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논문KCI 등재

사양 기반 설계 복잡도 지수(SDCI)에 기반한 제품 설계 전략 최적화 연구

Optimization of Product Design Strategies Using the Specification-Based Design Complexity Index (SDCI)

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주제분류학제간연구

초록

Purpose: This study aims to systematically address the inherent structural complexity in customized product design processes of small and medium-sized enterprises (SMEs). To achieve this, a Specification-Based Design Complexity Index (SDCI) was developed to quantitatively capture multi-dimensional design complexity. The SDCI allows the early estimation of design complexity levels in similar projects and provides an objective basis for resource allocation and schedule planning, thereby enhancing design quality and productivity. Methods: This study analyzed 297 cases of customized product designs collected from small and medium-sized enterprises (SMEs). The SDCI was developed using eight key variables, including the number of parts, the degree of new development, the frequency of design changes, the degree of customer involvement, and the reusability of design drawings. Each variable was normalized within a [0,1] range, and weights were derived using the Analytic Hierarchy Process (AHP). The SDCI was then calculated using a weighted linear combination of these variables. Results: Empirical analysis confirmed that higher SDCI values were significantly correlated with longer design time and higher cost, demonstrating its effectiveness as a reliable quantitative indicator of design complexity. Moreover, the SDCI facilitated the classification of design approaches into Sequential Engineering Design(SED) and Concurrent Engineering Design (CED), thereby improving the efficiency of resource allocation and project scheduling. Conclusion: The proposed SDCI provides SMEs with a practical decision-making tool for quantitatively evaluating design complexity and optimizing design strategy decisions. Future research should extend the applicability of the SDCI to diverse industries and investigate its statistical associations with performance indicators such as design time, cost, and quality, thereby further strengthening its generalizability and practical utility.

Abstract

Purpose: This study aims to systematically address the inherent structural complexity in customized product design processes of small and medium-sized enterprises (SMEs). To achieve this, a Specification-Based Design Complexity Index (SDCI) was developed to quantitatively capture multi-dimensional design complexity. The SDCI allows the early estimation of design complexity levels in similar projects and provides an objective basis for resource allocation and schedule planning, thereby enhancing design quality and productivity. Methods: This study analyzed 297 cases of customized product designs collected from small and medium-sized enterprises (SMEs). The SDCI was developed using eight key variables, including the number of parts, the degree of new development, the frequency of design changes, the degree of customer involvement, and the reusability of design drawings. Each variable was normalized within a [0,1] range, and weights were derived using the Analytic Hierarchy Process (AHP). The SDCI was then calculated using a weighted linear combination of these variables. Results: Empirical analysis confirmed that higher SDCI values were significantly correlated with longer design time and higher cost, demonstrating its effectiveness as a reliable quantitative indicator of design complexity. Moreover, the SDCI facilitated the classification of design approaches into Sequential Engineering Design(SED) and Concurrent Engineering Design (CED), thereby improving the efficiency of resource allocation and project scheduling. Conclusion: The proposed SDCI provides SMEs with a practical decision-making tool for quantitatively evaluating design complexity and optimizing design strategy decisions. Future research should extend the applicability of the SDCI to diverse industries and investigate its statistical associations with performance indicators such as design time, cost, and quality, thereby further strengthening its generalizability and practical utility.

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