Multi-Criteria Decision Support for Smart Manufacturing Innovation Ecosystems Toward Industry 6.0 - Saputra, Dhanar Intan Surya; Sutiksno, Dian Utami; Rahim, Robbi (JINAV: Journal of Information and Visualization, 2026)
The transition towards Industry 6.0 demands the evolution of intelligent manufacturing systems beyond automation and digitalization towards integrated, human-centric, and resilient innovation ecosystems. The assessment of ecosystem readiness in the face of such complexity is essentially a multi-criteria decision problem with conflicting objectives and structural risk constraints. This study proposes a non-compensatory multi-criteria decision support system using the ELECTRE method to evaluate the readiness of Smart Manufacturing Innovation Ecosystems in Indonesia. Seven industry 6.0-oriented criteria are considered, including technology infrastructure readiness, digital connectivity, human capital capability, sustainability, governance, cybersecurity, and investment costs. The structured decision matrix is normalized, weighted, and processed using concordance-discordance analysis to obtain an outranking dominance relationship between the decision alternatives. The results show that ecosystem readiness varies, with regions with balanced digital, governance, and cybersecurity readiness exhibiting structural dominance, while regions with lower digital readiness but lower investment costs are vetoed due to non-compensatory decision rules. Sensitivity analysis shows that the ranking of decision alternatives remains robust with moderate weight/threshold changes. The ELECTRE-based non-compensatory decision approach is more appropriate than compensatory approaches in evaluating strategic industrial constraints pertinent to the industry 6.0 transition. The study’s contribution is the operationalization of industry 6.0 principles within a decision support system framework, providing policy-relevant prioritization results pertinent to the smart manufacturing development strategy in Indonesia.