Design and Simulation of Sustainable Calibration Systems for Future Industrial Engineering Applications

Abstract

This study examined the design and simulation implications of sustainable calibration systems by quantitatively analyzing the role of digital calibration information flow within industrial engineering contexts. Using archival operational data from 1,620 calibration events, the analysis evaluated how certificate digitization, interoperability, data integrity controls, and automation intensity influenced key performance outcomes. Descriptive results showed an average certificate verification time of 1.84 hours, with rework due to missing data occurring in 7.8% of calibration events and record mismatch rates averaging 2.9%. Multiple regression analyses demonstrated that digital information flow variables explained a substantial proportion of variance in operational performance, with adjusted R² values ranging from 0.46 to 0.58 across models. Higher levels of automation intensity and certificate digitization were associated with significant reductions in verification time (β = −0.45, p < .001), rework frequency (β = −0.36, p < .001), and downtime exposure (β = −0.42, p < .001). Audit retrieval efficiency improved markedly in highly interoperable systems, with mean retrieval duration reduced to 6.2 minutes. Reliability testing confirmed strong internal consistency across constructs, with Cronbach’s alpha values ranging from 0.83 to 0.91. While direct relationships between digital maturity and energy intensity proxies were weaker, indirect sustainability benefits emerged through reduced non-value-added processing time, which averaged a 27.5% reduction in highly automated workflows. The findings demonstrated that digital information flow functioned as a quantitative driver of efficiency, quality, and service reliability in calibration systems. These results supported a system-level perspective in which sustainable calibration design and simulation must integrate digital information dynamics alongside physical calibration processes to enable resilient and resource-efficient industrial engineering applications.