سال انتشار: ۱۳۸۴

محل انتشار: اولین کنفرانس بین المللی و هفتمین کنفرانس ملی مهندسی ساخت و تولید

تعداد صفحات: ۱۰

نویسنده(ها):

A Azadeh – Department of Industrial Engineering and ResearchInstitute of Energy Management andPlanningFaculty of Engineering, University of Tehran, Iran
A Vazifeh – Department of Telecommunications, A. James ClarkSchool of Engineering, University of Maryland,CollegePark, MD-USA
H Izadbakhsh – Department of Industrial Engineering and Research Institute of Energy Management and Planning Faculty of Engineering, University of Tehran, P.O. Organizations and Methods Bureau Iranian Railways Company, Tehran, I.R. Iran
A Bukhari – Department of Telecommunications, A. James Clark School of Engineering, University of Maryland,College Park, MD-USA

چکیده:

This paper presents a framework for solving plant layout design problem. The integrated approach discussed in this paper is based on multivariate and multiattribute analysis. Layout design often has a significant impact on the performance of a manufacturing or service industry system and is usually a multiple objective problem. This paper proposes an integrated analytic hierarchy process (AHP) and principal component analysis (PCA) approach to solve a plant layout design problem. A computer-aided layout-planning tool was used to generate a considerable numbers of layout alternatives. The qualitative performance measures were weighted by AHP. PCA was then used to solve the multiple-objective layout problem. An example illustrated the effectiveness of the proposed methodology. The validity of the model is verified and validated by numerical taxonomy (NT) approach. Furthermore, a nonparametric correlation method, namely, Spearman correlation experiment shows high level of correlation between the findings of PCA and NT. The results of such studies would help policy makers and top managers to have better understanding and improve existing systems with respect to facility layout performance. The results of PCA AHP have been compared with a previous study which considersDEA and AHP approach. Furthermore, the PCA AHP approach presents more useful and exact results.