Enhancing reliability in advanced manufacturing systems: A methodology for the assessment of detection and monitoring techniques

Advanced manufacturing systems demand the utilization of technologies, methods and capabilities to improve production efficiency or productivity, while ensuring environmental and societal sustainability. Digitalization emerges as an alternative solution for improving the monitoring capabilities of manufacturing systems and consequently enhance the decision-making process. However, the widespread adoption of digital solutions introduces complexities in measurement reliability, data management, and environmental concerns in terms of e-waste and data storing. Therefore, enhancing monitoring capabilities while minimizing resource consumption is crucial for ensuring system reliability in a sustainable way. This research introduces a methodology for assessing the monitoring condition of manufacturing systems. By integrating functional and dysfunctional analysis, approaches that focus on identifying critical functions and potential failure modes of a system, the proposed methodology provides a comprehensive system perspective and targeted directives for improvement. The effectiveness and versatility of the methodology are demonstrated and discussed through its application to various manufacturing systems at a component, machine, and line level. • Approach combines functional & dysfunctional analyses to assess monitoring condition. • Holistic assessment focuses on optimizing resources and enhancing system reliability. • Recommendations to enhance system reliability are derived by linking critical functions with potential failures. • Adaptable to diverse manufacturing complexity, applicable across industries & system scales.