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Integration of Multi-Criteria Decision-Making and Dimensional Entropy Minimization in Furniture Design
Multi-criteria decision analysis (MCDA) in furniture design is challenged by increasing product complexity and component proliferation. This study introduces a novel framework that integrates entropy reduction—achieved through dimensional standardization and modularity—as a core factor in the MCDA methodologies. The framework addresses both individual furniture evaluation and product family optimization through systematic complexity reduction. The research employed a two-phase methodology. First, a comparative analysis evaluated two furniture variants (laminated particleboard versus oak wood) using the Weighted Sum Model (WSM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The divergent rankings produced by these methods revealed inherent evaluation ambiguities stemming from their distinct mathematical foundations, highlighting the need for additional decision criteria. Building on these findings, the study further examined ten furniture variants, identifying the potential to transform their individual components into universal components, applicable across various furniture variants (or configurations) in a furniture line. The proposed dimensional modifications enhance modularity and interoperability within product lines, simplifying design processes, production, warehousing logistics, product servicing, and liquidation at end of lifetime. The integration of entropy reduction as a quantifiable criterion within MCDA represents a significant methodological advancement. By prioritizing dimensional standardization and modularity, the framework reduces component variety while maintaining design flexibility. This approach offers furniture manufacturers a systematic method for balancing product diversity with operational efficiency, addressing a critical gap in current design evaluation practices.