Title: Development of a sustainable manufacturing strategy using analytic network process

Authors: Lanndon A. Ocampo; Michael Angelo B. Promentilla

Addresses: Department of Mechanical and Manufacturing Engineering, University of San Carlos, 6000 Cebu City, Philippines ' Department of Chemical Engineering, De La Salle University, 2401 Taft Avenue, 1004 Manila, Philippines

Abstract: This work explores the implementation of analytic network process (ANP) in developing a sustainable manufacturing strategy. Previous works fell short of addressing the need of developing a manufacturing strategy that simultaneously incorporates the demands of sustainability. Manufacturing strategy and sustainable manufacturing has been approached in the literature as two different concepts with having limited works done that holistically incorporate them. Thus, a proposed problem structure is developed that attempts to integrate these two concepts. The key aspect of the proposed framework is the explicit incorporation of stakeholders' interests in the strategy development process. Due to the number of decision components and their inherent relationships that must be simultaneously addressed in developing a sustainable manufacturing strategy, ANP is used in this work. This work is aimed at: 1) identifying the content of a sustainable manufacturing strategy that integrates sustainability and classical manufacturing strategy; 2) demonstrating the applicability of ANP in the complex manufacturing strategy formulation process. A Monte Carlo simulation is also implemented to check the robustness of the ANP results. Managerial insights and future work were also discussed.

Keywords: analytical network process; ANP; sustainability; manufacturing strategy; sustainable manufacturing; sustainable development; stakeholder interests; Monte Carlo simulation.

DOI: 10.1504/IJBSR.2016.075744

International Journal of Business and Systems Research, 2016 Vol.10 No.2/3/4, pp.262 - 290

Received: 02 Jan 2015
Accepted: 14 Oct 2015

Published online: 01 Apr 2016 *

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