An Agent-Based Model for No Fault Found Events

This paper develops an agent-based model to estimate the likelihood of the No Fault Found (NFF) phenomenon. NFF events are critical problems as the root cause of an issue cannot be diagnosed. This makes it difficult to quantify associated costs as potentially serviceable equipment is being returned for repair. Here, the authors first map the dynamic interactions experienced during NFF events across a predefined supply chain. The motivation is to understand component flow by evaluating the root causes of NFF in a more proactive way across the supply network. The data is collected using semi-structured interviews with 12 maintenance-related experts to understand how NFF manifests during maintenance across 7 UK organisations. Then, the NFF phenomenon across the supply chain is reflected using an agent-based model; to support decision-making at the design level, on component selection in terms of product reliability, and at the service level to support decision-making. Monitoring the NFF likelihood metric can help manage the problem, whilst demonstrate how qualitative information can be used to achieve maintenance objectives