Integrating data envelopment analysis and analytic hierarchy for the facility layout design in manufacturing systems


Ertay T., Ruan D., Tuzkaya U. R.

INFORMATION SCIENCES, cilt.176, ss.237-262, 2006 (SCI İndekslerine Giren Dergi)

  • Cilt numarası: 176 Konu: 3
  • Basım Tarihi: 2006
  • Doi Numarası: 10.1016/j.ins.2004.12.001
  • Dergi Adı: INFORMATION SCIENCES
  • Sayfa Sayısı: ss.237-262

Özet

Facility layout design (FLD) has a very important effect on the performance of a manufacturing system. The concept of FLD is usually considered as a multiobjective problem. For this reason, a layout generation and its evaluation are often challenging and time consuming due to their inherent multiple objectives in nature and their data collection process. In addition, an effective facility layout evaluation procedure necessitates the consideration of qualitative criteria, e.g., flexibility in volume and variety and quality related to the product and production, as well as quantitative criteria such as material handling cost, adjacency score, shape ratio, and material handling vehicle Utilization in the decision process. This paper presents a decision-making methodology based oil data envelopment analysis (DEA), which uses both quantitative and qualitative criteria, for evaluating FLD. The criteria that are to be minimized are viewed as inputs whereas the criteria to be maximized are considered as Outputs. A computer-aided layout-planning tool, VisFactory), is adopted to facilitate the layout alternative design process as well as to collect quantitative data by using exact and vague data by means of fuzzy set theory. Analytic hierarchy process (AHP) is then applied to collect qualitative data related to quality and flexibility. The DEA methodology is used to solve the layout design problem by simultaneously considering both the quantitative and qualitative data. The purposed integrated procedure is applied to a real data set of a case study, which consists of 19 FLDs provided of the plastic profile production system. (c) 2004 Elsevier Inc. All rights reserved.