A simulation-based fuzzy analytic network process approach in developing sustainable manufacturing strategy

• Main Authors: Ocampo, Lanndon, Clark, Eppie
• Format: text
• Published: Animo Repository 2015
• Subjects: Sustainability; Industrial ecology; Multiple criteria decision making; Business Administration, Management, and Operations
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1683; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2682/type/native/viewcontent
• Institution: De La Salle University

This paper adopts a probabilistic fuzzy analytic network process (PROFUZANP) approach in developing a sustainable manufacturing strategy. In this hybrid method, analytic network process handles the complexity of the problem structure under consideration, fuzzy set theory is used to describe vagueness in individual decision-making and probability theory is used to handle randomness in group decision-making. This holistic methodological approach addresses complexity and uncertainty both in individual and group decision-making which is useful in modeling group decisions such as developing a sustainable manufacturing strategy. In this work, an inclusive approach of integrating traditional manufacturing strategy concepts and sustainable manufacturing principles is proposed as a unifying decision model. The proposed decision structure adopts the hierarchical structure of manufacturing strategy and explores the presence of strategic responses and stakeholders' interests as significant components of sustainability. Using PROFUZANP, the decision model identifies the content policies of sustainable manufacturing strategy. This content strategy is expected to address both competitiveness and sustainability of manufacturing firms. Results are reported in this paper along with insights and future work. The contribution of this work is the integration of manufacturing strategy and sustainability into a coherent decision framework that requires the use of PROFUZANP in dealing with complex and uncertain group decision-making problem.