Taho Yang

The use of grey relational analysis in solving multiple attribute decision-making problems

There are many cases in daily life and in the workplace which pose a decision problem. Some of them involve picking the best from among multiple available alternatives. However, no single alternative works best for all performance attributes. This research proposes a multiple attribute decision making (MADM) method, grey relational analysis (GRA), for solving this kind of problem. Two cases, facility layout and dispatching rules selection problem, which have been analyzed by data envelopment analysis (DEA), were also analyzed using the GRA procedure, in order to illustrate the use of GRA. In the case of the facility layout problem, 18 alternative layouts and 6 performance attributes were considered. In the case of the problem of selecting dispatching rules, 9 alternatives dispatching rules and 7 performance attributes were considered. For the two cases examined, the results of comparisons show that GRA is efficient for solving MADM problem.

A hierarchical AHP/DEA methodology for the facilities layout design problem

Abstract Layout design often has a significant impact on the performance of a manufacturing or service industry system and is usually a multiple-objective problem. Neither an algorithmic nor a procedural layout design methodology is usually effective in solving a practical design problem. This paper proposed a hierarchical analytic hierarchy process (AHP) and data envelopment analysis (DEA) approach to solve a plant layout design problem. A computer-aided layout-planning tool was used to generate a considerable numbers of layout alternatives as well as to generate quantitative decision-making unit (DMU) outputs. The qualitative performance measures were weighted by AHP. DEA was then used to solve the multiple-objective layout problem. Empirical illustrations from a practical case study illustrated the effectiveness of the proposed methodology.

Solving a multiresponse simulation-optimization problem with discrete variables using a multiple-attribute decision-making method

The simulation model is a proven tool in solving nonlinear and stochastic problems and allows examination of the likely behavior of a proposed manufacturing system under selected conditions. However, it does not provide a method for optimization. A practical problem often embodies many characteristics of a multiresponse optimization problem. The present paper proposes to solve the multiresponse simulation-optimization problem by a multiple-attribute decision-making method-a technique for order preference by similarity to ideal solution (TOPSIS). The method assumes that the control factors have discrete values and that each control factor has exactly three control levels. Taguchi quality-loss functions are adapted to model the factor mean and variance effects. TOPSIS is then used to find the surrogate objective function for the multiple responses. The present paper predicts the system performances for any combination of levels of the control factors by using the main effects of the control factors according to the principles of a robust design method. The optimal design can then be obtained. A practical case study from an integrated-circuit packaging company illustrates the efficiency and effectiveness of the proposed method. Finally, constraints of the proposed method are addressed.

Flexible machine layout design for dynamic and uncertain production environments

Flexible manufacturing systems operate in a dynamic environment and face considerable uncertainty in production demands. The development of a flexible machine layout is a critical issue in creating a system that can respond effectively to these requirements. Unlike most existing methods for creating flexible layout designs, the procedure developed in this paper is not restricted to equal size machines. It optimizes the trade-offs between increased material handling costs as requirements change and machine rearrangement costs needed to adapt the layout to these changes. The proposed flexible machine layout design procedure formulates and solves a robust machine layout design problem over a rolling horizon planning time window. The formulation, details of the solution methodology, illustrative examples, and computational results are presented.

Integrated facility layout and material handling system design in semiconductor fabrication facilities

Semiconductor manufacturing is an important component of the U.S. manufacturing industry. Most of todays fabrication facilities and those being designed for the near future use a bay layout configuration and an overhead monorail system for moving material between bays. These material handling systems are usually designed with a spine or perimeter type of configuration. This paper investigates the layout and material handling system design integration problem in semiconductor fabrication facilities and proposes a methodology for solving this integrated design problem. A spacefilling curve approach is used to address the facility layout, while the structure of the spine and perimeter configurations are exploited to create a network flow problem to determine the material handling system design. Computational results are presented and show exceptional promise for this procedure in solving the integrated design problem in a semiconductor manufacturing environment.

A genetic algorithm for facility layout design in flexible manufacturing systems

The flexible manufacturing system (FMS) facility layout problem (FLP) involves the positioning of cells within a given area so as to minimize the material flow costs between cells. The FLP design includes specifying the spatial coordinates of each cell, the orientation of each cell in either a horizontal or vertical position, and the position of each cells pickup and dropoff points. The layout design problem is both tactically and strategically important since the layout plays a large role in determining the efficiency and flexibility of the system. The FMS layout problem differs from traditional layout problems in that there are additional constraints on a cells shape and orientation and the location of the pickup/ dropoff points must be determined. A mixed integer programming formulation for the FLP developed by Das (1993) is adapted and heuristically solved in this paper. Because of the NP-hard nature of the solution space, a genetic algorithm based decomposition strategy is proposed and computationa...

Six-Sigma project selection using national quality award criteria and Delphi fuzzy multiple criteria decision-making method

Six-Sigma is a tool of significant value in achieving operational excellence. The project selection decision is the early stage of implementation for a Six-Sigma intervention. The present study proposes national quality award criteria as the Six-Sigma project selection criteria, and proposes a hierarchical criteria evaluation process. The strategic criteria are evaluated by the management team using a fuzzy multiple criteria decision-making method. The sub-criteria which contain additional operational issues are evaluated by the Six-Sigma Champion. The proposed methodology is successfully applied in solving the project selection problem deriving from a component manufacturer. The results show that the higher a projects priority is, the greater the financial gains will be on completion of the project. Accordingly, the proposed methodology can prioritize the financial gain - which is the key performance indicator for a Six-Sigma project.

A neural-network approach for semiconductor wafer post-sawing inspection

Semiconductor wafer post-sawing requires full inspection to assure defect-free outgoing dies. A defect problem is usually identified through visual judgment by the aid of a scanning electron microscope. By this means, potential misjudgment may be introduced into the inspection process due to human fatigue. In addition, the full inspection process can incur significant personnel costs. This research proposed a neural-network approach for semiconductor wafer post-sawing inspection. Three types of neural networks: backpropagation, radial basis function network, and learning vector quantization, were proposed and tested. The inspection time by the proposed approach was less than one second per die, which is efficient enough for a practical application purpose. The pros and cons for the proposed methodology in comparison with two other inspection methods, visual inspection and feature extraction inspection, are discussed. Empirical results showed promise for the proposed approach to solve real-world applications. Finally, we proposed a neural-network-based automatic inspection system framework as future research opportunities.

Systematic layout planning: a study on semiconductor wafer fabrication facilities

This paper proposes to use Muther’s systematic layout planning procedure as the infrastructure to solve a fab layout design problem. A multiple objective decision making tool, analytic hierarchy process, is then proposed to evaluate the design alternatives. The proposed procedure is illustrated to be a viable approach for solving a fab layout design problem through a real‐world case study. It features both the simplicity of the design process and the objectivity of the multiple‐criteria evaluation process as opposed to existing solution methodologies.

Evaluating the supply chain performance of IT-based inter-enterprise collaboration

With the use of IT, the nature of business processes has changed from intra- to cross-enterprise. This has significantly altered enterprise interactions with suppliers and customers. Collaboration is essential for successful supply chain performance. In recent years a variety of initiatives have been adopted by industries. These attempted to create efficiency and effectiveness through integration of the activities and processes. However, enterprises can only gain significant benefits by mass collaboration. Collaborative Planning, Forecasting and Replenishment (CPFR), which result in deeper partnerships, have become an important factor in supply chains. We investigated the performance of CPFR; it possesses formalized guidelines and is a relatively new initiative. By using simulation, we investigated four CPFR alternatives that are used in the adoption of collaboration strategies in industries. Retailers have traditionally played the hub role in supply chains in order to reduce the bullwhip effect, but our simulation confirmed that shifting the retailer (buyer-driven) collaboration to a manufacturer (supplier-driven) approach was a more viable option.