Title: Selecting the best operational strategy for job shop system: an ANP approach

Authors: Rishu Sharma; Suresh Garg

Addresses: Department of Mechanical and Automation Engineering, Maharaja Agrasen Institue of Technology, Rohini, Delhi, India ' Department of Mechanical Engineering, Delhi Technological University, Delhi, India

Abstract: The manufacturing industries require efficient after sales service network to solicit customers. Since every vehicle entering service centre has different service and repair needs, it closely resembles job shop system. In the situations of complex decision domain, even an abstract solution of the decision problem is difficult to achieve. For such cases, analytic network process (ANP) is considered as an attractive multi criteria decision making tool. The objective of this paper is to select the best operational strategy in order to improve the performance of the job shop under study using ANP. The results from the study indicates that in order to improve its performance, attention should be given to improve the skills and behaviour of employees; which in turn improves the customer satisfaction leading to the improved business results. A case of automobile after sales service network is taken as an example for illustration of the proposed model.

Keywords: analytical network process; ANP; after sales service; balanced scorecard; BSC; job shop production; JSP; multicriteria decision making; MCDM; employee skills; employee behaviour; automobile industry; automotive after sales.

DOI: 10.1504/IJISE.2015.069544

International Journal of Industrial and Systems Engineering, 2015 Vol.20 No.2, pp.231 - 262

Received: 03 Jul 2013
Accepted: 11 Jul 2013
Published online: 23 May 2015 *

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