Sustainability Analysis in an Automobile Industry Using ISM and Micmac Analysis

Abstract

In the automotive industry, sustainable manufacturing involves integrating the triple bottom line of economic, environmental, and social aspects into manufacturing operations. However, the automotive industry faces challenges in prioritizing sustainability due to its interdependence and complexity, where effective decision-making requires identifying influential factors and understanding their relationship. To address the challenge, a hybrid method combining Interpretive Structural Modeling (ISM) and MICMAC analysis is utilized. ISM establishes connections between specific criteria, enabling a comprehensive understanding of their interdependencies. MICMAC analysis then helps the prioritization process by classifying factors according to their driving and dependency power. This approach helps stakeholders identify the most crucial factors and develop action plans to reduce or eliminate obstacles hindering
the adoption of sustainable manufacturing practices. This study addresses the sustainability issues in the automotive sector in Kerala, India. Furthermore, the study suggests the potential expansion by conducting a large-scale survey to include additional criteria, thereby enhancing the understanding of sustainable practices in the automotive sector. The results indicate the proposed ISM MICMAC model outperforms existing methods in several areas, including accuracy of prioritization (92.5% vs. 70% for AHP), resource efficiency (85% vs. 60% for Carbon Footprint Analysis), emission reduction (30% vs. 20% for LCA), and stakeholder engagement (85% vs. 80% for LCA).