Mixed-model and multi-model assembly lines: A systematic literature review on resource management

In modern dynamic manufacturing context, product personalisation, and the production-line customisation it may require, are crucial sources of competitiveness, making mixed-model and multi-model assembly lines indispensable. The variability resulting from both internal and external factors, along with resource flexibility, plays a critical role in these settings. Nonetheless, systematic analyses of how resources are considered in such environments remain limited, particularly about variability and the interactions among different resource types. Thus, this work conducts a Systematic Literature Review, analysing 63 studies on Mixed-Model Assembly Lines (MMALPs) and Multi-Model Assembly Lines (MuMALPs). The review investigates resource characteristics – such as space, operator skills, costs, or equipment availability – and whether and how variability in operating times or market demand is addressed. The review shows that cost and availability are the most frequently examined resource characteristics, while space remains comparatively underexplored. Line design and line balancing stand out as the primary objectives, typically tackled via integer programming or metaheuristics, whereas machine learning – though less common overall – is more often employed under high-variability conditions. The results offer practical insights for both researchers and practitioners by highlighting the current gaps uncovered by these findings and suggesting avenues that would be particularly valuable to explore in light of the results obtained, thereby underscoring the need for more in-depth research on flexible and reconfigurable lines, as well as broader implementation in real-world applications in MMALPs and MuMALPs.