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

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]

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]

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]

An optimization of the production process is defined as the search for solutions with improved production efficiency. Process optimization should be one of the main components of a business strategy that not only delivers benefits to customers but also helps increase the performance of production processes and benefits the entire business. The traditional approaches to job shop scheduling are based on the exact mathematically formalized model. If the number of model parameters is high and the environment is rather uncertain, the practical applications are quite restricted. That is why the theory proposes an approach based on a large-scale computer simulation. The main goal of this paper is to show that in a concrete company case, the simulation-based approach provides increased productivity. The presented study proposes the practical application of the Tecnomatix software used in the research to optimize the production system. The partial aims of the paper are as follows: (1) to create a simulation model of the production system with the help of the Plant Simulation module, (2) to model the current state of matters in the company, and (3) to propose a solution to the problem. Ultimately, we show that the simulation approach to the production line control provides rather effective solutions when compared to the intuitive one based on trial-and-error experience. The improvement includes a significant (1) shortening of the production cycle and (2) increase in productivity. [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]

Simulation models have become promising methods to investigate and improve real-world systems. This paper describes the development of effective simulation-based models for maintenance systems in a manufacturing environment whereby production lines send their faulty but repairable items to a repair shop. The proposed models aim at investigating the centralized storage of repaired items with three replenishing strategies, lot-for-lot (L4L), economic order quantity and reorder point (Q-R), and minimum-maximum order level (s-S) reordering policies of repairable items with backordering allowance in a risk-free and flexible manner to effectively manage the procurement of new repairable items and control three inventories of repairable items, repaired ready-for-use, new, and faulty awaiting repair. The models take into account the uncertain environment of maintenance systems and the probabilistic nature of the failures, repair times, and lead times of repairable items. The demand for repairable items in these three inventories is both stochastic and dynamic. A simulation case problem is presented to demonstrate the suitability and applicability of the proposed simulation models and to study the influence of different parameters on performance measures using parametric analysis. The main results are the vital decision-making insights provided by the developed models about the three reordering policies and the three inventories of repairable items. These managerial insights are essential for achieving minimum inventory costs and maximum service levels. [ABSTRACT FROM AUTHOR]

The paper deals with the problem of production material flow management. The proper way of logistic tasks management has an impact on the production process effectiveness and the cycle time, which is a very important factor in manufacturing. Reducing the production process cycle time results not only in the ability to provide more customers with orders but also in increasing the level of resources usage (machines, operators etc.). In order to reach the aim of improving production effectiveness, the simulation modeling was used. It is a computer method that supports a decision-making process and allows to perform experiments on production without interfering with the real process. The paper also includes a risk analysis performed to evaluate the imperfections of simulation modeling, based on the rules of fuzzy logic. [ABSTRACT FROM AUTHOR]

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]

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]

The delay is a very important element in modeling hardware behavior, and is realized in many hardware description languages such as ADLIB-SABLE, Verilog, and VHDL. The state of the art on hardware delay identifies four classes. In the first class, mean values are used as a precise delay element in the simulation; we found it in VHDL (VHSIC (very high speed integrated circuit) Hardware Description Language), where a single value is utilized to characterize the transport delay. In the second class, the delay is represented by an interval min max, meaning that the delay value is precisely unknown and every value in the interval can represent a possible value for the actual delay. In the third class, a delay is expressed in the form of a stochastic distribution. Fuzzy models of delay constitute the last class. In reality, it is very difficult, if not impossible, to obtain a precise value of the delay; there are many reasons for that: temperature, voltage, variation in the manufacturing process, and other environment parameters. The Min Max DEVS formalism allows an efficient design of the min max delay by proposing a definition of the lifetime function based on time interval. Moreover, its simulation semantics allows the simulation of Min Max DEVS models with only one replication, allowing us to conclude whether the min max delay is too large or exact simulations cannot be obtained. In this paper, we propose to highlight the Min Max DEVS formalism through examples from digital circuits, after having recalled its basic definitions and its simulation semantics. Then, we compare the simulation results obtained with those provided by the well-known tool in the field of digital circuits, Verilog, using the same examples. [ABSTRACT FROM AUTHOR]

Increasing competition and globalization that encompasses all dealings in the world of business compel SMEs to seek more successful organizational and management modes and approaches. This paper presents a simulation model for the application of Lean methods and tools in SMEs and their impact on the improvement of production processes and product sustainability. The Lean concept can be used to achieve more efficient production whilst manufacturing lower-cost products including shorter manufacturing cycle, high quality, and added value. Research results show the usefulness of the application of dynamic simulations in the detection of critical places in processes and the usefulness of the application of relevant Lean methods and Lean tools for process improvement. Simulation results underline better performance of product manufacturing through the use of Lean tools with the aim to eliminate any waste. Reengineering the assembly line focuses on the following aspects, namely reducing waste, internal logistics, redesigning workplaces, and changing the workplace layout. [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]

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]

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]

Make-To-Stock (MTS) and Make-To-Order (MTO) are the two traditional strategies in production management. In the case of the MTS there is a growing demand for a new approach, which is called Make-To-Availability (MTA) strategy. The paper characterizes and compares the MTS and MTA strategies. The comparative analysis based, among others, on computational experiments carried out in a computer program developed in Microsoft Visual Studio 2017 Environment was presented. The models have been prepared for both strategies with the same assumptions: external conditions (market demand) and internal conditions (structure of the production process). The investigation of how the strategies respond to various scenarios of demand intensity was done. The simulation models were prepared and validated for the case of the production line in one of the industrial automation company. The research shows that the use of the MTA strategy in the majority of cases gives much better results than the use of the MTS strategy due to the minimization of storage costs and the costs of non-fulfillment of the customers' demand. The directions for further research were also presented. [ABSTRACT FROM AUTHOR]

The paper describes the use of the Plant Simulation software to create a simulation model of the manufacturing process in the VTC200C machining centre. A genetic algorithm was used to optimize the production process. It is an algorithm that learns itself and looks for the best solution based on input data. The optimization is done based on the assessment of the output data from the simulation model. Based on the results of the optimization, a more efficient production plan was designed in the selected company. [ABSTRACT FROM AUTHOR]

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]

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]

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

This paper presents the first proof of concept validation of the STAR thruster prototype. The device contains an innovative multifunctional monolithic heat exchanger, enabled by metal additive manufacturing processes. A 316L stainless steel printed thruster is characterized through a combination of dry heating and wet firing tests. This includes verification testing with argon in both cold and hot firing mode, at a range of electrical power inputs. Thrust measurements range from 9.7 mN ± 0.16 mN–29.8 mN ± 0.16 mN, with a maximum measured specific impulse of 80.11 ± 1.49 s. Thrust performance is measured using a high-precision balance, and liquid-metal power transfer terminals to eliminate thermal drift. Highly coupled multiphysics computational models provide validation of the electro-thermal and thermo-fluidic characteristics of the prototype, including a prediction of the maximum propellant stagnation temperature and structural temperature, which were 649 °C and 854 °C. • Proof of concept validation of the Super-high Temperature Additive Resistojet. • SLM enabled a thin-wall concentric monolithic heat exchanger and resistive heater in 316L. • The prototype produced a specific impulse of 80.11 ± 1.49 s with Ar propellant. • Simulations suggest that the maximum structural temperature was of 854 °C. [ABSTRACT FROM AUTHOR]

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

This paper aims to provide an introduction to the analytical modelling and the discrete-events simulation for a manufacturing system. A general method of constructing a Markov chain and the simulation with discrete events using Delmia Quest software, are presented. In the present paper, those interested can find a real case study: modelling and simulation of the headrest support manufacturing line. The scientific contribution of this paper consists in the development of a theoretical model implemented in a real case study. The theoretical model estimates the production rate of the line and then, using this model we can establish how many parts in the buffers are required in order to achieve a production rate of X parts per minute. In the first phase, the manufacturing line is analysed, then the Markov chains for subsystems with two machines and a buffer are constructed. As the Markov chains need more time to provide solutions in queues theory, they can be used only for small production lines. To find the production rate for all the system, it is necessary to apply the Markov chains and the decomposition method. Those methods are implemented in the C/C++ programming. To validate the analytical model, the discrete-event simulation with Delmia Quest software is used. The article presents some comparisons between modelling with Markov chains and simulation with Delmia Quest software and provides a method of optimization of the buffers for the case study. [ABSTRACT FROM AUTHOR]

This paper presents the application of the Discrete Event Simulation (DES) in an industrial plant to analyze the behavior of the consumption and generation of electrical energy in conjunction with other variables of the process. In other words, the process modeling was conducted considering the energy consumption in equipment as well as the local photovoltaic (PV) energy generation. A medium-sized plant was the reference base used herein, and the main variables considered were the time of supply of tanks and processing of raw material, active power of equipment and energy tariffs. A simulation model with resolution in seconds was designed, enabling the simulation of consumption curves of each equipment of a given part of the production process. The equipment of variable active demand was modeled by a mathematical regression method, and the others were assumed with constant power. The same model was altered to unit in minutes for simulating the monthly electricity consumption, so as to obtain financial results. The contractual rules for electricity supply were included, and the use of a diesel-powered generator was taken into account. The application of a freeware was employed as a low cost alternative for small and medium-sized companies, even though the lack of graphic resources has increased the complexity of the system modeling process. The model with resolution in seconds proved to be efficient to simulate the consumption profile of a specific equipment that alters the power in a short-time period, such as the pumps. The model, on the other hand, in minutes allowed a more effective analysis in terms of finance, enabling the verification of alternative scenarios throughout a month. The monthly cost reduction perceived by considering self-generation in this model was about 36%. Detailed diagram of the main elements of modeling of a manufacturing process of an industry concentrating on the consumption and generation of electric energy. Image 1 • The electricity consumption in an industrial process can be approached in a simulation model. • PV energy can be simulated together with variables of industrial processes. • The discrete event simulation can be used in industrial processes to optimize the electricity management. [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]

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]

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]

Abstract Models of distributed manufacturing systems cannot be consistent without a formal ontology. In this paper, the ontology formulation and maintenance are addressed in the scope of a collaborative modelling environment – in which concurrency, consistency, and model life cycle management should be supported. Thus, an extensible foundational ontology for manufacturing – system modelling is proposed in which the formal definitions of the modelling environment itself enable the definition of the manufacturing system's elements. The presented approach ensures the consistency of ever-changing models. The ontology is integrated into a modelling framework through the concept of description layers that assist in the management of the model description's complexity. The feasibility of the approaches is illustrated in an industrial case study that models of a manufacturing system for material processing. [ABSTRACT FROM AUTHOR]

Due to the compliance and geometrical defects of composite parts, gaps exist between assembly components after the preassembly. Assembly requirements impose to fill these gaps to eliminate any unexpected internal stresses. Although it is identified as a problematic and expensive nonadded value stage, a gap measurement is still needed. This paper develops a numerical process for gap prediction before the assembly step. After the assembly components are scanned in a specified configuration, finite element meshes are created using the scanned data and the shape variations of each component caused by constraints and forces in different configurations are evaluated by finite element analysis. Assembly gaps are finally assessed by assembling the simulated preassembly shapes of all components. The feasibility of the proposed method is proved by an experiment. [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]

This paper presents a methodology for determining the optimal supply chain design with economic, environmental and risk management considerations. A multi-objective model based on mixed integer programming is proposed seeking three objectives: First, to minimize the total cost of transportation and the costs associated to the use of intermediate nodes. Second, to minimize the risks of product losses in transportation. Third, to minimize the environmental impact of CO2 emissions produced by transportation and storage operations. The proposed model is solved with two approaches: First, a commercial solver to compute the Pareto-optimal set of solutions. Second, a simulation-based optimization approach that allows to obtain statistically different but efficient solutions such that the decision-maker will be able to trade-off objectives while considering only Pareto optimal solutions. Experiments on random instances demonstrate the capability of the models and methods. [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]

Data reconciliation is a crucial technique to improve the accuracy of the measured data in industrial processes. However, most traditional data reconciliation researches mainly focused on global modeling for single mode processes, but little attention was paid to multimode processes. In this paper, a layered online data reconciliation strategy based on Gaussian mixture model is proposed for complex industrial processes with multiple modes. In the proposed data reconciliation framework, Gaussian mixture model is first used to identify and partition different operating modes from process data. Then, layered data reconciliation models are established for each operating mode. In the online data reconciliation step for new data, it is reconciled with the trained reconciliation models from different modes and its posteriors corresponding to different modes are calculated for new data. Finally, the reconciled result is obtained by the weighted sum of individual reconciled data in each operating mode. The effectiveness and feasibility of the proposed data reconciliation strategy are validated through a real industrial application on the sodium aluminate solution evaporation process. [ABSTRACT FROM AUTHOR]

Business process simulation (BPS) enables detailed analysis of resource allocation schemes prior to actually deploying and executing the processes. Although BPS has been widely researched in recent years, less attention has been devoted to intelligent optimization of resource allocation in business processes by exploiting simulation outputs. This paper endeavors to combine the power of a genetic algorithm (GA) in finding optimum resource allocation scheme and the benefits of the process simulation. Although GA has been successfully used for finding optimal resource allocation schemes in manufacturing processes, in this previous work the design of these algorithms is ad hoc, meaning that the chromosomes, crossover and selection operators, and fitness functions need to be manually tailored for each problem. In this research, we pioneer to design and implement a Petri Nets based Generic Genetic Algorithm (GGA) framework that can be used to optimize any given business processes which are modeled in Color Petri Nets (CPN). Specifically, the proposed GGA framework is capable of producing an optimized resource allocation scheme for any CPN process model, its task execution times, and the constraints on available resources. The effectiveness of the proposed framework was evaluated on archive management workflow at Macau Historical Archives and an insurance claim workflow from an Australian insurance company. In both case studies, the framework identified significantly improved resource allocation scheme relative to the one that existed when the data for the case studies were collected. [ABSTRACT FROM AUTHOR]