irrelevant processes from the overall process, and results in improvements to the process. We assume a probability density function of log-normal type, which is the probability density function from the input materials to the end of the process. The present paper evaluates a certain compatibility constraint with lead time by applying risk neutrality and the martingale measure of the stochastic integral under this assumption. After the evaluation value is calculated by the evaluation equation, a process control system evaluates each subprocess and performs rescheduling to improve the utilization efficiency of the entire manufacturing process. Thus, a front-end process is used to cancel requests to the process, and follows the instructions in the process control systems. However, the present paper gives only a simulation evaluation in which the parameters are calculated, and does not discuss compatibility between an evaluation value based on the calculated manufacturing lead time compatibility constraint and a real system. However, the paper offers an idea for finding bottleneck subprocesses in a manufacturing process, and for use as a software tool for process synchronization. [ABSTRACT FROM AUTHOR]