Manufacturing System Selection Using FuzzyAHP

Issue: Vol.7 No.1

Authors:

Shashi Kant (Manav Rachna International University, Faridabad)

Keywords: JIT, KANBAN, CONWIP, HYBRID, FUZZY-AHP.

Abstract:

 

A multistage, serial, unreliable manufacturing systemunder JIT environment has been considered here. JIT policy involves three important pull production systems i.e. KANBAN, CONWIP and Hybrid manufacturing systems. The present paper demonstrates the brief introduction about the three JIT techniques and application of FUZZY-AHP method to select the best possible manufacturing systems. WIP inventory, Service Level, Throughput, Lost Demand, Total Cost, Utilization of Machine and Utilization of Buffer are the chosen criteria to select the best policy.

References:

[1] Boroushaki, S. and Malczewski J., (2008), Implementing an extension of AHP using OWA operators with FUZZY quantifiers in ArcGIS, Computers and Geosciences 34, 399- 410.

[2] Chan F.T.S., (2001), Effect of KANBAN size on JIT manufacturing system, Journal of Materials Processing Technology 116. 146-160.

[3] Duri C., Frein Y. and Lee H.S., (2000), Performance evaluation and Design of a CONWIP system with Inspection, Int. Journal of Production Economics 64. 219- 229.

[4] Ghamari Y.K. (2006), Analyzing KANBAN and CONWIP controlled assembly systems, University of Tsukuba.

[5] Ghamari Y.K., Sato Ryo (2008), A Performance Evaluation of KANBAN, CONWIP and Base-stock in Serial Production Lines, Discussion Paper Series No.1202, Department of Social Systems and Management, University of Tsukuba, Japan.

[6] Hossein Cheraghi S., Mohammad Dadashzadeh, Mahesh Soppin (2008), Comparative Analysis of Production Control Systems through Simulation, Journal of Business & Economics Research –Volume 6, Number 587.

[7] Huang Min, Wang D. and Ip W.H., (1998), Simulation Study of CONWIP for a cold rolling plant, Int. J. of Production Economics, 54, 257-266.

[8] Ju-Hua Mo, Huang Min and Wang Xing Wei, (2008), The combination of Push and FUZZY Logic Control for the production control of a General Serial Line, 5th International conference on FUZZY systems and Knowledge Discovery, Journal of Computer Society, 648-653.

[9] Ovalle, O.R &Marquez A.C., (2003), Exploring the Utilization of CONWIP system for SCM & a comparison with fully integrated SCM, Int. J. of Production Economics, 83, 195-215.

[10] Saaty, Thomas L. (1970),The Analytical Hierarchy Process. University of Pittsburgh, Pittsburgh.

[11] Sari Ahmet, (2004), Literature Review Project: Applicability of JIT in service environments, Research and Development Methodology, PAFIS-2004.

[12] Sarker, B.R. & Balan C.V., (1999), Operation planning for multi-stage KANBAN system, European Journal of Operational Research, 112. 284-303.

[13] Shahabudeen P., Gopinath R. and Krishnaiah K., (2002), Design of Bi-Criteria KANBAN System using Simulated Annealing Technique, Journal of Computers and Industrial Engineering, 41, 355-370.

[14] Sharma Sanjay,Agrawal Narayan (2009), Selection of a Pull Production Control Policy under Different Demand Situations for a Manufacturing System by AHP-Algorithm” Computers and Operations Research, 36(5), 1622-1632.

[15] Sharma Sanjay, Agrawal Narayan (2011),Application of FUZZY-Techniques in a Multistage Manufacturing System” The International Journal of Advance Manufacturing Technology,DOI 10.1007/s00170-011- 3607-9.