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Abstract
  • Circular-economy targets and emerging regulatory constraints increase the need to assess manufacturability and end-of-life disassembly already in early design, where late discovery of feasibility issues can trigger costly redesign loops. For this purpose, we represent product designs as AND/OR assembly graphs, that encode feasible assembly alternatives. We ask whether constraining product-leveled its on an AND/OR assembly graph and evaluation in a production simulation can target this issue. Toanswer the question, this paper specifies a framework concept for optimizing product configurations with respect to assembly and disassembly. Design edits are restricted to graph-valid operators and further pruned by a manufacturability knowledge graph that encodes admissible substitutions and hardconstraints. Candidate designs are evaluated by a production simulation across assembly and disassembly scenarios, returning a vector of performance indicators. Training uses scalarization of this vector, while full vectors are retained for post-hoc trade-off analysis. We also describe a minimum viable prototype that instantiates a restricted subset of the concept: binary joining-method selection on editable operations with a scheduling-based evaluator and a reinforcement-learning loop.
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