This study empirically examines how inspection automation maturity is associated with quality performance and operational burden in high-reliability aerospace and defense supply chains. In this study, high-reliability aerospace and defense supply chains are defined as supplier-side manufacturing, inspection, and quality-assurance processes for aerospace and defense-related parts, assemblies, and special processes, rather than the entire distribution or sales chain. Using 88 valid survey responses from personnel involved in quality, inspection, production, and IT/system-related tasks, this study operationalized inspection automation maturity as a formative composite index (X_AUTO) and as four component-level variables: automated or semi-automated inspection equipment use (E1), algorithm- or model-based judgment (E2), reduced dependence on manual judgment through reverse coding (E3_REV), and lead-time reduction attributable to automation at the inspection-activity level (E4). The dependent variables were lead-time burden (Y_LT), cost burden (Y_COST), and defect escape (Y_ESCAPE_ORD). Descriptive statistics, correlation analysis, mean comparison by automation level, standardized OLS regression, ordinal logistic robustness analysis for the ordinal defect-escape variable, Harman's single-factor test, and sensitivity analyses were conducted. Additional sensitivity analyses compared the four-component index with an alternative three-component index excluding E4, and model stability was assessed using 5,000 bootstrap resamples and repeated 10-fold cross-validation. The negative association with defect escape remained significant when E4 was excluded (β = - .996, p < .001; bootstrap 95% CI [-1.262, -0.808]), and cross-validated Q² values were positive across all models. The results show that the composite automation maturity index was negatively associated with defect escape, while it was positively associated with lead-time and cost burdens. Ordinal logistic regression produced a consistent negative association between X_AUTO and defect escape. At the component level, reduced dependence on manual judgment showed the most robust negative association with defect escape; however, this result should be interpreted cautiously because E3_REV was measured using a single reverse-coded item. These findings suggest that inspection automation in high-reliability supply chains should be understood as a combined process involving equipment-based data acquisition, algorithm-assisted judgment, standardized decision criteria, reduced dependence on manual judgment, and interorganizational integration of digital inspection data.

1. 서 론
2. 연구방법
    2.1 연구설계 및 개념적 연구모형
    2.2 자료 및 표본
    2.3 변수의 조작적 정의
    2.4 자료 전처리 및 통계분석 절차
    2.5 분석상 유의점
3. 결과
    3.1 표본 특성 및 자료 선별 결과
    3.2 주요 변수의 기술통계 및 상관분석
    3.3 검사자동화 수준별 주요 결과변수 평균 차이
    3.4 검사자동화 성숙도와 품질성과 및 운영부담에대한 회귀분석
    3.5 강건성 및 민감도 분석
4. 논의
    4.1 검사자동화 성숙도와 품질성과․운영부담의관련성
    4.2 자동화 구성요소별 차별적 관련성
    4.3 결함 유출 감소에서 수동판정 의존도 감소의의미
    4.4 공급망 맥락과 운영부담의 해석
    4.5 이론적 및 실무적 시사점
    4.6 연구의 한계와 향후 연구 방향
5. 결론
References

• Hong-Tae Kim(Department of Advanced Convergence in Aerospace and Defense, Hanbat National University) | 김홍태 (국립한밭대학교 우주국방첨단융합학과)
• Geon-Hee Kim(Department of Advanced Convergence in Aerospace and Defense, Hanbat National University) | 김건희 (국립한밭대학교 우주국방첨단융합학과)
• Byung-Chan Min(Department of Industrial and Management Engineering, Hanbat National University) | 민병찬 (국립한밭대학교 산업경영공학과) Corresponding author