Evaluation Of Flexible Manufacturing Systems Research Articles

Reliability evaluation of flexible manufacturing systems based on three-layer index system with time-varying weights

With the development of industrial manufacturing, flexible manufacturing system provides an effective way to improve the machining quality and efficiency, as well as reduce the manufacturing cost. Fflexible manufacturing system reliability has been one focus of recent studies. But a systematic, effective and executable reliability evaluation method has not yet proposed in existing researches. This work firstly presented a three-layer index system for flexible manufacturing system reliability evaluation, which is composed of the whole layer indexes, subsystem layer indexes and equipment layer indexes determined by system composition and running features analysis. Time-varying weights of each layer are calculated through the modelling of the reliability and reliability importance based on the classical two-state failure hypothesis. Then, considering multi-state failure modes of elements, a fuzzy evaluation model of flexible manufacturing system reliability is established based on fault grading and statistics, considering grade and number distributions of faults within a certain statistical period. Moreover, through a simulation case of a box-parts finishing flexible manufacturing system, the influence of failure rates and service time on the index weights distribution is firstly revealed, which can provide theoretical basis for the improvement of flexible manufacturing system reliability; then the effectiveness of the proposed method is verified through the comparison of results obtained by the previous model based on two-state failure and the proposed model based on multi-state failure.

Manufacturing-Production Systems and Their Importance: Evaluation of Flexible Manufacturing Systems (FMS)

Flexible manufacturing systems (FMS), transitional or absolute customer to encounter the various requirements and preferences, helping to protect organizations which in the circumstances of competitive environment in eachother exactly known always to created, are constructed as a structure that could really keep producing various products and services with minor modifications. Computers are used to help manufacturing lines. This research provides the literature review of manufacturing-production systems, categorisation of manufacturing techniques, advanced manufacturing technologies, manufacturing process modeling, modeling definitions, and database organizational structures, data regulations and procurement for Flexible Manufacturing Systems-Techniques, and eventually the research conclusion and recommendation. Mostly with significant developments in the manufacturing sector, the database idea has become an essential and fundamental element of every type of production system. Its most fundamental tasks are the preservation and accessibility of services required to regulate industrial operations. This study also utilizes SWOT (Strengths, Weaknesses, Opportunities, and Threats) evaluation to explore the appropriateness of manufacturing techniques, FMS in industrial manufacturing automated processes. The highlighted elements indicate manufacturing systems' considerable potential to address advanced manufacturing modernization challenges.

A Simulation-based Framework for the Economic evaluation of Flexible Manufacturing Systems

Due to the increasing market demand volatility, globalization of markets and shorter product life cycles, the importance of flexible manufacturing systems gain more and more importance across all industry sectors and sizes of companies. Especially, the increasing planning uncertainties concerning the product mix and volume lead to a growing demand for flexibility. In this context, methods for the economic evaluation of flexible manufacturing systems take a significant role in drawing meaningful conclusions, which allow the creation of an optimized level of flexibility. This paper presents a simulation-based framework for an assessment methodology in order to conduct an economic evaluation of flexible manufacturing systems. Within the developed framework, costs induced by flexibility are allocated activity-based according to their actual cause. The identification of flexibility-induced cost and their causes, provide an overall improved cost transparency. Based on this, target-oriented optimization can be applied more effectively.

A Group Decision Making Approach for the Evaluation of Flexible Manufacturing Systems

In today’s competitive global market, manufacturing companies extremely compete to produce products of the highest quality, the lowest cost, and the best customer satisfaction. The survival of a company depends on the capable of tackling with variations and adapting changing conditions. In this respect, flexible manufacturing systems (FMS) are capable of processing various parts, styles and quantities of production in manufacturing systems. However; it is quite complex process for firms to decide the appropriate FMS design as it involves multiple and conflicting criteria and multiple decision makers under various uncertainties. The fuzzy set theory offers an efficient tool to cope with vagueness and to define performance measurement of FMS in a multi-attribute group decision making (MAGDM) framework. In this study, we present a MAGDM approach based on hesitant fuzzy sets to evaluate FMS in a fuzzy environment. A practical example is also provided to demonstrate the proposed methodology.

Performance evaluation of flexible manufacturing system using digraph and matrix/GTA approach

The aim of this paper is to identify and analyse various measures and sub-measures that could influence the performance of flexible manufacturing system (FMS) and to develop a model to manage these measures. In this research work, digraph and matrix methodology has been utilised for determining the impact of different measures on the performance of FMS with the help of a single numerical value, i.e., index of performance. The findings of this study have important managerial significance. The management can determine the measures which strongly affect the performance of FMS with the help of this approach and can obtain better insight and guidelines for determining various decisions relating to process and operations improvement to improve the performance of the system. The procedure helps to compare different industries in terms of their performance index. If the performance index value of an industry is not as per with the required range, then, performance index of all the measures should be compared and weak measures should be made stronger by making improvements in the concerned measuring elements. Evaluation of performance index for an organisation, comparison of different industries performance and ways to improve the performance are a unique contribution in this domain.

Multi attribute decision making model for the evaluation of flexible manufacturing system

A Multi attribute decision making model for evaluation of alternative Flexible manufacturing systems and rank them suitably when their attribute features are presented in a combination of cardinal and ordinal values is discussed. A decision supporting model which readily accepts the cardinal and ordinal data for the attribute features of the alternatives and gives out the evaluation of the alternatives in terms of ranks is developed.

Multi Attribute Decision Making Model for the Evaluation of Flexible Manufacturing System

A Multi attribute decision making model for evaluation of alternative Flexible manufacturing systems and rank them suitably when their attribute features are presented in a combination of cardinal and ordinal values is discussed. A decision supporting model which readily accepts the cardinal and ordinal data for the attribute features of the alternatives and gives out the evaluation of the alternatives in terms of ranks is developed.

Performance evaluation of flexible manufacturing systems under uncertain and dynamic situations

The present era demands the efficient modelling of any manufacturing system to enable it to cope with unforeseen situations on the shop floor. One of the complex issues affecting the performance of manufacturing systems is the scheduling of part types. In this paper, the authors have attempted to overcome the impact of uncertainties such as machine breakdowns, deadlocks, etc., by inserting slack that can absorb these disruptions without affecting the other scheduled activities. The impact of the flexibilities in this scenario is also investigated. The objective functions have been formulated in such a manner that a better trade-off between the uncertainties and flexibilities can be established. Consideration of automated guided vehicles (AGVs) in this scenario helps in the loading or unloading of part types in a better manner. In the recent past, a comprehensive literature survey revealed the supremacy of random search algorithms in evaluating the performance of these types of dynamic manufacturing system. The authors have used a metaheuristic known as the quick convergence simulated annealing (QCSA) algorithm, and employed it to resolve the dynamic manufacturing scenario. The metaheuristic encompasses a Cauchy distribution function as a probability function that helps in escaping the local minima in a better manner. Various machine breakdown scenarios are generated. A ‘heuristic gap’ is measured, and it indicates the effectiveness of the performance of the proposed methodology with the varying problem complexities. Statistical validation is also carried out, which helps in authenticating the effectiveness of the proposed approach. The efficacy of the proposed approach is also compared with deterministic priority rules.

Performance Evaluation of Flexible Manufacturing Systems with Finite Local Buffers: Fixed and Dynamic Routings

This article evaluates the performance of flexible manufacturing systems with finite local buffers and fixed or dynamic routing rules, and addresses the optimal design or system configuration problem of maximizing the system throughput. The costs include machine cost, part (or pallet) cost, and local buffers cost. First, the system throughputs and their behaviors are considered with both queueing network analysis and simulation, and it is shown for a fixed routing model that the system throughput in the case of finite local buffers is greater than in the case of infinite local buffers. For a fixed versus dynamic routing rule, it is also found that the throughput in the former case can be close to the one in the latter case by changing the setting parameters. Next, the design problems of maximizing the system throughput are considered numerically for fixed and dynamic routing cases. Then, it is seen that better combination of design variables is a class of the monotonicity in local buffers, service rates, and routing probabilities.

A nonparametric stochastic procedure for FMS evaluation

Evaluating alternative manufacturing technologies in the presence of multiple performance measures is often a difficult task for the decision maker. It is for this reason that justification and evaluation of flexible manufacturing systems has been receiving significant attention in the manufacturing circles. This paper proposes an innovative framework, which is based on the combined application of data envelopment analysis and nonparametric statistical procedures, for the selection of flexible manufacturing systems. The strengths of this methodology are that it incorporates variability measures in the performance of alternative systems, provides decision maker with effective alternative choices by identifying homogeneous groups of systems, and presents graphic aids for better interpretation of results. The methodology is illustrated through its application on a previously reported data set.

Implementation of an object-oriented tool for the simulation of manufacturing systems and its application to study the effects of flexibility

Although there is a reasonable number of currently available modelling tools for the analysis and evaluation of flexible manufacturing systems, these models, in general, neglect flexibility. They do not consider that in a flexible manufacturing system there is the possibility of different operation sequences. As a consequence, while flexibility in manufacturing is much 'in vogue', the development of models that are able to improve the understanding and consequences of having flexibility is still incipient in the literature. This paper presents work to develop a tool to support the analysis of flexible automation. The tool described is an objectoriented discrete-event simulator, called OOSimFlex, capable of modelling different alternative systems design and analysing a manufacturing system using multiple performance measures under different manufacturing flexibility levels. The paper describes the major theoretical concepts employed for the development of a highly flexible and interactive simulation model environment.

A decision model for evaluation of flexible manufacturing systems in the presence of both cardinal and ordinal factors

This paper presents a model for evaluating alternative Flexible Manufacturing Systems by considering both quantitative and qualitative factors. The evaluation process utilizes a recently proposed Data Envelopment Analysis (DEA) model, which incorporates both ordinal and cardinal measures, in conjunction with new extensions in DEA. The paper contributes to the body of knowledge in two important ways. First, it provides a new model based on pair-wise comparisons of specific alternatives, which significantly improves the discriminatory power of DEA. The second major contribution is to detail the model's utility in its application for evaluating strategic manufacturing technologies, specifically Flexible Manufacturing Systems. The consideration of both tangible and intangible factors, which is a primary goal in strategic evaluation of systems, is achieved in this methodology. The model is illustrated through an application on a previously reported data set. The analysis of results provide useful insights that include both seller's and buyer's perspectives of system evaluation.

IDSSFLEX: an intelligent DSS for the design and evaluation of flexible manufacturing systems

IDSSFLEX: an intelligent DSS for the design and evaluation of flexible manufacturing systems

IDSSFLEX: an intelligent DSS for the design and evaluation of flexible manufacturing systems

This paper describes IDSSFLEX, a computer system for the analysis and evaluation of Flexible Manufacturing System (FMS) design configurations. IDSSFLEX is an intelligent decision support system which selects from among several configurations and control strategy alternatives of design, the most appropriate one for a specific case. In order to accomplish such an objective, the system presents simultaneously the following features: ability to quantify subjective factors, ability to account for individual preferences, and ability to cope with multiple criteria decision making. A case study illustrates the effectiveness of the computer system.

IDSSFlex: An Intelligent DSS for the Design and Evaluation of Flexible Manufacturing Systems

IDSSFlex: An Intelligent DSS for the Design and Evaluation of Flexible Manufacturing Systems

Intelligent decision support system for flexible manufacturing system design

The aim of this paper is to develop a new methodology of analysis and evaluation of Flexible Manufacturing System (FMS) design configurations. It examines the use of an integrated, systemic, global and user oriented approach for the complex problem of selecting among several configuration alternatives the most suitable for a specific case. The methodology is implemented using the Decision Support System framework, offering an objective tool to help managers and engineers during the design stage of the development cycle of these manufacturing systems. A case study illustrates the effectiveness of the developed methodology.

EVALUATING FLEXIBLE MANUFACTURING SYSTEMS ALTERNATIVES USING DATA ENVELOPMENT ANALYSIS

ABSTRACT The decision to invest in flexible manufacturing systems (FMS) and other advanced manufacturing technologies has been an issue in the practitioner and academic literature for over two decades. To this end, a number of models have been proposed to help decision makers evaluate FMS. Many of these models realize that the justification and investment process will require the consideration of multiple criteria that are capable of incorporating both traditional and non-traditional factors. In this paper data envelopment analysis (DEA) modeling is introduced as a technique to aid in the evaluation of FMS. A number of DEA models and some extensions are presented to aid in the investment and adoption decision process. Managerial and research implications for the use of these models are also presented.

The Performance Evaluation of Flexible Manufacturing Systems with Dynamic Routing and Its Optimal System Configurations

The Performance Evaluation of Flexible Manufacturing Systems with Dynamic Routing and Its Optimal System Configurations

The Performance Evaluation of Flexible Manufacturing Systems with Finite Local Buffers and its Design Problem

The Performance Evaluation of Flexible Manufacturing Systems with Finite Local Buffers and its Design Problem

A chance-constraints linear programming model on the economic evaluation of flexible manufacturing systems

Abstract The implementation of flexible manufacturing systems lFMSsr normally entails a large initial investment under a long-term, uncertain environment. Many effects of installing a FMS will be due to improvement in throughput efficiency, quality, flexibility and the opportunity costs. However, most economic evaluations of FMSs assume the problem is deterministic, such that they fail to model accurately and capture the nature of FMSs. This paper uses stochastic variables to capture the.nature of a FMS under given resource limitations and leads to a multistage chance-constraints linear programming lLPr formulation. Finally, in order to incorporate the uncertainty of capital investment, the interest rate as a function of time is considered over the whole planning horizon and the decision model is extended under continuous and variable discounting.