THE ROLE OF CALIBRATION ENGINEERING IN STRENGTHENING RELIABILITY OF U.S. ADVANCED MANUFACTURING SYSTEMS THROUGH ARTIFICIAL INTELLIGENCE

Abstract

This research addresses a persistent problem in advanced manufacturing: AI initiatives promise higher availability, yield, and effective capacity, yet their realized impact is constrained when the underlying measurement systems are weakly calibrated and uncertainty is not governed. The purpose is to quantify how AI-enabled calibration engineering relates to plant-level reliability and to specify the organizational and data conditions under which benefits materialize. We adopt a quantitative cross-sectional, case-based design spanning eight U.S. enterprise manufacturing cases and associated cloud and on-premise operational data sources, combining a structured survey of operations stakeholders with de-identified archival KPIs. The sample includes 402 respondents nested within sites and linked to CMMS, production counters, calibration certificates, GR&R summaries, and historian records. Key variables include an AI-Enabled Calibration Practices index capturing predictive interval setting, automated drift detection, AI-assisted GR&R, digital-twin utilization, and alerting workflows; moderators for data quality, operator training, and equipment age; and reliability outcomes constructed from MTBF, MTTR, availability, OEE, FPY, and DPPM. The analysis plan specifies descriptive profiling, correlation matrices, and multiple linear regressions with robust errors and site fixed effects, plus moderation tests and sensitivity checks. Headline findings show a positive association between AI-enabled calibration practices and reliability that strengthens when data quality and training are higher and attenuates as fleets age. Implications for managers are to institutionalize calibration metadata and uncertainty budgets as machine-readable context, enforce ingestion gates for decision-grade data, and stage capability building that pairs metrology governance with targeted training. A targeted literature review of 47 peer-reviewed studies substantiates the constructs and methods employed.