• 품질경영학회지
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• 제48권1호
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• pp.51-68
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• 2020

Purpose: The primary objective of this research is to develop the optimal operating conditions as well as their associated design spaces for a Cryogenic Submerged Arc Welding(SAW) process by improving its quality and productivity simultaneously. Methods: In order to investigate functional relationships among quality characteristics and their associated control factors of an SAW process, a stepwise design of experiment(DoE) method is proposed in this paper. Based on the DoE results, not only a multi-dimensional design space but also a safe operating space and normal acceptable range(NAR) by integrating statistical confidence intervals were demonstrated. In addition, the optimal operating conditions within the proposed NAR can be obtained by a robust optimal design method. Results: This study provides a customized stepwise DoE method (i.e., a sequential set of DoE such as a factorial design and a central composite design) for Cryogenic SAW process and its statistical analysis results. DoE results can then provide both the main and interaction effects of input control factors and the functional relationships between the input factors and their associated output responses. Maximizing both the product quality with high impact strength and the productivity with minimum processing times simultaneously in a case study, we proposed a design space which can provide both acceptable productivity and quality levels and NARs of input control factors. In order to confirm the optimal factor settings and the proposed NARs, validation experiments were performed. Conclusion: This research may provide significant contributions and applications to many SAW problems by preparing a standardization of the functional relationship between the input factors and their associated output response. Moreover, the proposed design space based on DoE and NAR methods can simultaneously consider a number of quality characteristics including tradeoff between productivity and quality levels.

• 디지털융복합연구
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• 제12권5호
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• pp.125-130
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• 2014

오늘날의 글로벌 시장에서의 경쟁은 많은 회사들이 시장에서 충분한 다양성을 가진 product family를 개발하도록 하고 있다. Product family를 설계할 때 중요한 이슈 중에 하나는 제품의 공통성과 차별성간의 절충점을 찾아내는 것이다, 이와 동시에 Product family를 설계할 때 리드타임을 단축시키고, 품질을 향상시키며 비용을 절감하는 것뿐만 아니라 제품의 환경 성능을 고려하는 것도 필요하다. 본 연구에서는 환경성을 고려한 메타 휴리스틱 알고리즘 기반의 그린 Product Family 재설계 방법론을 제안한다. 제안하는 방법은 그린 product family의 설계를 위해 메타휴리스틱 알고리즘으로써 유전자 알고리즘과 green product family index (GPFI)를 이용한다. 추가적으로 product family 레벨과 부품 레벨의 product family 재설계 추천방안도 제시하였다. 본 연구에서는 테이블 램프 product family를 대상으로 제안한 방법의 효율성과 타당성을 검증하였다.