Simulation Of Flexible Manufacturing Systems Research Articles

Building a Reusable Data Model to Support Systematic Layout Planning with Discrete Event Simulation of Flexible Manufacturing Systems

Manufacturing has undergone a greater change in recent years than it has over almost the entire past century. Due to the variety of products, shortening delivery times and changing customer habits, the COVID-19 pandemic has demanded greater flexibility from manufacturing companies than ever before. One of the fundamental parts of manufacturing flexibility is the design of manufacturing layouts, which has so far not followed automation and methodological developments with regard to technological areas of manufacturing. In this article, a new method for supporting traditional factory design methods with digital manufacturing tools is introduced.

Simulation of flexible manufacturing systems at the preliminary design stage

Approaches to more efficient design of machining equipment in flexible manufacturing systems are analyzed, with particular application to the aviation industry, the manufacture of airplane engines, and high-tech manufacturing.

Simulation Modeling and Analysis for Investigation of Part Launching Rule in a FMS Scheduling

Background/Objectives: The intention of this simulation study is to inspect the effect of multi-level scheduling rules on the four different performance measures of proposed FMS (flexible manufacturing system). Methods/Statistical Analysis: Input data has been collected from the real existing system and proposed FMS simulation model has been developed using JAVA programming. Findings: The flow of parts through the system has been managed with multi-level scheduling rules related to launching of parts in to a system. The proposed simulation model has been modeled for the existing system and a common optimum part selection rule for the performance parameters such as MFT(mean flow time), make span, mean machine utilization, and mean Automated Guided Vehicle (AGV) utilization has been developed. Application/Improvements: Case study has been conducted on the existing system and the proposed simulation model has been created. The shortest processing time rule was found to be optimum upon comparing other two scheduling rules when output performance measures considered. The proposed simulation model aids in better scheduling of automobile and electronics applications.

Development and evaluation of feature-focused dynamic routing policy

This paper reports on a development of feature-focused dynamic routing policy and its evaluation in a flexible manufacturing systems (FMS) simulation framework. The dynamic policy is based on an integrative methodology in which process planning system IMPlanner is integrated with FMS simulation module. IMPlanner’s rule-based system process selection system performs knowledge-intensive task of generating alternative processing options for each feature for parts in production plan. Generated alternative routings (process plan network) for each part are utilized in the FMS simulation module such that routing decision in FMS are made on periodic intervals by considering alternative processes for each feature and making decision based on the current system status and performance. The proposed framework has been evaluated in an experimental FMS simulation module, implemented in Arena, in which two performance criteria, machine utilization and WIP, were used to make routing decisions. The feature-focused approach is compared with traditional static decision-making, and its improved performance is demonstrated.

Modeling and Analysis for Minimization of Mean Flow Time in FMS Simulation

The aim of this paper is to deal with a simulation study on effect of part launching, part sequencing at central buffer and tool selection rules on a flexible manufacturing system (FMS) involving tool movement along with part movement policy. A typical FMS is selected for a study of discrete event simulation model. Simulation experiments are conducted on various combinations of decision rules and it is found to be good in evaluated performance measures.

Energy Modeling and Simulation of Flexible Manufacturing Systems Based on Colored Timed Petri Nets

SummaryIncreasing pressures from a variety of directives and standards have caused manufacturing enterprises to consider and implement energy assessment and energy performance goals—to improve both their economic and their environmental performance. Flexible manufacturing systems (FMSs) pose a challenge for energy management because of their complexity and the difficulty of data collection. FMSs allow manufacturers to adjust to customers’ requirements and meet changing demands, which makes it possible for manufacturers to respond quickly to the market. To address this challenge, a practical energy model for machining systems based on colored timed Petri nets (CTPNs) is proposed. In this article, the energy consumption of FMS are first analyzed. Then, an energy model of FMSs based on CTPNs is proposed in which the uncertainty of task assignment and volatility of operation time are treated by Petri net (PN) functions so that data on the consumption of FMSs can be collected automatically. Finally, through the case study of an FMS with two jobs, the proposed energy model is simulated and the simulation results with colored PN tools are shown to be significant in practice.

Analysis of performance measures of flexible manufacturing system

Flexible manufacturing system (FMS) is a highly integrated manufacturing system. The relation between its components is very complex. The mathematical programming approaches are very difficult to solve for very complex system so the simulation of FMS is widely used to analyze its performance measures. Also the FMS components are very sophisticated and costly. If FMS has to be implemented then it is better to analyze its results using simulation which involves no loss of money, resource and labor time. As a typical discrete event system FMS have been studied in such aspects as modeling and performance analysis. In this paper, a concept and implementation of the Petri nets for measuring and analysis of performance measures of FMS is applied. Also the system has been modeled in Visual Slam software, i.e. AweSim. The other well defined mathematical technique, i.e. bottleneck technique has also been applied for the purpose of comparison and verification of the simulation results. An example FMS has been taken into consideration and its Petri net model, AweSim model, and mathematical model has been constructed. Several performance measures have been used to evaluate system performance. And it has been found that the simulation techniques are easy to analyze the complex flexible manufacturing system.

Simulation of a Flexible Manufacturing System with AutoMod Software

A flexible manufacturing system (FMS) is a highly automated, complex system. Simulation is a well-proven method to design or analyze an FMS. Deployment of a radio frequency identification (RFID) system in FMS produces large volumes of RFID data streams, which provide valuable information to improve the operation of FMS. Different frameworks are presented in this paper regarding the use of RFID data streams in an FMS simulation. Simulations are performed with AutoMod software. Related technical details are also presented. The paper’s structure is complied as the following steps: step 1, the introduction of AMHS, FMS and AutoMod; step 2, FMS simulation using AutoMod software; step 3, simulation frameworks driven by RFID data streams; step 4, conclusion.

Using mega-trend-diffusion and artificial samples in small data set learning for early flexible manufacturing system scheduling knowledge

Neural networks are widely utilized to extract management knowledge from acquired data, but having enough real data is not always possible. In the early stages of dynamic flexible manufacturing system (FMS) environments, only a litter data is obtained, and this means that the scheduling knowledge is often unreliable. The purpose of this research is to utilize data expansion techniques for an obtained small data set to improve the accuracy of machine learning for FMS scheduling. This research proposes a mega-trend-diffusion technique to estimate the domain range of a small data set and produce artificial samples for training the modified backpropagation neural network (BPNN). The tool used is the Pythia software. The results of the FMS simulation model indicate that learning accuracy can be significantly improved when the proposed method is applied to a very small data set.

Modelling and simulation of an intelligent flexible manufacturing system via high-level object Petri nets (HLOPN)

A dynamic model of a flexible manufacturing system (FMS) is considered based on the information characteristics of system infrastructure. According to the physical architecture and working requirements, a software framework for FMS modelling and simulation is proposed to describe the parallel flow of different work-pieces in the shop. The model is based mainly on the concepts of both object-oriented programming and high-level Petri net methods. A material transportation protocol is designed to realize the respective processing of routine orders of work-pieces within the main resources of the FMS shop. Using a specially designed protocol, a fully automated job shop FMS can be achieved. An FMS simulation tool that can show the dynamic process of all the system resources during task execution is finally introduced.

Object-oriented modeling and simulation of flexible manufacturing systems: a rule-based procedure

Simulation by a software model, is one of the most frequently used techniques for the analysis and design of manufacturing systems. In the software engineering research area, the object-oriented approach has fully demonstrated to be an effective technique with respect to the design and implementation phases of complex software projects. Even if object-oriented programming has proven to be a powerful technique, a systematic design method should also be used in order to implement reliable software, in particular in the development of simulation models. This paper presents a new procedure to develop flexible manufacturing system (FMS) simulation models, based on the UML analysis/design tools and on the ARENA ® simulation language. The two main features of the proposed procedure are the definition of a systematic conceptual procedure to design FMS simulation models and of a set of rules for the conceptual model translation in a simulation language. The goal is to improve the software development efficiency through a rule-based approach and to add some of the fundamental object-oriented features to the ARENA ® simulation environment.

A knowledge Petri net model for flexible manufacturing systems and its application for design and verification of FMS controllers

The development of a Flexible Manufacturing System (FMS) controller is a very complicated task, both in the aspects of hardware and software. The design and verification of the controller is crucial for the development of FMS prior to putting it into test and use. This paper presents a knowledge-based Petri net model for FMS and its application for design and verification of an FMS controller. The modelling of FMS is implemented through incorporating Petri net techniques with general problem-solving strategies in AI and knowledge-based system techniques. The places and transitions and their relations of the knowledge Petri nets are annotated, based on an object oriented representation and programming techniques, from which the knowledge Petri nets can be formulated. A template can be first defined for a knowledge Petri net model, and then the model for FMS individuals is established in the form of instances of the template. The design and verification of an FMS controller is based on the checking for the control parts of FMS with the help of temporal relationships between the specification and physical operations of the FMS controller. The approach makes it simple to express FMS controls, and procedural language can be used for knowledge and information processing. It is thus possible to make a computer programme generate a Petri net for a given FMS, which is envisaged as necessary for the design and verification of an FMS controller. The developed knowledge Petri net system for FMS is internetenabled and implemented through Java. It can be used for modelling and simulation of FMS, the design and verification of an FMS controller both as a standalone application and a www browser applet on the internet. Case studies are provided for the modelling and analysis of a FMS, and the design and verification of the FMS controller, to show the effectiveness over development with conventional methods and systems.

Intelligent Manufacturing Systems: Intelligent Protocols for Communication Within FMS

In this paper recent results on intelligent communication protocols (ICP) tailored for applications within flexible manufacturing systems (FMS) are presented. These have been derived on the grounds of the concept of ICP emulation by using the technique of object oriented modelling and emulation programming. The resulting ICP have been tested through their application in parallel simulation of complex medium size FMS. Developed models have been derived using three alternatives: math-analytical queue, adequate Petri-net, and appropriate object-oriented models. Some of simulations results obtained illustrate this novel development in ICPs for FMSs. Copyright ©2001 IFAC

Modeling and Simulation of Flexible Manufacturing Systems Controlled by Petri Nets

A software tool for modeling and simulation of Flexible Manufacturing Systems is proposed in this paper. Variety of robots, conveyers and working machines can be used in building of the FMS. Control program for the whole system is written through Petri net model. Transformation from Petri net into control program is automated. Programming language is derived from real language for robot control. Simulation is done in 3D environment with full real-time animation. Used technique of 3D animations allows using different views to system with full zooming and change of angle and position.

The development of intelligent decision support tools to aid the design of flexible manufacturing systems

The design of flexible manufacturing systems (FMSs) is an essential but costly process. Although FMS design appears to be an excellent area for applying artificial intelligence (AI) and computer simulation techniques, to date there have been limited investigations on integrating AI with the modular simulation software available for FMS design. In this paper an integrated approach for the automatic design of FMS is reported, which uses simulation and multi-criteria decision-making techniques. The design process consists of the construction and testing of alternative designs using simulation methods. The selection of the most suitable design (based on the multi-criteria decision-making technique, the analytic hierarchy process (AHP)) is employed to analyze the output from the FMS simulation models. Intelligent tools (such as expert systems, fuzzy systems and neural networks), are developed for supporting the FMS design process. Active X technique is used for the actual integration of the FMS automatic design process and the intelligent decision support process.

Application of software reuse and object-oriented methodologies for the modelling and control of manufacturing systems

In this paper object-oriented design and the application of software reuse of components of flexible manufacturing systems (FMS) will be introduced. The goal of this research is to provide methods and tools to build up FMS simulation models and control strategies easily, fast and reliably. As a software tool the SALMS reuse repository and its application will be demonstrated. The design methodology used for model development is based on the object-oriented Rational Rose CASE tool and on the use-case design of the OOSE methodology. A hybrid simulation and scheduling system (SSS) is used to validate and evaluate all results. SSS has been implemented as a combination of a traditional simulation/animation system (SIMAN/Cinema) and an intelligent expert environment (G2). The application of the real-time, intelligent G2 environment points to one of our R and D goals, to create intelligent, real-time control of FMS. Reuse in SIMAN/Cinema and in G2 will be analysed separately and together in general, and in the context of FMS.

An Investigation of Stochastic Analysis of Flexible Manufacturing Systems Simulation

This paper describes the use of an ARIMA (autoregressive-integrated-moving-average) model and its equivalent state space models to produce rule-based knowledge for flexible manufacturing systems (FMS) that can be used to investigate a wide variety of problems including machine breakdown, material shortage, and changes of scheduling rules. One great advantage of using the proposed models is the ease with which the simulation results can be summarised, analysed and captured, as well as the availability of the mathematical representation of the knowledge that can be kept in a knowledge database for evaluation and selection of alternative FMS strategies in a real-time environment. Various case studies are used to illustrate the methodology and the development of ARIMA and state space models, the analysis includes the system cost and stability of changes or interventions, the relationships among the simulation inputs and outputs, and the formulation of the production rule-base for the FMS scheduler. Management can use this integrated approach to describe and predict the dynamic behaviour of a complex FMS.

Modelling, scheduling and simulation of flexible manufacturing systems using extended stochastic high-level evaluation Petri nets

The present paper presents the new extended stochastic high-level evaluation Petri nets (ESHLEP-N) which are more suitable for modelling and simulation of flexible manufacturing systems (FMSs). The advantages of ESHLEP-N lie in the fact that their resulting models are not only simpler, more intuitive and more descriptive, but also of the more inferential and decisive power. Based on the ESHLEP-N model, the scheduling and simulation expert system (ES) for the FMS is designed and established. With the help of the ES, we will put forward some new dynamic-rescheduling rules aiming at reducing no-inputs and blockings. The simulations show that the throughputs of the rescheduling can increase on an average by 6.48% as compared with those of the non-rescheduling. The comparison between the experiment on the real FMS and the simulation on the ES indicates that the ES is effective.

A study of scheduling rules of flexible manufacturing systems: A simulation approach

This study examines the effects of scheduling rules on the performance of flexible manufacturing systems (FMSs). Several machine and AGV scheduling rules are tested against the mean flowtime criterion. In general, scheduling rules are widely used in practice ranging from direct applications as a stand-alone scheduling scheme to indirect application as a part of complicated scheduling systems. In this paper, we compare the rules under various experimental conditions by using an FMS simulation model. Our objective is to measure sensitivity of the rules to changes in processing time distributions, various levels of breakdown rates, and types of AGV priority schemes. A comprehensive bibliography is also presented in the paper.

Tools for Design and Optimal Control of Production Line and Flexible Manufacturing Systems

Abstract Flexible manufacturing system (FMS) is a net of workstations interconnected by ways which are followed by products. This paper introduces the factors which influence the design and control of FMS and shows by using the Petri nets and Markovian decision process the FMS modelling and simulation.