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Research on collaborative manufacturing process modelling and simulation is of great significance in improving production efficiency and product quality, reducing costs, promoting collaborative work, and supporting decision-making. However, current studies have not offered the optimal costs of node enterprises participating in collaborative manufacturing, and ignored the impact of demand uncertainty of suppliers, manufacturers and customers on costs and economic benefits. Therefore, this paper aimed to study the collaborative manufacturing process modelling and simulation of production cost and economic benefit accounting analysis. First, this paper summarized three cost types, conducted cost accounting for the collaborative manufacturing process, and analysed its economic benefits. Second, based on the basic timed automata (TA) model, this paper used a timed input/output automata with port labels (Lp-TIOA) for modelling test cases of the simulation system. Finally, the experimental results verified the effectiveness of the constructed simulation model. [ABSTRACT FROM AUTHOR]

In recent years, paradigms like production quality or zero-defect manufacturing have emerged, highlighting the need to improve quality and reduce waste in manufacturing systems. Although quality can be analyzed from various points of view during different stages of a manufacturing system's lifecycle, this research focuses on a multidomain simulation model definition oriented toward the analysis of productivity and geometric quality during early design stages. To avoid inconsistencies, the authors explored the definition of descriptive models using system modeling language (SysML) profiles that capture domain-specific semantics defining object constraint language (OCL) rules, facilitating the assurance of model completeness and consistency regarding this specific knowledge. This paper presents a SysML profile for the simulation of geometric deviation propagation in multistage manufacturing systems (SysML4GDPSim), containing the concepts for the analysis of two data flows: (a) coupled discrete behavior simulation characteristic of manufacturing systems defined using discrete events simulation (DEVS) formalism; and (b) geometric deviation propagation through the system based on the geometrical modeling of artifacts using concepts from the topologically and technologically related surfaces (TTRS) theory. Consistency checking for this type of multidomain simulation model and the adoption of TTRS for the mathematical analysis of geometric deviations are the main contributions of this work, oriented towards facilitating the collaboration between design and analysis experts in the manufacturing domain. Finally, a case study shows the application of the proposed profile for the simulation model of an assembling line, including the model's transformation to Modelica and some experimental results of this type of analysis. [ABSTRACT FROM AUTHOR]

Improving the performance of manufacturing systems is the objective of management activities. The paper presents how this objective can be achieved by modeling and simulation. Base on the manufacturing process of the part support bush it is modeled the production line. Modeling is done using the TECNOMATIX PLANT SIMULATION program. Using the first model, by simulation, it was found that the resulting production after eight hours was relatively reduced: 28 pieces. Under these conditions, an additional welding post was introduced in the second model. It results in double the production and also in narrow places. The third model is designed in such a way that bottleneck is eliminated, and there is also an increase in production. [ABSTRACT FROM AUTHOR]

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

This paper demonstrates a new methodology for designing a virtual factory model and model execution on the basis of a real schedule plan. The main characteristic of the developed method is that the inputs are regarded as one of the main parameters of the production process, and the main objective is to create a low-cost production process model. The methodology is adjusted for use in SMEs (Small and Medium-Sized Enterprises) with individual or unique type of production. For such companies, the method represents an ability to optimize existing production processes through detecting and eliminating possible errors and disturbances before the real production process is executed at an acceptable cost. The applicability and suitability of the developed method for virtual production performance has been proven with the verification process, where the input data for the simulation was obtained from a real company. The simulation results have shown that the presented methodology is a useful tool for the optimization of the production process. [ABSTRACT FROM AUTHOR]

The paper is a partial synthesis of the work that a team within the Faculty of Managerial and Technological Engineering has in the field of modeling and simulation of systems with Petri nets. The paper deals with three issues. The first part is Modeling and simulation of manufacturing systems with timed Petri nets. The first part presents the way in which the performances of some manufacturing systems are evaluated using timed Petri nets. The first example is a manufacturing system specific to the textile industry. The system has three production lines. In this case, the modeling with timed Petri nets allows the analysis of the operation of the flow lines and highlights the bottleneck. Another modeled manufacturing system is specific to a series production, more precisely it refers to the manufacture of gas cookers within a company from Oradea. The model with Petri nets also describes the supply sequences of the stocks of parts and subassemblies. The next modeled system is an automated manufacturing system for the packaging of detergents. The complexity of the Detergent Packing System and the high level of automation, require the use of efficient modeling and simulation methods to verify the validity of the solutions adopted. In this chapter is present the model of a robotic welding cell. The second part of the paper, the transition from timed Petri nets to hierarchical colored Petri nets, shows how Petri nets were developed for a robotic cell for metallographic analysis. The third part is dedicated to modeling with colored Petri nets timed with complex colors of the flexible manufacturing cell A007 within the Department of Industrial Engineering. [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]

The aim of this paper is to optimize the production process of graphics card assembly in an unnamed company. For the optimization of the production process, we will use the Tecnomatix Plant Simulation software from Siemens. The first and most important step to optimize the manufacturing process is to analyse the current process so that we can pinpoint where bottlenecks or downtime is occurring. For this reason, the first simulation is dedicated to the current production process. In the second simulation, we have successfully implemented all the proposed changes within the upgraded manufacturing process. These changes included replacing the human workforce with two robots in the tenth stage, which involves the assembly of large components. The implementation of the upgraded process allows 44 graphics cards to be assembled in one hour, an increase of 15 graphics cards compared to the current process. In an eight-hour shift, 353 graphics cards can be assembled, which is 118 graphics cards more than the current production process. [ABSTRACT FROM AUTHOR]

Resin transfer molding (RTM) process is a major molding process in the manufacture of resin-based composites, and the simulation of this process can play a key role in the process of optimization for the design of RTM parts. This paper independently developed a three-dimensional non-isothermal RTM simulation model based on the control volume/ finite element method (CV/FEM) on the basis of two-dimensional isothermal RTM program. Based on the Darcy equation, the continuity equation, the energy conservation equation, the curing reaction equation and multiple rheological curing models, the simulation model adopts semi-discrete method and three convergence criteria to effectively solve the problems of mold preheating and resin non-isothermal in the non-isothermal RTM simulation process. For the simulation problems such as viscosity changing and curing heat release during the filling process, the simulation function has reached the level of similar international products. After the application verifications of the flat plate test piece and casing simulation, this simulation model can simulate filling time, velocity and pressure of RTM process that is the same as the products in the world. This simulation model basically has the ability of simulation for the actual complex structure parts. [ABSTRACT FROM AUTHOR]

The potential security problems of blockchain technology are constantly restricting the development process of related industrial applications. The cost of deploying a blockchain system in a real environment to conduct research on security issues is relatively high, and the related security analysis and verification are also destructive and irreproducible. Therefore, based on the idea of layered design, this paper proposes a blockchain system simulation platform. The blockchain system is divided into four layers in the simulation platform: the consensus layer, network layer, contract layer, and storage layer. In the consensus layer, the problem of computing resource waste is solved. In the network layer, a peer-to-peer network topology simulation is implemented. In the storage layer, the problem of redundant storage is solved. In the contract layer, the contract replay speed is accelerated. Finally, a prototype of an efficient blockchain simulation system is implemented based on the above methods. [ABSTRACT FROM AUTHOR]

Manufacturing is an important part of the modern economy. It is characterized by complexity in terms of systems, approaches, and interactions with intrinsic and extrinsic factors. Numerous efforts have been developed to use modeling and simulation tools to improve manufacturing efficiency and productivity and to achieve maximum quality, especially with the different mutations in the factories of today. This paper reviews the conventional and modern tools used in manufacturing system design and production improvement. Challenges that need to be addressed by the simulation community are discussed in depth. Finally, the evolution, advances, current practices, and future opportunities are discussed in the context of the contemporary manufacturing industry. [ABSTRACT FROM AUTHOR]

Simulation software Tecnomatix Plant Simulation was originally created for a modelling and subsequent simulation of production and logistics processes. Its variability, however, opens its use also in other areas such as transport in urban agglomerations. Based on that, research was implemented to verify the program's application in urban transport, specifically to visualize and simulate traffic processes at the traffic node. The paper describes a methodology which made it possible to create a simulation program for traffic light intersections, and presents examples of the simulation model application. The proposed methodology will enable the application of Tecnomatix Plant Simulation to create a complex simulation model of the logistics process. It will mainly enable to simulate the field of production logistics and city logistics within one simulation model. [ABSTRACT FROM AUTHOR]

Rigorous development of theory in operations management has been lacking. Although many theories have been proposed, they are often not developed in a format and depth that can be falsified, refined, or supported. This special issue includes three papers that illustrate rigorous development of theory for future testing using mathematical, simulation, or managerial approaches. [ABSTRACT FROM AUTHOR]

A new finite element dynamic model of a moving yarn segment has been proposed in this paper based on the absolute nodal coordinate formulation (ANCF). Apart from taking into account the elastic properties of the yarn in three dimensions, the model also considers the viscosity in the longitudinal direction and takes into account the effect of gravity and air resistance. In this paper, the simulation described the movement of the yarn segment that is pulled by the fixer on the guideway. Then, a corresponding experiment was proposed to evaluate the theoretical model. The theoretical and experimental comparisons of the motion tracing exhibited good agreement, demonstrating that the new model could predict the actual moving trace of the yarn segment. Moreover, another simulation of the spatial motion of the yarn segment was presented, to elucidate the role of the model in predicting the movement of the yarn segment. After considering the parameters of the actual process and its constraints, the authors established that the proposed model could be used to predict the trajectory of a yarn segment in the actual production process, which is vital when fabricating textile products. [ABSTRACT FROM AUTHOR]

2-D directed self-assembly (DSA) is an emerging lithography for the 5-nm process node and beyond that can substantially increase design flexibility in critical routing layers and reduce the number of cuts for better yield. The state-of-the-art 2-D DSA process manipulates the orientation of double posts inside guiding templates to guide block copolymers (BCPs) to form 2-D patterns. However, a key challenge arises on how to correctly assign double post orientations and place cut patterns to make desired net connections for a given routing instance. In this paper, we propose a novel 2-D DSA-compliant routing (2-D-DCR) framework to systematically derive feasible orientation assignments for double posts to maximize routability. Specifically, 2-D-DCR features a complete set of new routing rules which transform the underlying physical BCP growth principles for large-scale routing, adopts a network-flow-based double-post assignment routing algorithm, and leverages a 2-D DSA line-end creation property to maximally reduce line-end cuts. Experimental results show that our 2-D-DCR can effectively generate a 2-D-DCR solution with zero double post conflicts, maximized routability, and minimized the number of cuts. [ABSTRACT FROM AUTHOR]

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Discrete Event Simulation (DES) is one of the most important simulation techniques in decision-making in several areas. Some authors state that small and large companies can benefit significantly through the utilisation of DES. Literature shows that most DES studies carried out are at large companies. Studies carried out at small and medium-sized enterprises (SMEs) have been mostly explored on a one-off, caseby-case basis, given the characteristics and limitations of smaller companies. In order to expand DES studies in a wide range of companies, this article seeks to consider the SME characteristics and limitations prevent them from broadly adopting traditional (“hard”) DES. Then an alternative application of DES in “soft” mode was proposed. A review of facilitated DES frameworks was carried out. The frameworks were critically analysed in this review in relation to their adequacy to specific SME requirements and similar contexts. Finally, some issues and characteristics of these frameworks are presented that make directly applying in these contexts difficult. Furthermore, some suggestions are proposed for developing future facilitated DES frameworks. (Received in February 2022, accepted in May 2022. This paper was with the authors 3 weeks for 1 revision.) [ABSTRACT FROM AUTHOR]

Several continuous manufacturing processes use stochastic texture images for quality control and monitoring. Large amounts of pictorial data are acquired, providing important information about both the materials produced and the manufacturing processes involved. However, it is often difficult to measure objectively the similarity among industrial stochastic images or to discriminate between texture images of stochastic materials with distinct properties. Nowadays, the degree of discrimination required by industrial processes often goes beyond the limits of human visual perception. This paper proposes to model this specific class of textures as colored noise and presents a new approach for multiresolution stochastic texture representation and discrimination in industry (e.g., nonwoven textiles and paper). The wavelet transform is used to represent stochastic texture images in multiple resolutions and to describe them using local orientation and density variability as features. Based on this representation, a multiresolution distance measure for stochastic textures is proposed, and industrial applications of the method and experimental results are reported. The conclusions include ideas for future work. [ABSTRACT FROM AUTHOR]

The rapid development of additive manufacturing technology (AM) is revolutionizing the traditional continuous fiber-reinforced polymer (CFRP) manufacturing process. The combination of FDM technology and CFRP technology gave birth to continuous fiber reinforced thermoplastic composites (CFRTPC) 3D printing technology. Parts with complex structure and excellent performance can be fabricated by this technology. However, the current research on CFRTPC printing mainly focuses on printing equipment, materials, and the improvement of mechanical properties. In this paper, the CFRTPC 3D printing track errors are investigated during the printing process, and it is found that the polytetrafluoroetylene (PTFE) tube in the nozzle of the printer head is often blocked. Through detailed analysis, a line-following mathematical model reflecting the deviations of the CFRTPC printing track is established. According to the characteristics of the fiber and its track during actual laying, a modified line-following model, without the minimum curvature point, is further proposed. Based on this model, the actual printing track for the theoretical path is simulated, the process tests are carried out on the printing track at different corner angles, and the relevant rules between the parameters of the model and different corner angles are obtained. The mathematical model is verified by experiments, and the clogging problem of the printer head caused by the fiber track error is solved, which provides theoretical support for the rational design of the fiber track in CFRTPC printing. [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]

Healthcare facilities require flexible layouts that can adapt quickly in the face of various disruptions. COVID-19 confirmed this need for both healthcare and manufacturing systems. Starting with the transfer of decision support systems from manufacturing, this paper generalizes layout re-design activities for complex systems by presenting a simulation framework. Through a real case study concerning the proliferation of nosocomial cross-infection in an intensive care unit (ICU), the model developed in systems dynamics, based on a zero order immediate logic, allows reproducing the evolution of the different agencies (e.g., physicians, nurses, ancillary workers, patients), as well as of the cyber-technical side of the ICU, in its general but also local aspects. The entire global workflow is theoretically founded on lean principles, with the goal of balancing the need for minimal patient throughput time and maximum efficiency by optimizing the resources used during the process. The proposed framework might be transferred to other wards with minimal adjustments; hence, it has the potential to represent the initial step for a modular depiction of an entire healthcare facility. [ABSTRACT FROM AUTHOR]

Production systems present a different complex consisting of interconnected sub-units. For their proper functioning, it is necessary to use approaches in the design process that will fully accept the interaction of individual units. A dynamic simulation is now a powerful tool for the need of designing production systems. However, in its application in practice, we often encounter various. This paper presents a framework for using dynamic simulation in production systems design. It describes suggested steps to take when we start the process of production systems design, mainly the process of data collection and simulation model building (current and future virtual systems). The article details framework usage and describes the most important challenges of each step. The proposed framework is then successfully applied to a real-life project of innovation of a production system in a pressing shop, where every step of the framework is documented with a working example and with described difficulties or outcomes that each step gave to the team. The result of the dynamic simulation application at the presented real example by the software Witness, the saving was 40.000 EUR. [ABSTRACT FROM AUTHOR]

In this paper a novel approach for monitoring tool-related faults in milling processes by utilizing process simulation-based machine learning algorithms, specifically Random Forest algorithms, for fault detection is presented. In order to train machine learning models in tool condition monitoring, laboratory tests have traditionally been required. This method eliminates the need for costly, time-consuming laboratory tests. The training process has been simplified by utilizing analytical simulation data and provides a more cost-effective solution by leveraging analytical simulation data. Based on the results of this study, the proposed approach has been demonstrated to be 94% accurate at predicting tool-related faults, demonstrating its potential to serve as an efficient and viable alternative to conventional methods. These findings have been supported by actual measurement data, with a notable accuracy rate of 93% in the predictions. Furthermore, the results indicate that process simulation-based machine learning algorithms will have a significant impact on the tools condition monitoring and the efficiency of manufacturing processes more generally. To further enhance the capabilities of the proposed fault monitoring system, process-related and machine-related faults will be investigated in future research. Several machine learning algorithms will be explored as well as additional data sources will be integrated in order to enhance the accuracy and reliability of fault detection. [ABSTRACT FROM AUTHOR]

The concept of industry 4.0 includes implementation of preventive and predictive mainte-nance of manufacturing systems. In the paper the matrix structure of manufacturing system is proposed that enables the implementation of production processes even in the event of manu-facturing resource failure. The simulation model of the system is prepared using Tecnomatix Plant Simulation software. The simulation experiments are conducted for different buffers capacities and availability of manufacturing resources. The simulation method enables to ana-lyze the impact of the failure of manufacturing resources on the throughput and average lifespan of products. The matrix structure enables to predict of the manufacturing system per-formance reduction due to partial or total failure of manufacturing resources and evaluate the changes of the work in process level. [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 develops a Monte Carlo Simulation (MCS) approach to estimate the performance of a multistate manufacturing network (MMN) with joint buffers. In the MMN, products are allowed to be produced by two production lines with the same function to satisfy demand. A performance index, system reliability, is applied to estimate the probability that all workstations provide sufficient capacity to satisfy a specified demand and buffers possess adequate storage. The joint buffers with finite storage are considered in the MMN. That is, extra work-in-process output from different production lines can be stored in the same buffer. An MCS algorithm is proposed to generate the capacity state and to check the storage usage of buffers to evaluate whether the demand can be satisfied or not. System reliability of the MMN is estimated through this MCS algorithm. Besides, performability for demand pairs assigned to production lines can be obtained. A practical example of touch panel manufacturing system is used to demonstrate the applicability of the MCS approach. Experimental result shows that system reliability is overestimated when buffer storage is assumed to be infinite. Moreover, joint buffer for an MMN is more reliable than buffers are installed separately in different production lines. [ABSTRACT FROM AUTHOR]

Lean manufacturing appears to hold considerable promise for addressing a range of simultaneous, competitive demands including high levels of process and product quality, low cost and reductions in lead times. This research addresses the application of lean manufacturing concepts to the continuous production sector with a focus on the motor manufacturing industry. The goal of this research is to investigate how lean manufacturing tools can be adapted from the discrete to the continuous manufacturing environment. This paper presents lean manufacturing as a leading manufacturing paradigm applied in many sectors. The fundamental focus on lean production is the systematic elimination of non-value added activity and waste from the production process. The implementation of lean principles and methods results in improved system and surrounding performance. Value stream mapping is used to first map the current state used to identify sources of waste and to identify lean tools to eliminate this waste. The future state map is then developed for a system with lean tools applied to it. To quantify the benefits gained from using lean tools and techniques in the value stream mapping, a detailed simulation model is developed and a designed experiment is used to analyze the outputs of the simulation model for different lean configurations. This paper demonstrates the implementation of lean philosophy through layout modification. [ABSTRACT FROM AUTHOR]

A floorprint-based yield modeling, assurance and optimization method for the defect tolerant NASIC system under broken nanowire (NW) defects has been proposed in a short version of this paper, and the proposed models and methods are further validated and demonstrated through extensive parametric simulations in this paper. A yield model for each defect tolerant NASIC technique is developed based on the nature of the defects of concern in a floorprint-based analysis, thereby establishing an adequate foundation to evaluate and optimize the manufacturing process and defect tolerance by providing a capability to take into account the effect of each individual defect tolerance technique or synergetic effect of various combinations of the techniques on the overall expected yield of the product. According to the simulation results given in this paper, the defect tolerant NASIC system with 15 row and column NWs, respectively, each with length = 0.000034 on horizontal and vertical core nanoarray in a nanotile can achieve a yield higher than 99.8%. Ultimately, intelligent exploitation of the proposed yield modeling and simulation methods will make possible to realize a reliable NASIC-based computing system. [ABSTRACT FROM AUTHOR]

This paper proposes a general simulation model to assess the throughput of non-homogeneous transfer lines. The transfer line has no intermediate buffers between adjacent machines. Machines are subject to random operation dependant failures. The transfer line is dedicated to producing only one product type which can be assimilated to an aggregation of various product types. Due to lack in line balancing, the considered transfer line is non-homogeneous so that its machines have different processing times. The purpose of this paper is to evaluate the performance of approximate analytical approaches dealing with non-homogeneous transfer lines. Several production line configurations have been analyzed and statistical tests were carried out to show that approximate approaches generate significant errors and cannot give a good estimate, compared to simulation results, of the throughput of unbuffered, non-homogeneous transfer lines subject to operation dependant failures. [ABSTRACT FROM AUTHOR]

Due to the increased emphasis on technology, modern manufacturing processes are no longer labor intensive. Therefore, the traditional cost estimation approaches based on volumetric measures are inadequate to asses the costs accurately. Contemporary approaches such as activity based costing have been suggested that track hidden costs by relating them to the specific activities, thus providing a much more realistic estimation for manufacturing costs. Since activity based costing does not assign cost of under-utilized resources to customers, the issue of resource under-utilization remains unaddressed. The present paper recognizes resource under-utilization cost to be an important consideration in order to identify the potential bottlenecks in the manufacturing process. This paper proposes an activity based costing model to identify resource under-utilization assuming normally distributed demand. In light of futuristic uncertainty about order sizes and in order to validate the proposed model, a discrete-event simulation approach has been presented. [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 transfer systems conveyor type are an important component of the modern manufacturing systems. Designing and constructing a conveyor involves evaluating its performance for the adoption of the most effective constructive solutions. The paper shows how modelling and simulation can be used in assessing the performance of a conveyor. The studied parameters refer to the kinematic characteristics (the speed of the conveyor) and to the functional indicators of the system components (input rate, service rate). [ABSTRACT FROM AUTHOR]

The manufacturing operations often involve multistage processes where the process capability of each stage is affected by the process capability of its precedent processes. This property is known as the cascade property. The purpose of this paper is to estimate the process capability of the second stage of two-stage process while the cascade property impact is removed using residuals analysis. To this end, a method is proposed to determine the specification limits of the residuals based on the specification limits of the quality characteristics in the first and second stages. The C , C and S indices are used to calculate the capability of the second stage in the two-stage process. The results of simulation study show the satisfactory performance of the proposed method in estimating the pure process capability of the second stage. [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]

Process variations increasingly challenge the manufacturability of advanced devices and the yield of integrated circuits. Technology computer-aided design (TCAD) has the potential to make key contributions to minimize this problem, by assessing the impact of certain variations on the device, circuit, and system. In this way, TCAD can provide the information necessary to decide on investments in the processing level or the adoption of a more variation tolerant process flow, device architecture, or design on circuit or chip level. In this first of two consecutive papers, sources of process variations and the state of the art of related simulation tools are reviewed. An approach for hierarchical simulation of process variations including their correlations is presented. The second paper, also published in this issue, presents examples of simulation results obtained with this methodology. [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]

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]

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]

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]

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]

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]

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]

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]

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]

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]