Building Resilient Supply Chains in Constrained Environments: A Socio-Technical Systems Approach to APS Implementation in Iranian Advanced Industries

Operational resilience in politically and economically constrained environments requires a paradigm shift from reactive contingency planning to proactive, intelligence-driven supply chain design. Grounded in Socio-Technical Systems (STS) theory, this longitudinal action research study investigates the design and implementation of a bespoke Advanced Planning and Scheduling (APS) system within two flagship Iranian advanced industries: automotive (Iran Khodro - IKCO) and aerospace (Iran Aerospace Industries Organization - IAIO). The implemented framework integrates a dynamic, multi-attribute Risk-Weighted Supplier Database (RWSDB)—formalized through a Multi-Criteria Decision Analysis (MCDA) model—with a finite-capacity scheduling engine. This creates a co-adaptive system where social (organizational learning, incentive structures) and technical (algorithms, data architecture) elements evolve synergistically. Over a ۲۴-month implementation period, we employed a mixed-methods approach. Results indicate statistically significant improvements: a ۲۸% reduction in raw material inventory (p < ۰.۰۱), a ۳۱% increase in supplier on-time delivery, and a ۱۷% rise in Overall Equipment Effectiveness (OEE). A detailed case study on microcontroller unit (MCU) sourcing demonstrates how the RWSDB quantifies risk to guide decisions, showing that the lowest-priced supplier can exhibit a ۱۰۲۸% higher risk-adjusted total cost than a more reliable alternative. The study concludes that technological success is contingent upon parallel changes in performance metrics, skills, and culture, providing a replicable model for industrial resilience in similarly constrained economies.

کلیدواژه ها:

Socio-Technical Systems Theory ، Advanced Planning and Scheduling (APS) ، Supply Chain Resilience ، Multi-Criteria Decision Analysis (MCDA) ، Iranian Industry ، Sanctions.