The seven-step failure diagnosis in automotive industry. (October 2020) - Altinisik, Armagan; Hugul, Ozgur
Highlights: 7-step diagnosis approach for automotive failures has been developed. Phenomenon is the key to narrow down the search perimeter of the problem. Diagnosis performance score, lead time, and NTF ratio could be used to improve the diagnosis competency. Failure repeatability, necessity of advanced diagnostic equipment, and non-linear interactions of causes are the highest impact on complexity. Abstract: Problem solving (PS) competency has been considered as the key competitive weapon for automotive manufacturers. Correct and reliable diagnosis is considered as the most important challenge in PS process. In this study, the seven-step approach for complex and cross-functional diagnosis has been developed based on the first two steps of universal PS approach. The proposed procedure puts the phenomenon forward prior to the definition of root causes. Obviously, it will speed up the PS process by narrowing the search perimeter. The structured and validated procedure guides the experts to optimize their diagnosis process. The new method was integrated with knowledge management system 'SW e-Lua' to transfer the accumulated know-how to the new projects. The key indicators, such as diagnosis performance, lead time, and no trouble found (NTF) ratio, have been developed to improve the efficiency of the new approach. The significant improvements were obtained through three years of implementation. By this way, the competency level of the diagnostic experts could be traced and improved. The factors affecting the complexity and the quality of a diagnosis were proposed and surveyed through OEMs, suppliers and aerospace industries. The structured problem description and the validated phenomenon were defined as the most important factors to narrow down the perimeter of the problem; consequently, they increase the efficiency of the diagnosis process. On the other hand, non-linear interaction of parameters, failure repeatability, and the necessity of advanced diagnostic equipment usage were revealed as the highest impact on the diagnosis complexity.