A Priority-Rule-Based Approach for the Dynamic Control of Reassembly in Matrix-Remanufacturing Systems

Remanufacturing is confronted with a high degree of inherent uncertainty, particularly during core disassembly. Variability in disassembly propagates into reassembly as parts arrive unpredictably, due to task failures or damaged components, yielding a dynamically changing pool of parts that defies fixed planning. Moreover, individual components may be compatible with multiple final-product variants, vastly expanding the matching possibilities. As a result, during reassembly, unpredictably arriving components have to be dynamically allocated into reassembly sequences and station assignments, as fixed planning is infeasible. The aim of this paper is to design and assess a priority-rule-based control approach for dynamic reassembly in matrix-remanufacturing systems facing uncertain component availability. The production control evaluates incoming components to form feasible pairs and determine the reassembly sequence, while an allocation agent assigns these pairs to workstations. We compare a suite of domain-specific priority rules and introduce a novel reassembly-specific priority rule via discrete-event simulation across scenarios of increasing variant and layout complexity, assessing their impact on throughput, work-in-progress, and station utilisation. Results show that the selection of priority rules had a significant effect on both performance and system stability. Results indicate that the reassembly-specific priority rule increasingly outperforms the conventional one as complexity rises. Nonlinear interactions between matching and allocation decisions become more pronounced as variant diversity and system complexity grow. By focusing on the interplay between uncertain disassembly outcomes and dynamic reassembly, the paper addresses a previously relatively unexplored problem statement in remanufacturing.