Low volume production layout optimization — An intelligent enabler based model

The manufacturing industry is witnessing an increase in demand for low volume individualized composite products. However, integrating this process intensive composite manufacturing into the traditional materials based production line requires an adaptive and dynamic factory layout planning. Isolated simulation models cannot address the complexities involved in seamless integration of distinct products to existing production lines. Hence, this paper proposes a transformative technology enabled Digital Twin (DT) integrated system that leverages data, based on appropriate level of abstraction to simplify the system. The model leverages a combination of Discrete Event Simulation (DES) and Agent Based Modeling (ABM) to accurately represent a carbon fiber production facility. The proposed model analyzed both independent and correlated variables and identified key enablers that influence layout planning decisions. The integrated model revealed that the Double Diaphragm Preforming workstation experienced $\sim 65 \%$ idle time. The correlated variables led to locating targeted iterations through Pearson’s correlation coefficient analysis and identified strong interdependencies of 0.9967 between press tool and trimming workstations. This novel technique provided insights on machine interactions and optimize complex systems using hybrid simulation and an immersive environment. The proposed framework established flexibility through targeted parameter adjustments and improved responsiveness towards the dynamic production landscape.