Development and Validation of a Smart Failure Management System for SMEs in Manufacturing

This paper presents the development and validation of a smart failure management system designed for small and medium-sized enterprises (SMEs) in the manufacturing sector. The system integrates the Berlin Problem-Solving Circle, a comprehensive framework for systematically addressing production failures through a knowledge-based expert system. It includes a manual failure entry interface and graphical failure data representation, supported by artificial intelligence (AI) algorithms such as Bayesian Networks for probabilistic inference and Case-Based Reasoning for complex problem-solving. Additionally, an integrated e-learning platform disseminates theoretical and practical method knowledge to employees. The development process spans several critical phases, including knowledge acquisition, system implementation, and validation of user interaction on the shop floors of selected manufacturing companies. This structured approach ensures the system’s effectiveness in addressing complex failures and facilitating continuous improvement. Preliminary results indicate significant improvements in failure prediction, diagnosis, and resolution. The findings underscore the system’s wide applicability across various manufacturing environments, highlighting its potential to improve production quality, reduce costs, and foster continuous learning within SMEs. This paper demonstrates the system’s capacity to promote greater efficiency and resilience in failure management.