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Simulation-based optimization for industrial processlines is discussed in this paper. Our approach combinesmultidisciplinary modeling, modern sensitivity analysismethodology as well as multiobjective optimization bymeans of object-oriented software design principles. As aresult, a simulation and optimization approach that can beextended and modified due to users' needs can be developed.Our approach is illustrated by a real-world examplefrom papermaking industry. [ABSTRACT FROM AUTHOR]

In complex manufacturing systems, such as a semiconductor wafer fabrication facility (wafer fab), it is important to accurately predict cycle times and work-in-progress (WIP) levels. These key performance indicators are commonly predicted using detailed simulation models; however, the detailed simulation models are computationally expensive and have high development and maintenance costs. In this paper, we propose an aggregate modeling approach, where each work area, i.e., a group of functionally similar workstations, in the wafer fab is aggregated into a single-server queueing system. The parameters of the queueing system can be derived directly from arrival and departure data of that work area. To obtain fab-level predictions, our proposed methodology builds a network of aggregate models, where the network represents the entire fab consisting of different work areas. The viability of this method in practice is demonstrated by applying it to a real-world wafer fab. Experiments show that the proposed model can make accurate predictions, but also provide insights into the limitations of aggregate modeling. [ABSTRACT FROM AUTHOR]

With the introduction of new technologies, the scope of miniaturization has broadened. The conditions under which complicated products are designed, manufactured, and assembled ultimately influence how well they perform. The intricacy and crucial functionality of products are frequently only fulfilled through the use of high-precision components such as micro gears. In power transmission systems, gears are used in a variety of industries. Micro gears or gears with micro features, with tolerances of less than 5 μm, are pushing manufacturing processes to their technological limits. Monte-Carlo simulation methods enable an accurate forecast of inaccuracies in compliance. The complexity of the micro gear's design, on the other hand, increases the simulation computation and runtime. An alternative method for simulation is to create a surrogate model to predict the behavior. This paper proposes a statistical surrogate model to predict the conformity of a pair of micro gears. Afterward, the advantage of the surrogate model enables the optimal tolerance assignment while taking gear functionality and production cost into account. [ABSTRACT FROM AUTHOR]

Manufacturing large and/or complex structural components is today non-trivial and far-too expensive, due to limitations in the state-of-the-art production processes. Swarm robotics could then bring a different perspective and it may promise flexible, autonomous, and highly robust solutions for a large variety of applications; hence, its adoption in industry and construction may change manufacturing rules. The present contribution introduces a continuous model to capture the behavior of a swarm of manufacturing agents (e.g., drones, 3D printers, etc..) as well as a very simple, but effective, numerical implementation to simulate the evolution of such a swarm. The paper also presents one- and two-dimensional examples, showing the potentiality of the proposed approach in predicting swarm behaviors. [ABSTRACT FROM AUTHOR]

The level of performance is an important aspect of the design and control in a production line. Particularly, the level of performance of variable production line (VPL) is one of the most important influential factors in deciding production line’s flexibility. The majority of the existing solution methods for performance prediction and evaluation problems of VPL assume that the processing times, time between failures and repair times are deterministic or exponentially distributed, which could not be applied to all the problems in real cases. This paper relaxes these restrictions by proposing an ARENA simulation model for performance prediction and evaluation based on the variability theory in Factory Physics. The variable properties of time interval between product arrivals and VPL are simulated, which combining with the coefficients of variations, are presented. Through the simulation, how the variable factors influence the performance of VPL is demonstrated. The methodology in this paper can be applied to effectively predict and evaluate the performance in VPL in various production scenarios before implementing them in reality. [ABSTRACT FROM AUTHOR]

The aim of the paper is to present a case study and to point out the possibilities of using computer simulation for the purpose of increasing the efficiency and efficiency of custom production of a company. The use of simulation modeling as a scientific method in research and in practice brings benefits such as financial, time, material and energy savings, as well as streamlining activities in real practice. The development of advanced simulation systems has opened up new possibilities and significantly supported the trend of streamlining production activities, thus reducing costs and improving business performance. Simulation, however, is not a tool for obtaining an optimal solution, but rather a tool that allows you to test different decision outputs on a simulation model. Such a simulation model makes it possible to carry out various experiments to evaluate, analyse and determine solution parameters that can then be used in a real system. Risk factors can be investigated and determined beforehand by 'replacing' the running simulation model while monitoring system performance and behaviour, then, after applying the required changes, the future behaviour of the system is examined for any potential problems and obstacles. Can be removed in advance. The goal is to analyse the material flow in the production process and then create a simulation to determine the length of production and identify bottlenecks in the production process. In order to get a better idea of the production process, a simulation model was developed in the selected software tool as a custom production project under the conditions of a particular company. The incentive to start production is given to the customer, where every order placed is immediately sent to the customer. The highest frequency order in the enterprise's production program is used to create the material flow. [ABSTRACT FROM AUTHOR]

This paper presents a research that investigates solutions and algorithms for determining the optimum machine layout served by autonomous material handling system, like mobile robot or automated guided vehicle. Unlike previous works which solved the layout problem by optimizing the distance between facilities, in this paper the machine layout is addressed based on optimizing the travel time of the material handling system. The proposed approach can include boundary kinematic constraints of vehicle while optimizing the objective function such as velocity, acceleration, orientation, and trajectory curvature. The nonlinear constrained model is transformed to unconstrained problem using penalty method. Then, a simulated annealing-based algorithm is used to search for the optimum locations of machines among all possible feasible layouts. The simulation results showed that the proposed approach was efficient enough to use in real factories due to including a vehicle path planner integrated in an overall layout design scheme that involves searching of vehicle control parameters. [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]

With the development of casting process and its numerical simulation technique, many demands of realism and clearness in post-processing have arisen. This paper introduces the implicit surface to post-processing for the results of casting simulation so as to meet these demands. In this paper, a robust and fully automatic algorithm is proposed for extracting the implicit surface in the signed distance function calculated from the import stereolithography files. Then several applications of implicit surface in the post-processing of casting simulation are listed in two categories. The applications in the first category include fast rendering of massive data, section view in arbitrary direction, visualization of residual liquid, and casting deformation, giving clear and pretty visualization of the results in simulation, and making it possible for engineers and process designers to look through the opaque mold, gain insights to casting process, and locate possible defects. The applications in the second category involve thickness distribution and modulus calculation, which offer important characteristics of castings and facilitate the optimization of casting processes. [ABSTRACT FROM AUTHOR]

An ever increasing trend in today's dynamic and competitive world markets, manufacturing organizations should provide the right amount of flexibility at the right time in the right direction. Among many manufacturing strategies available, reconfigurable manufacturing system is emerging as an attractive alternative to meet this goal. Organizations in pursuit of reconfigurations are often presented with a number of options and hence face a problem of evaluating the feasible alternative configurations before choosing the best one. The study reported in this paper is related to an organization interested in reconfiguring the present manufacturing setup. A number of alternative configurations were identified. Simulation models were developed for these configurations, and the results of the simulation experiments were analyzed to assess the suitability of each configuration in the point of view of five performance measures. The simulation experiments, method used to analyze the simulated results, and the outcome of the study are reported in this paper. [ABSTRACT FROM AUTHOR]

Pull policies may perform quite differently depending on the particular manufacturing system they must control. Hence, it is clear the necessity of having efficient performance evaluation models to select the best control policy in a specific context. This paper proposes a mathematical programming representation of the main pull control policies applied to single-product serial manufacturing systems. The proposed models simulate the pull controlled system in the sense that, if instantiated with the same parameter values as in a simulation model, their solution gives the same event sequence of the simulation. The proposed mathematical representation is also used for a formal comparison of the considered pull control policies. The new models presented in this paper can represent a base to build new efficient optimization algorithms for the design of pull controlled production systems. [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]

In spite of the development of automated tolerance inspection systems for manufactured parts over the years, there are still processes that inevitably require manual intervention making full automation impossible in most cases; in particular when dealing with deformable parts. In most current industrial inspection systems, a deformable part under inspection must first be mechanically constrained on a rigid support or jig so as to be able to compare it with its nominal shape. This paper presents a new system to perform real-time surface inspection of deformable parts that does not require fixturing. Instead, the proposed system applies virtual forces to the part's CAD model as if the part was installed in the fixturing device. Normally, a precise finite element method (FEM) simulation should be used to approximate the deformation that appends when the part is installed in the device. Even with a fast parallel computer, FEM is far from being real-time and cannot be used for on-line inspection. In the proposed system, a radial basis function approximation of the FEM simulation is trained off-line and used to speed-up the simulation by an order of magnitude. Experimental evaluation of the proposed system is presented for three plastic parts. Using the proposed scheme, an approximation of 0.25 mm compared with the real deformation was obtained. In this paper, statistical results are presented such as the average deviation, standard deviation, and processing time between the approximations obtained with the proposed method and with the finite element method applied to the full CAD model. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of classical cellular manufacturing systems compared to other two systems proposed in literature: fractal cells and remainder cells. This paper proposes three strategies to control a cellular manufacturing system with remainder cell and how to configure and control a fractal manufacturing system. The performance measures of the manufacturing systems are analyzed when several unforeseen events occur as: machine breakdowns, production mix changes, demand fluctuations, and processing time variability. A simulation environment developed by Arena® package was used to investigate the three manufacturing system configurations. The performance measures investigated are: throughput, throughput times of the parts, work in process, manufacturing utilization, and due date performance (tardiness). The simulation results show how the fractal and remainder cells can be a valid alternative to cellular manufacturing systems in a very dynamic environment. [ABSTRACT FROM AUTHOR]

Java Agent DEvelopment framework (JADE™) is a leading platform for the development of agent-based systems that are complaint with Foundation for Intelligent Physical Agents specifications. Due to the complexity, concurrency, and dynamic nature of manufacturing, it has been an important application of agent-based systems. Application of multi-agent concept in simulation leads to the agent-based simulation. Modeling the elements of manufacturing system (such as part, machine, and AGV) in reactive agent architecture is a better way of modeling for achieving discrete-event agent-based simulation. This paper focuses on modeling of different agents in manufacturing domain on JADE reactive architecture. Modeling of different agents on a shop floor in JADE reactive architecture led to the development of a simulator known as an agent-based shop floor simulator (ABSFSim). In the modeling process, different agents in the manufacturing domain have been identified by physical and functional decomposition. Internal architecture of individual agents is finalized based on their behavioral requirements. Modeling of the agents is an important development step of ABSFSim. A randomly generated sample manufacturing system has been used for testing and demonstration of ABSFSim. The modeling details provided in this paper are useful for development of agent-based systems in manufacturing domain as well as other discrete systems. [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]

As corner smoothing algorithm is crucial to high-speed CNC machining, a new error constraint optimization method for corner smoothing algorithm is proposed in this paper. Traditional corner smoothing algorithms are all based on a toolpath to generate motion trajectory, and the same allowable error is used for all smoothed corners. However, in using this method, the contour error of workpiece will be invalidated because of the cutting tool radius in real cutting processing, thereby resulting in over-cutting or inefficiency. In this study, the tool offset and corner smoothing algorithm are combined in order to optimize the error constraint. Besides, a cutting process geometry model was established to analyze the error relationship. On the basis of this model, the smoothing error constraints of each corner can be solved according to the allowable contour error of the workpiece. Finally, motion trajectory is planned through a multi-constraint planning strategy, which can balance the contour error in workpiece at each corner and can guarantee the cutting accuracy, compared with the traditional corner smoothing algorithm. Moreover, a test workpiece is designed to verify the correctness of the proposed algorithm through simulation and actual experiments. The experimental outcome proves that the proposed method improves the workpiece cutting accuracy in high-speed CNC machine tool. [ABSTRACT FROM AUTHOR]

In the computer numerical control (CNC) machining for free form surfaces, the time-optimized and smooth feedrate profile plays an essential role in the high-speed and high-precision machining. For the traditional feedrate scheduling method (e.g., the "bang-bang" control method), there may be many fluctuations in the planned feedrate profile, especially in region of large curvature, which results in poor quality of machining surface. To address this issue, a novel concept called sliding arc tube (SAT) is proposed in this paper, from which the trajectory is partitioned as feedrate restricted intervals (FRIs) determining the target feedrate and the positions of tool acceleration and deceleration on the tool path. The SAT is built based on the local geometric information of tool paths. As the SAT is constructed in the tube-shaping process and then sliding on the tool path and finally blocked by it, the breaking point for generating the FRI is found on the trajectory curve. For the proposed FRI identification method, it is computational efficient and it can be implemented in the real-time manner in the CNC controller. Results from both simulation and real machining experiments validate that, with the proposed SAT, the FRIs can be precisely and efficiently identified for the given trajectory curve, the frequent acceleration and deceleration of machine tool is alleviated, and the machining quality can be improved in this way. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to analyze the quality of ductile iron castings through simulations and experiments. Standard tensile test specimens are considered as simple cast products for which a multi-cavity mold is designed, simulated, and optimized to minimize porosity using MAGMASoft. X-ray imaging, hardness measurement, and tensile testing are done for selected specimens produced using optimized mold design. Next, finite element simulation of tensile testing until fracture is done in ABAQUS using elastic-plastic material model and porous metal plasticity model. Simulation results for sound specimen are found to be in good agreement with the experimental results. Since mold design optimization is solely based on porosity minimization, no porosity is observed in the final mold design. However, if multi-criteria optimization of mold is done, the specimens may show some porosity which can be integrated in the developed finite element model of tensile testing. It is concluded that simulation-based mold design optimization can produce nearly defect-free castings and at the same time exhibit the similar mechanical properties as their sound counterparts produced with other manufacturing processes. [ABSTRACT FROM AUTHOR]

With the rapid development of high-energy laser system, thick silicon mirror, as an important optical component to reflect laser, is required to have a surface with micron-level flatness, which poses significant challenges to silicon mirror manufacture process. Fine rotation grinding (FRG) is a typical efficient method for silicon mirror manufacture. A geometric model is developed in this paper to research silicon mirror surface figure control mechanism in FRG process. The model demonstrates the relationship between the grinding spindle obliquity and the mirror surface figure. From an application perspective, the relationship between the spindle obliquity and the spindle dial gauge indication is further presented. Based on this model, a MATLAB program is designed to give a series of simulation results for researching spindle adjustment regularity and getting the most ideal spindle obliquity. Besides, several grinding experiments are carried out. The simulation and experiment results are in good agreement, and a silicon mirror surface with the flatness of less than 2 μm is achieved. The proposed grinding geometric model can provide an actual guide for grinding spindle adjustment to control the surface figure of silicon mirror. [ABSTRACT FROM AUTHOR]

There are many emerging manufacturing processes whereby surface structures are processed by spatially laser patterning of an entire feature at a time, as opposed to rastering a small beam. It is important to ascertain and ideally control the induced thermal fields underneath the pattern. This paper develops a computational framework to rapidly evaluate the induced thermal fields due to application of a laser on the surface. The aggregate thermal fields are efficiently computed by superposing individual “beamlet” heat-kernel solutions, based on Green’s functions, to form complex surface patterns. The utility of the approach is that laser-process designers can efficiently compute the results of selecting various system parameters, such as spatially-variable laser intensity within a pattern. This allows one to rapidly compute system parameter studies needed in the manufacturing of new products. Included are:A computational framework to compute the time-transient thermal response from a spatio-temporally non-uniform laser beam in an arbitrary spatial pattern andAn analysis of how the results can be used to track the evolution of the thermal gradients and their correlation to thermal stresses. Three-dimensional examples are provided to illustrate the technique. The utility of the approach is that an analyst can efficiently ascertain a large number of laser-input scenarios without resorting to computationally-intensive numerical procedures, such the Finite Element Method. [ABSTRACT FROM AUTHOR]

Hot metal gas forming is a modern metal forming process which is generally utilized to manufacture automotive parts with complex shape and light-weight materials such as aluminum-magnesium alloys. One of the critical parameters in this approach is controlling the internal pressure of the tube during the hot forming process. The improvement of formability in tube hydroforming by utilizing pulsating pressure paths has been confirmed in the last few years. In this paper, the effect of the pulsating pressure on the hot tube gas bulging process has been investigated by experimental and numerical methods. In addition, an oscillating heating mechanism was used to provide a uniform temperature distribution along the tube. A novel, simple pneumatic system was designed and used to provide pressure paths. Moreover, the finite element simulation of hot tube gas bulging was carried out to investigate the effect of different parameters of pulsating pressure on tube formability and thickness distribution. The simulation and experimental results showed that the proposed pulsating pressure path improved formability and thickness distribution along the tube in the hot metal tube gas bulging process. It was also concluded that the axial feeding intensifies the effect of pulsating pressure on formability and it should be applied right after the start of the plastic deformation of the tube. [ABSTRACT FROM AUTHOR]

The classical conjugation and envelope method is very accurate and effective for forward and inverse calculations of grinding helical surfaces. However, this method involves complicated mathematics and requires that the profiles be continuous. It can also result in undercutting or interference to the desired surface profiles. In this paper, a new approach is proposed to simulate the grinding process of helical surfaces on cutting tools. The paper begins with the reconstruction of cutter helicoids from sampled points. Using the recovered helical parameters from the sample points, the cross-sectional profile of the cutter surface is derived using a polynomial curve. A numerical method for calculating the profile of the grinding wheel required for the cutter surface profile is then provided. Finally, an optimization method is presented for solving the problem of inverse calculation to determine the helical surface profile for a given grinding wheel profile and setting parameters. The feasibility of the approach is tested by simulation results, which shows that the proposed approach can eliminate undesired tool-work interferences and undercutting. [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]

Discrete event simulation (DES) has been widely applied to modelling and simulation of computer and engineering systems and is an active field of research that has now evolved from 2D to 3D discrete event simulation. This paper attempts to address several key issues in a successful implementation of DES models based on our own and the previous experiences of others. It describes the common basis, which forms the core for the application of modelling and simulation methodologies that are available to support manufacturing systems analysis, design and performance evaluation. Through a comprehensive literature survey, this paper summarises and compares the most widely used optimisation techniques for simulation of manufacturing systems; an overview of the recent and popular simulation languages and packages available for the modelling and simulation community and the classification of their utility for modelling and simulation of manufacturing systems is also given. Finally, this paper summarises and reports the latest development in the most exciting world wide web (www)-based simulation techniques that represent a future that may completely change the nature and future exploitation of modelling and simulation technology in industry. [ABSTRACT FROM AUTHOR]

FinFET technology is one of the most promising candidates in replacing planar MOSFET beyond the 22 nm technology node. However, the complexity of FinFET manufacturing process has caused challenges in reliable device testing. Gate oxide short (GOS) is one of the dominant defects that has significant impact on circuit reliability. In this paper, we present a GOS defect model for FinFETs by introducing the defect as a pinhole in the gate oxide of a triangular fin shape structure. The pinholes are represented by small cuboid cuts of various sizes on the fin top and sidewalls along the channel. The 3D Sentaurus TCAD simulation results in the development of an analytical GOS defect model that can be used in circuit-level fault modeling, which leads to generating more realistic test patterns. [ABSTRACT FROM AUTHOR]

From Germany's Industry 4.0 mission to Made in China 2025 and Make in India mission to British Factory of the Future in 2050, digital manufacturing (DM) is promoting in the world's major industrial countries as a technology foundation of the future manufacturing. At the same time, in the different segments of the DM realm, different forms of information technologies (IT) are flourishing such as the following: computer-aided manufacturing, robotics control in manufacturing, and process simulation. This paper is aimed to review the latest initiatives ofDMin the leading universities and major industrial countries. Along with, a critical literature review of various initiatives in the area of DM-assisted hybrid additive manufacturing (DM-HAM) has also been carried out. DM-HAM seems to be very promising for next generation multi-operational manufacturing as it is time saving and economical. The highlights of this review will provide a guide for the upcoming research activities in the area of DM-HAM. [ABSTRACT FROM AUTHOR]

Silicon content prediction is quite significant for supervising the state of blast furnace and is usually selected as the indicator to represent the thermal state. In practical industry, the fluctuation exists in the operation of blast furnace all the time. What's worse, it is inaccurate to build the predictive model with many outliers. To solve these problems, this paper has developed a model to predict the silicon content using support vector regression (SVR) combined with clustering algorithms, including hard C-means (HCM) clustering and fuzzy C-means (FCM) clustering. Through data processing, the data points are clustered based on the similarity, and then different SVR models are established. In order to make full use of FCM, a new method using multiple SVRs and FCM based on membership degree (MFCM-SVRs) is proposed where the membership degree is applied to eliminate the outliers. Simulation results verify that the multiple SVRs based on HCM (HCM-SVRs) and MFCM-SVRs possess superiority in terms of accuracy and speed, which makes the method serve better for practical production. [ABSTRACT FROM AUTHOR]

Remanufacturing is recognized as a major circular economy option to recover and upgrade functions from post-use products. However, the inefficiencies associated with operations, mainly due to the uncertainty and variability of material flows and product conditions, undermine the growth of remanufacturing. With the objective of supporting the design and management of more proficient and robust remanufacturing processes, this paper proposes a generic and reconfigurable simulation model of remanufacturing systems. The developed model relies upon a modular framework that enables the user to handle multiple process settings and production control policies, among which token-based policies. Customizable to the characteristics of the process under analysis, this model can support logistics performance evaluation of different production control policies, thus enabling the selection of the optimal policy in specific business contexts. The proposed model is applied to a real remanufacturing environment in order to validate and demonstrate its applicability and benefits in the industrial settings. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) maturity allows diffusion of this technology in conventional production environments. In the decision to adopt a new technology, production costs are one of the most important factors to analyse, even if they are not developed enough yet. In the last decade, several cost models for AM have been proposed, but each of them focuses on a specific aspect of the process, lacking the ability to consider the effective costs associated with AM, i.e. regarding AM as part of a more general production context. The aim of this study is to develop a cost model that evaluates process costs of AM for relevant technologies such as stereolithography, selective laser sintering and electron beam melting when integrated in a general production process. The integration of AM on the shop floor is proved by the introduction of an index such as the Overall Equipment Effectiveness (OEE) index, which allows this evaluation to be more connected to real production system issues. At the end of the paper, an experiment to compare the results of the proposed model with those of previous studies is reported and it is put in evidence how this model overcomes the previous problem of estimation. [ABSTRACT FROM AUTHOR]

Density's increase in Static Random Access Memory (SRAM) has become an important concern for testing, since new types of defects, that may occur during the manufacturing process, are introduced. On the one hand, new manufacturing defects may lead to dynamic faults, which are considered one of the most important causes of test escape in deep-submicron technologies. On the other hand, the SRAM's robustness is considered crucial, since it may affect the entire SoC. One of the most important phenomena to degrade SRAM reliability is Negative-Bias Temperature Instability (NBTI) causing the memory cells' aging. In this context, the paper proposes to analyse the impact of NBTI on SRAM cells with resistive defects that eventually escape manufacturing test and, with aging, may generate faults over time. Finally, SPICE simulations adopting a commercial 65 nm CMOS technology library have been performed in order to estimate NBTI's precise impact over time. [ABSTRACT FROM AUTHOR]

This paper examines the role that weight restrictions play in Data Envelopment Analysis (DEA). It is argued that the decision to include a factor (input or output) in a DEA model represents an implicit judgement that the factor has a non-trivial weight. it therefore seems perverse to allow DEA to assign a trivial weight to that factor in assessing the efficiency of a unit. There is therefore a strong case for imposing restrictions on factor weights. However. many existing methods of weight restriction are in practice unwieldy. This paper proposes an alternative approach we term contingent weight restriction which is both practical and intellectually consistent with (he DEA philosophy. The paper explores the impIications of alternative methods of weight restriction using simulated data from a well known production process. [ABSTRACT FROM AUTHOR]

Composites manufacturing processes usually involve multiscale models in both space and time, highly non-linear and anisotropic behaviors, strongly coupled multiphysics and complex geometries. In this framework, the use of simulation for real-time decision making directly in the manufacturing facility is still precluded nowadays, in spite of the impressive progresses reached in numerical analysis and computer science during the last decade. In this paper, a process-specific simulation tool based on reduced order modeling is introduced, the Simulation App. This concept is presented through a practical case involving a multi-physics and coupled problem describing the manufacturing process of a composite outlet guide vane. We show that several manufacturing settings can be simulated in few seconds with the Simulation App, thus enabling fast process optimization. Finally, the advantages over general-purpose simulation software, in the context of process simulation, are discussed. [ABSTRACT FROM AUTHOR]

In many manufacturing environments, the production horizon of the same part code between two consecutive set-ups should be limited to a few hours or shifts. When 100 % sampling is not possible, on-line quality control on a quality characteristic should be immediately started by means of a control chart. In this paper, we investigate the statistical performance of a nonparametric (distribution-free) Shewhart Sign (SN) control chart for monitoring the location of a quality characteristic in a production process with a finite horizon and a small number of scheduled inspections. The observations taken from the process are assumed to be continuous random variables. By implementing a SN control chart, any model assumption about the distribution of observations is needless to guarantee a nominal in-control (IC) performance: after each process set-up, this overcomes the important problem of lack of information about the distribution of the observations collected for the quality characteristic to be monitored. An extensive simulation study is conducted to compare the statistical performance of the distribution-free Shewhart SN control chart to the normal theory-based Shewhart Student's t control chart: several types of distributions of observations and different numbers of scheduled inspections are considered to show the advantages related to the implementation of the Shewhart SN control chart. An illustrative example presents the implementation of the Shewhart SN control chart on a real data set collected in a beverage company. [ABSTRACT FROM AUTHOR]

Rough machining is a major stage of production in face-gear precision manufacturing, and flexible, universal, and efficient rough machining is conducive to the reduction of manufacturing cost and time. Therefore, in this paper, the planing method for spur face-gear processing with a 4-axis CNC planer is proposed, together with a detailed study on the principle of meshing between the shaper and the face-gear, equations of the shaper tooth surface and the face-gear tooth surface, and the application of the planer tool to copy the shaper. Then, on this basis, equations of profiling curves as well as equations of the swing angle range and the radical feed range of the planer tool are derived. Finally, the method of planing the spur face-gear through multi-group envelopes is proposed with the NC processing code written according to the above principle, and the feasibility of the planing method for the spur face-gear and the correctness of the NC code are proved by the results of the simulation processing test based on the Vericut software. [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]

Individualized production, which is a major goal of many high-wage countries, describes a production process in which all elements of a production system are designed in such a way that they enable a high level of product variety at mass production costs. This paper demonstrates recent advances in the individualized production with die-based manufacturing processes, namely high-pressure die casting and plastics profile extrusion. Within these application areas, the chosen approach aiming at individualized production is based on the use of numerical die and process design. The design procedure relies on numerical process simulations based on a nonlinear optimization library and a spline-based geometry kernel. All components interact automatically without requiring user interaction; thus, a completely independent optimization cycle can be achieved. The numerical optimization helps to reduce-or even eliminate-the so far very characteristic manual reworking steps of an original die or process design. These reworking steps are a major cost factor when it comes to individual production. Their abolishment through the presented numerical approaches therefore represents a large step towards the concept of individualized production. [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]

In manufacturing systems, batch building processes are very common, as goods are often transported or processed in batches and must therefore be collected before these transport or processing steps can occur. In this paper, we present a method for the performance analysis of general batch building processes in material flow systems under the timeout and capacity rules. The proposed model allows for stochastic collecting times and incorporates no restrictions with respect to the number of arriving units and their interarrival times. The accuracy of the discrete-time approach is demonstrated by comparing this approach with a discrete-event simulation model in continuous-time. Subsequently, the model is applied to two cases: a transportation case from the health care industry and the process of building a batch for a batch processor. [ABSTRACT FROM AUTHOR]

This paper formulates the tasks that can be solved by the simulation systems of small and medium batch production. The author defines the requirements to the simulation systems of the given production class and describes the strategy and parameters of sampling tests on different stages of an industrial process and, besides, the sequence of experiments execution. [ABSTRACT FROM AUTHOR]

The five-axis milling is widely applied to complex surface machining. When cutting forces of milling processes increase, the consequent workpiece and tool deflections may result in poor machining quality and high processing cost. There are a lot of researches on three-axis milling processes simulation, but very few about five-axis milling. To solve these disadvantages, this paper presents an integrated system containing modeling, simulation, and optimization of five-axis milling processes. The system has three major applications: (1) simulation verification of milling processes, (2) cutting forces prediction, and (3) cutting parameters (feedrate) optimization. The material removal process simulation used for verifying the five-axis milling is based on the three-dexel (depth element) model, and the cutter-workpiece engagement regions are extracted from the geometric model. According to the extracted cutter-workpiece engagement regions, the instantaneous cutting forces could be predicted. The feedrate is off-line modified for balancing the given maximum or the reference cutting forces with the predicted cutting forces on different machining steps. The developed system is validated experimentally to show that the modeling, simulation, and optimization methods could improve the accuracy and efficiency of five-axis milling processes. [ABSTRACT FROM AUTHOR]

Machining operations such as turning, milling, and drilling are commonly employed machining processes in industry. With the push toward a future of sustainable manufacturing, machining processes need to be evaluated and optimized accordingly. This paper focuses on the energy aspects in metal cutting and attempts to provide an overall assessment of energy consumption and energy efficiency against the operating conditions. Specifically, the effects of tool geometry and cutting parameters in turning of ANSI 4140 steel are investigated through numerical experiments using finite element simulation. The variables considered include cutting speed, rake angle, nose radius, and edge radius. The effects of these parameters on cutting energy consumption and cutting efficiency are analyzed. The results show that the effects of these parameters on cutting energy and cutting efficiency are different. Strategies for minimizing cutting energy and maximizing cutting efficiency are suggested. [ABSTRACT FROM AUTHOR]

Many additive manufacturing technologies involve the deposition of particles onto a surface followed by selective, targeted, laser heating. This paper develops a modular computational framework which combines the various steps within this overall process. Specifically, the framework synthesizes the following: Numerical examples are provided and extensions are also addressed for two advanced processing scenarios involving solid-liquid-gas phase transformations. [ABSTRACT FROM AUTHOR]

Although high strengths up to 1,500 MPa can be obtained by means of hot stamping, the strength and uniformity of components cannot be guaranteed during mass production if the cooling channel is not properly designed. In this paper, we propose a method for designing the cooling channel by means of the energy balance principle and arrangement methods such as the triangular method, tool split, and the connection rule for 2D sections to improve the strength and uniformity of hot stamped components. Two separate approaches for designing the cooling channel are suggested. One is to reduce facility and maintenance costs, and the other is to reduce the cooling cycle time, which critically affects productivity. These approaches were applied to hot stamping tools for manufacturing a roof side that is used as part of the structure of an automobile. Cooling performance and cooling uniformity of the designed cooling channel were verified with finite element simulation. Finally, hot stamping tools for manufacturing a roof side were designed to reduce cooling cycle time and were then manufactured to verify the proposed design methods. A roof side was manufactured by means of the hot stamping tools with the designed cooling channel, and the strength and the uniformity of the component were evaluated by means of a tensile test, observation of the microstructure, and measurement of the micro-Vickers hardness. [ABSTRACT FROM AUTHOR]

This paper investigates how changes in chatter amplitude and frequency depend on process damping effect in dynamic turning process. For this purpose, the two degrees of freedom (TDOF) cutting system was modeled, and for an orthogonal turning system, the process damping model with a new simple approach was developed. To further explore the nature of the TDOF cutting model, a numerical simulation of the process was developed by this model. This simulation was able to overcome some of the weaknesses of the analytical model. The equations of motion for this cutting system were written as linear and nonlinear in the τ-decomposition form. The variation in the process damping ratios for different work materials was simply obtained by solving the nonlinear differential equations. A series of orthogonal chatter stability tests were performed for the identification of dynamic cutting force coefficients, using AISI-1040, Al-7075, and Al-6061 work materials, at a constant spindle speed. Finally, the experimental results were analyzed and compared with the simulation model, and it was observed that the results obtained through the experiments comply with the simulation model results. [ABSTRACT FROM AUTHOR]

In experiments, it is usually difficult to accurately determine simulation input parameters such as heat source parameters, material properties at high temperature, etc. The uncertainty of such input parameters is responsible for the large error of thermal simulation for weld-based additive manufacturing. In this paper, a new approach is presented to calibrate uncertain input parameters. The approach is based on the solution of the inverse heat conduction problem of small-scale five-layer deposition and the application of the infrared (IR) imaging technique. The calibration of heat source parameters involves a multivariate optimization search using the pattern search method, whereas the calibration of the combined radiation and convection model includes a number of one-dimensional searches using the Fibonacci search method. Based on an in-depth analysis of IR images, thermal characteristics such as mean layer temperature and cooling rate are selected as the comparison results and included in cost functions. Lastly, the validity of the approach is demonstrated by a simulation case of 15-layer deposition with calibrated input parameters. The comparison between the simulated and experimental results verifies the improved prediction accuracy. [ABSTRACT FROM AUTHOR]

For a manufacturing equipment, any unplanned breakdown during the production period results into a high production loss. To keep the manufacturing facilities in good condition, preventive maintenance is planned. However, because of limited time and availability of resources, not all the system components can be or need to be repaired/replaced during a planned opportunity. Hence, the unplanned breakdowns can also be considered as an opportunity to do the maintenance activities for other components to take the advantage of economic dependency in multi-component system. However, when the system is under maintenance, it is very conservative to take the decision of maintenance actions on the components because of limited available time and resources. For such situation, this paper consider an opportunistic maintenance model for a multi-component system to take maintenance decision with a constraint on available time and the system availability requirements. The maintenance decisions for each component involves one of the three actions namely, repair, replace or do nothing to achieve the target availability with minimum maintenance cost. The model also considers the effect of component failures on the quality of product being manufactured as well as the production schedule on the machine. The cost of rejections is considered in the total failure cost along with the maintenance and downtime costs. The production schedule delay factor is considered as a constraint for the maintenance decision to account for the effect on production schedule delay. The optimal solution for the model is obtained using three solution methodologies namely simulated annealing, genetic algorithm and sequence heuristics. Using a real-life example of high pressure die casting machine, the opportunistic maintenance approach is demonstrated and results are discussed. [ABSTRACT FROM AUTHOR]

In this paper, we analyze a model of capacity sharing for a set of independent firms, geographically distributed, that often have to implement an opportune tool to integrate their resources and demand forecasts in order to gather a specific production objective. We formulate the problem as a cooperative game and identify a capacity sharing solution using the Gale-Shapley model. The allocation rule takes into account the utility functions of the involved firms, and we show how the capacity allocation rule can be designed to induce all firms to report truthfully their information. Moreover, we show that, under this allocation rule, truth telling is a dominant strategy, with each firm reporting truthfully its private information, regardless of the reporting decisions of other firms. Moreover, the proposed research develops a distributed approach able to facilitate the capacity sharing process by using a multi-agent architecture; then a discrete simulation environment has been developed to compare the proposed approach with a centralized one. Several simulation scenarios were conducted to analyze the performances' trends in various environment conditions. [ABSTRACT FROM AUTHOR]

Nowadays, high-speed machining is usually used for production of hardened material parts with complex shapes such as dies and molds. In such parts, tool paths generated for bottom machining feature with the conventional parallel plane strategy induced many feed rate reductions, especially when boundaries of the feature have a lot of curvatures and are not parallel. Several machining experiments on hardened material lead to the conclusion that a tool path implying stable cutting conditions might guarantee a better part surface integrity. To ensure this stability, the shape machined must be decomposed when conventional strategies are not suitable. In this paper, an experimental approach based on high-speed performance simulation is conducted on a master bottom machining feature in order to highlight the influence of the curvatures towards a suitable decomposition of machining area. The decomposition is achieved through the construction of intermediate curves between the closed boundaries of the feature. These intermediate curves are used as guidance curve for the tool paths generation with an alternative machining strategy called 'guidance curve strategy'. For the construction of intermediate curves, key parameters reflecting the influence of their proximity with each closed boundary and the influence of the curvatures of this latter are introduced. Based on the results, a method for defining guidance curves in four steps is proposed. [ABSTRACT FROM AUTHOR]