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Flexible Manufacturing System (FMS) offers opportunities for manufacturers to improve their technology, competitiveness, and profitability through a highly efficient and focused approach to manufacturing effectiveness. Data envelopment analysis (DEA) has been utilized as a multiple criteria tool for evaluation of FMSs. The concept of the assurance region (AR) is restricting the ratio of any two weights to some range to avoid the evaluated alternatives from ignoring or relying too much on any criterion in evaluation. In this paper, we develop a fuzzy DEA/AR method that is able to evaluate the performance of FMS alternatives when the input and output data are represented as crisp and fuzzy data. Based on Zadeh's extension principle, a pair of two-level mathematical programs is formulated to calculate the lower and upper bounds of the fuzzy efficiency score of the alternatives. We transform this pair of two-level mathematical programs into a pair of conventional one-level DEA/AR method to evaluate the FMS performance. An example illustrates the application of the proposed methodology. Keywords: Flexible manufacturing system; Data envelopment analysis; Assurance region; Fuzzy sets

The characteristics of activity structures where customized offerings are created with near mass production efficiency are analyzed by outlining modularity and build-to-order production as key features of customizing. The analysis illustrates that a supplier must combine the potential for flexibility offered by the principle of build-to-order production with elements of the rigidity associated with mass production systems in order to customize at reasonable cost.

This paper explores the hierarchical production planning (HPP) problem of flexible automated workshops (FAWs), each of which has a number of flexible manufacturing systems (FMSs). The objective is to decompose medium-term production plans (assigned to an FAW by ERP/MRP II) into short-term production plans (to be executed by FMSs in the FAW) so as to minimize cost on the condition that demands have just been met. Herein, the HPP problem is formulated by a linear programming model with the overload penalty different from the underload penalty and with demand constraints. Since the scale of the model for a general workshop is too large to be solved in the simplex method on a personal computer within acceptable time, Karmarkar's algorithm and to interaction/prediction algorithm, respectively, are used to solve the model, the former for the large scale problems and the latter for the very large scale. With the help of the above-mentioned algorithms and HPP examples, Karmarkar's algorithm and the interaction/prediction algorithm are compared and analyzed, the results of which show that the proposed approaches are quite effective and suitable for both 'push' and 'pull' production. Keywords: Flexible automated workshops; Flexible manufacturing systems; Hierarchical production planning; Karmarkar's algorithm; Interaction/prediction approach

The aim of this paper is to present some existing and several new indicators of performances useful to help the designer to find a good solution for morphology and choice of material handling systems in flexible manufacturing systems. Our purpose here is to focus on the evaluation of the pair morphology-material handling systems, studied concurrently due to their strong interdependence. As a result of a survey of literature in this area, we present in this paper the indicators we have retained as suited to this purpose and easily implemented. New indicators related to the performances of these systems, such as the flexibility, are also suggested. A classification of indicators is introduced: (1) the operational indicators, which characterise the dynamic behaviour of the studied FMS such as the mean flow-time of jobs or the utilisation rates of machines; (2) the strategic indicators which measure the capacity of the system to evolve toward manufacturing new products such as the flexibility on which the emphasis is put; (3) the economic indicators such as the purchasing cost, the functioning cost or the maintenance cost. To better introduce the role, the usefulness of each indicator and their practical use, an illustrative example is presented.

Several evaluation methods with various types of flexibility have been developed over the years to evaluate various manufacturing systems. However, it is not easy to use them to evaluate the flexibility of manufacturing systems because of three limitations: 1) ambiguous definitions of flexibility, 2) interdependence among various types of flexibility, and 3) mixed use of available and realized flexibility. This paper proposes a new concept of flexibility called comprehensive flexibility. Then it is quantified: it is an integrated performance measure which covers various types of flexibility in manufacturing systems. A case example is presented to illustrate the process of quantifying the proposed measure and interpret the meaning of the measure.

The flexible/agile production paradigm has replaced the mass production paradigm as the dominant framework in industrial management. One of the trends reflecting this paradigm shift is the transition from people control to customer satisfaction. Furthermore, in the flexible production paradigm, workers receive wages based on their qualifications and not according to piece-rate basis.

A manufacturing facility can be considered flexible if it can adapt to changes rapidly and economically, both in its internal and external environment. Routeing flexibility, or the capacity of a facility to manufacture each product through anyone of several routes, is necessary in today's constantly changing market as it allows the facility to address changing production situations. Process planners are tasked with identifying the routes most feasible to production. Route selection problem involves identifying the set of routes which should be implemented so as to optimize costs related to routeing flexibility.

The objective of this study is to develop a general design and performance evaluation model for the system designers in the initial design phase of the integrated manufacturing system based on the RAM(Reliability, Availability and Maintainability) and life cycle cost(LCC). The methodology proposed in this research, includes the following three-step generative approach. First, a deterministic approach to find the optimal system configuration for the initial system configuration is considered under the assumption that the system availability is one(no failure and maintenance), and in second step a stochastic simulation model based on RAM and LCC is developed. Using the results of this two-stage simulation, a system performance index(SPI) was developed for the performance evaluation of the system. In the last step we developed a simulation model using FACTOR/AIM to consider a variety of performance factors and compared the results through a sample example. Key words: Flexible Manufacturing System, Integrated Manufacturing Systems, Simulation, RAM, LCC

In this paper, performance measures such as mean flow time and work-in-process inventories will be used to determine the changes in the performance of a cellular manufacturing system due to product mix variations.

The implementation of flexible manufacturing systems (FMS) can significantly enhance the competitiveness of small- and medium-sized enterprises (SMEs). FMS can improve production efficiency, flexibility and quality control. To ensure success, however, SMEs should also develop organization structures and corporate cultures that complement the efficiencies offered by FMS.

Manufacturing cells and flexible assembly allow PacSci's Motor Products Div. to produce step motors in a wide range of configurations and lot sizes Rockford, IL - Set up a focused […]

Introduction Traditional manufacturing Stable, repetitive tasks, high volumes and long runs of standard product designs have been the mainstay of traditional manufacturing industries. These tasks lead to the lowering of [...]

The application of options theory to the valuation of expansion-flexible manufacturing systems (FMS) is explored. The problem, which is encountered in the evaluation of FMS investment plans, is characterized by a model for exchanging risky assets which addresses the weaknesses of the net present value method. An illustrative example of two-period investments is also discussed to show the advantages of the approach.

Having gone public this past summer, Rawlings Sporting Goods is successfully growing its apparel business and dramatically improving its production by adopting some of today's most advanced flexible manufacturing concepts. [...]

With organizations seeking every possible way of becoming more competitive, a careful examination of the workplace now offers significant scope for improving organizational performance. Advances in IT and telecommunications remove many barriers of time and space, creating opportunities for adopting flexible work practices such as remote working, flexible offices and teleworking. This article examines the opportunities draws on the author's experience within the U K subsidiary of Digital Equipment Corporation, an organization that has gained significant practical experience in implementing flexible working.

The use of Flexible Manufacturing Systems (FMS) as a key factor in improving productivity has become widespread. FMS is considered by the Japanese as the most important element in maintaining future competitiveness. Though flexibility has become a 90s 'buzz word', its management is poorly understood; many FMSs show a marked lack of flexibility. The selection of an FMS must be matched to the needs and competence of the company. The development of a sequential tool, a framework for analysis, will help. The framework is based on the need to ensure consistency between the firm's strategy and environment and FMS selection and implementation. Five competitive forces will affect the decision. Suppliers have an important influence on implementation of an FMS as it can shift the bargaining relationship between supplier and buyer. In addition the implementation of an FMS results in a changed relationship between buyer and seller. Another effect of an FMS is to alter the level of competition in an industry by increasing product differentiation and market segmentation. On the one hand, the level of initial investment needed may raise the entry barrier; on the other hand, exit barriers can be reduced as companies can sell or use the system for other purposes. One of the significant results of FMS implementation can be the change in industry boundaries. Industry and market trends analysis will indicate the optimum level of flexibility. The company should be able to specify the level of incremental revenue if it were to implement FMS immediately. Of course, the decision is also dependent on competitors' activities. While making the decision, technology forecasts need to be considered and this should be followed by the development of a manufacturing strategy. This has to be linked to business strategy before the flexibility level can be agreed. Strategic flexibility is the combination of design, volume and product mix flexibilities facilitating the manufacturing strategy. Design flexibility is the ease with which new parts can be added or subtracted, allowing the company to respond to the market. Volume flexibility provides the ability to operate profitably at different overall output levels and product mix flexibility is the product range which can be made without major capital cost. The actual selection of FMS equipment can involve simulation techniques, manufacturers' recommendations, learning decisions and other procedures. This should be followed by the financial evaluation and the techniques can be any of the standard ones. At this point management needs to consider the organization and skills implications. Often the real barrier is not the hardware but the managerial infrastructure. The organization needs to be able to adapt to the demands of the FMS by balancing conflicting pressures for innovation while maintaining the firm's traditional values and culture.

In an effort to cope with heightened global competition, powerful large firms have been searching for 'flexibility'--emphasizing lean production, downsizing, outsourcing, and dispersed production networks. But as fast as the […]

Flexible material handling systems help manufacturers meet changing market demands. For most companies, the days of dedicated machinery producing hundreds of thousands of identical parts have been over for several […]

A quadratic programming problem can show how part movement can be minimized in a flexible manufacturing system with tool flexibility. It is implied in the problem that the tool can perform different operations. It takes into account the combined goal of part movement minimization and workload balancing. Based on several numerical examples, it is evident that less complex loading problems can be solved in reasonable time.

Cost-of-ownership (COO) analysis has started to gain acceptance in the semiconductor industry as a tool for evaluating potential cost and benefit tradeoffs of purchased equipment. However, use of the technique […]

A computer simulation was used to compare TOC, JIT, and traditional manufacturing systems. Four performance measures were considered: average WIP inventory, average flow time, standard deviation of flow time, and total system output.

Manufacturing companies rely on flexible manufacturing systems and strategic marketing information systems to quickly respond to market trends. The increasingly segmented and specialized markets have made mass production and slow information collection techniques obsolete. Computer-integrated manufacturing cuts engineering time by 18 to 30% while improving quality 100 to 400% and boosting productivity 40 to 70%.

The ability of FMS to enhance the competitive position of organizations has been well documented. However, empirical research on the operating characteristics of these systems over an extended period is scarce. In this study, the operating characteristics of three FMSs are reported over a six-year period.

This paper presents results of a study dealing with the design of cellular manufacturing systems using mathematical modelling techniques. A background study was performed to select the best factors used for performance analysis. The selected design methodologies are applied to a numerical example and results are evaluated using quantitative measures of performance. The result of this analysis can assist the decision maker in selecting the best method for manufacturing cell design.

Traditional economic evaluation methods concentrate on maximizing or minimizing a single objective such as net present value and pay back period. In the last decade, there has been an increased awareness of the need to consider multiple attributes in the evaluation of advanced manufacturing systems. Various methods have recently been developed for the evaluation of CIM systems. This paper discusses multiattribute methods for justification of CIM systems and outranking methods including ELECTRE, ORESTE, and PROMETHEE.

The advantages, workability and pitfalls of flexible manufacturing systems (FMS) are discussed. Large-scale, sophisticated implementation of FMS usually not cost-effective. The key is to undertake simple, specific alterations when planning for FMS. Adoption of modular systems approach that utilizes cell control systems that can withstand little or no disturbance when added requirements are engineered in the future., Advances in control technology and a more realistic approach to application are making flexible manufacturing an alternative even in job shops. In the 25 years or so that flexible manufacturing [...]