The development of semi-automated assembly systems that are capable of accommodating heterogeneous operations remains challenging when equipment standardisation must coexist with task-specific functional requirements. This study proposes a requirement-driven engineering methodology that systematically distinguishes reusable workstation infrastructure from operation-specific technological modules, integrating industrial requirements, assembly-process decomposition, modular architecture definition, mechanical design, structural verification, process monitoring, and functional verification. The methodology is demonstrated through the engineering and physical implementation of three heterogeneous workstation configurations for automotive electric-motor assembly, involving bearing press-fitting, housing and retaining-ring installation, and operator-assisted fastening and printed circuit board assembly. Under a prescribed reference load of 1000 N and the adopted finite element modelling assumptions, numerical verification of the critical pressing support yielded a maximum von Mises stress of 130.6 MPa and a maximum displacement of 0.036 mm, corresponding to a calculated stress safety factor of 6.29 and a displacement compliance ratio of 13.89 relative to the specified acceptance criteria. These results establish numerical compliance of the analysed component under the considered loading conditions but do not constitute experimental validation of the complete production system. The principal engineering contribution lies in establishing a traceable methodology for translating heterogeneous assembly requirements into a common physical architecture while retaining operation-specific functionality. By supporting the reuse of structural and infrastructural solutions, systematic module integration, and requirement-based verification, the proposed approach provides a transferable engineering basis for developing semi-automated assembly workstations without requiring each configuration to be designed as an independent machine.
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Silva et al. (2026) studied this question.
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