Agent-based error prevention algorithms

This article presents a new methodology using distributed algorithms to identify and prevent errors in production and service. A sequential production/service line is selected to challenge the analysis, and reveal if the distributed algorithms can outperform centralized algorithms in automating error prevention. Agent-based error prevention algorithms (AEPAs) are developed for distributed agents to identify and prevent errors with decision rules. Analytical studies and simulation experiments are conducted to compare AEPAs with traditional centralized error prediction and detection algorithms. The results show that the AEPAs employing nominal and optimistic rules perform better than the centralized algorithms in terms of preventability and reliability. Collaboration among agents improves AEPAs’ performance. It is recommended to prevent errors by two agents simultaneously executing the AEPA employing the integrated nominal rule.