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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]

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]

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]

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

Production systems 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]

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]

Simulations are widely used in manufacturing system design, production planning and decision making. The aim of this paper is to present the possibility of using Monte Carlo simulations in the production plan optimizing and in the project risk management. Optimization is accomplished through two different approaches which principles and results are mutually compared. According to the first approach, production optimization is performed via a deterministic model using the Generalized Reduced Gradient algorithm. The second approach is based on the stochastic model. The optimized production plan is submitted to risk analysis. Two approaches are demonstrated in order to reduce the rate of risk. The first way is modifying the production plan to increase the forecast reliability; the second approach is limiting the uncertainty of key variables. The detailed methodology enables implementing presented approaches in solving various optimization tasks. [ABSTRACT FROM AUTHOR]

Currently, robotic manufacturing cells entail complex decisions concerning sequencing issues due to uncertainty which arises in different parameters such as time to failure, time to repair and cycle times that can be effectively supported by computer simulation models. The paper is focused on part sequencing of a two-machine robotic cell in a flow shop which produces different parts. The process is supported by a single gripper robot to load/unload products and also in displacement within the system. This study considers machine failures and repair such that S2 cycle time and total production cost should be minimized. In this study, simulation facilitated input part sequence and also data envelopment analysis method is applied to trace the optimum sequence for satisfying the objective functions. Results through some numerical examples showed some simulation advantages specially to model many uncertainties and what if analysis. [ABSTRACT FROM AUTHOR]

This paper proposes a study of a milling process planning to determine the tolerancing for manufacturing using statistical tool. The deviation between the machined surface and the surface corresponding to the nominal one due to combined errors is expressed in terms of the small displacement torsor parameters. These parameters are considered as random variables, displacements are expresses as variances. Experimentation is realised on a set of manufactured parts which consists of measuring various defects on machine tool. The experimental results and the simulation results are compared in this paper. [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]

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 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]

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

The purpose of this paper is to present an applicable approach for the valuation of in-plant logistics efficiency. Therefore, we developed a time-based efficiency concept that considers all relevant time losses when executing production logistics processes. The occurring delays are captured in real-time using modern auto-ID-technologies. For the valuation and improvement of in-plant logistics efficiency, we propose to use simulation modelling to investigate the cause-effect relations in the production system in advance. Thus, a discrete event simulation model has been constructed to model the workflow of a production system with discrete manufacturing processes and its in-plant logistics processes. The aim of the provided simulation study is to prove the functionality and to verify the applicability of the current approach in business practice. [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]

Selective Laser Melting (SLM) is actually the most attractive technique in an Additive Manufacturing (AM) technology because of the possibility to build layer by layer up nearly full density metallic components without needing for post-processing. One of the main problems in SLM processes is represented by the thermal distortion of the model during forming; the part tends to be deformed and cracked due to the thermal stress. Therefore, it is important to know the effect of the process parameters on the molten zone and consequently on the density of the consolidated material. Great advantage can be obtained from the prediction of temperature evolution and distribution. The aim of this study is to evaluate the influence of the process parameters on the temperature evolution in a 3D model. The developed code evaluates the distribution and evolution of the temperatures in the SLM process and simulates the powder-liquid-solid change by means of a check of the nodes temperature. (Received in June 2010, accepted in June 2011. This paper was with the authors 1 month for 1 revision.) [ABSTRACT FROM AUTHOR]

In recent years, the manufacturing sector has faced unparalleled levels of change and its intricacies are also challenging. This has lead to manufacturers acquiring new methods for planning and control of their manufacturing systems. One approach that can give good results in this context is simulation modelling. In this paper, a simulation modelling technique is applied to a bottling process in a winery to analyze the variations in the duration of the process with different changes in the production line. Step changes have been made during the simulation model construction. Based on the results of this study, it is possible to predict in which parts of the process it is best to invest so that a greater yield can be obtained. The objective of this study was achieved, since the process duration could be reduced from a two-day bottling process to attain all the bottling in a single day. [ABSTRACT FROM AUTHOR]

In this paper, a Multi-Criteria Scheduling Algorithm (MCSA) based on swapping of dispatching rules and Selective Rerouting (SR) approach based on lateral entry of critical jobs in the queue of alternate machine is used. Further, the effect of simultaneous application of MCSA and SR has been investigated. The system performance has been evaluated using mean flow time, maximum flow time, mean tardiness and maximum tardiness as the performance measures. Simulation studies using ProModel® simulation software were carried out at different breakdown levels for a range of part complexity and part mix, in three types of flexible job shops with Job/Machine ratio less than, equal to and greater than unity involving a total of 799 simulation runs. Each run of simulation spans for a period of 2000 completed jobs. The results establish that simultaneous application of MCSA and SR improves the system performance between 12.17 % to 28.73 % and 30.51 % to 47.67 % over that when SR and MCSA respectively are applied individually. The improvement is more at low breakdown levels and high part complexity. [ABSTRACT FROM AUTHOR]

Agents are autonomous and computational entities that perceive their environment through sensors and act upon their environment through effectors. Application of agents in simulation of manufacturing system helps in modelling the concurrent behaving entities close to the real system. A manufacturing agent should be modelled to impart the required functionality to the manufacturing entity. As agents are autonomous, they run asynchronously and need to be synchronized with the simulation clock for simulating the manufacturing system. This paper deals with the synchronization of manufacturing agents, working of the agent-based simulator of a shop floor controller for a sample manufacturing system and the hybrid communication protocols involved during simulation. The manufacturing agents were built on JADE™ platform, which is a leading multi agent development framework that helps in developing FIPA compliant agent-based systems. Agent-based modelling and simulation of entities in the manufacturing system provides flexibility for real-time decision making. [ABSTRACT FROM AUTHOR]

Cell Formation (CF) problem involves grouping the parts into part families and machines into manufacturing cells, so that parts with similar processing requirements are manufactured within the same cell. Many researches have suggested methods for CF. Few of these methods; have addressed the possible existence of exceptional elements (EE) in the solution and the effect of correspondent intercellular movement, which cause lack of segregation among the cells. This paper presents a simulation-based methodology, which takes into consideration the stochastic aspect in the cellular manufacturing (CM) system, to create better cell configurations. An initial solution is developed using any of the numerous CF procedures. The objective of the proposed method which provides performances ratings and cost-effective consist in determine how best to deal with the remaining EE. It considers and compares two strategies (1) permitting intercellular transfer and (2) exceptional machine duplication. The process is demonstrated with a numerical example. [ABSTRACT FROM AUTHOR]

Cellular manufacturing is an application of a group technology used to improve the performance of manufacturing systems. A number of factors, including vulnerability to machine breakdown, under utilization of resources and eventual unbalanced workload distribution in a multi-cell plan disturb the smooth working of the factory when using the group technology concept. This paper focuses on a manufacturing cell composed of unreliable machines. We are interested in the problem of cell production availability facing unexpected circumstances due to an internal perturbation caused by machine breakdown. We consider a policy of intercellular transfer in the event of breakdown to improve the availability of the cells. We examine through simulation the performance of the system and evaluate the intercellular transfer policy in terms of some selected criteria. The results indicate, under the assumed conditions, that the developed policy improves the performance of the production cells. [ABSTRACT FROM AUTHOR]