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Enhancing Industrial Design Competitiveness: Research and Application of a Machine Tool Industrial Design Decision-Making Method Based on Product Family Architecture and Systematic Evaluation

This study employs an innovative industrial design decision-making approach based on the notion of product family architecture and structural equation modeling. The aim is to enhance the product competitiveness of machine tool enterprises, which is crucial for their development. Key domains within m...

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Bibliographic Details
Published in:Applied sciences 2023-11, Vol.13 (21), p.11831
Main Authors: Yao, Zhiwei, Wu, Xumin, Wu, Yu, Wen, Xintong
Format: Article
Language:English
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Summary:This study employs an innovative industrial design decision-making approach based on the notion of product family architecture and structural equation modeling. The aim is to enhance the product competitiveness of machine tool enterprises, which is crucial for their development. Key domains within machine tool industrial design were systematically analyzed, leading to the creation of a design evaluation criteria system. Through quantitative data, the importance order of indicators at all levels was determined to enhance the overall competitiveness of product industrial design. First, teachers of relevant majors and professionals from machine tool companies completed a Likert scale questionnaire to validate the PFA-SEM hypothesis model. Next, a subjective–objective integrated weighting method was introduced to guide the ranking of multiple design elements. The feasibility of this method was confirmed by applying the Entropy-Based Multi-Objective Decision-Making Method (Technique for Order Preference by Similarity to Ideal Solution). These approaches helped achieve industrial design improvements in Heatking induction vertical hardening machines. This research aids in optimizing machine tool design, guiding design iterations, and serving as a reference for the development and optimization of other machine tool design solutions.
ISSN:2076-3417
2076-3417
DOI:10.3390/app132111831