인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Previous studies on the Cost of Quality (COQ) have focused on direct costs, employing prevention, appraisal, and failure costs (PAF). However, the advent of ISO 9001–2015] edition underscores the importance of the risk approach in quality management, necessitating the inclusion of project risks in COQ calculation. This paper introduces a prototype Fuzzy Expert System (FES) model tailored for determining optimal COQ in commercial projects while accounting for project risks. Using the means of the Prevention - Appraisal - Failure model and utilizing data gathered from prior research and validated through official questionnaires and interviews, this study assigns weights to quality risks and allocates them to respective COQ components. Risks such as inadequate planning, coordination issues, construction errors, and delays are identified as influential factors affecting COQ. Our findings suggest that COQ in commercial projects typically amounts to approximately five percent of the project budget. Validation of the prototype Fuzzy Expert System achieved through application to five actual cases (including two for system familiarization and three for validation), demonstrates an accuracy rate of 95%. The prototype Fuzzy Expert System emerges as a valuable tool for COQ evaluation, serving as a reliable checkpoint for individuals with varying levels of expertise in the field.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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