An Analysis Method to Identify the Importance of Technical Parameters for Complex Products

Due to prominently specialized requirements and significant nonlinear relationship between technical parameters, it is challenging to optimize the design for complex products. Traditional design methods, such as axiomatic design and model-based system engineering (MBSE), either heavily rely on subjective opinions from experts or are difficult to implement for complex products. This study proposes an analysis method to provide a more objective approach for ranking the importance of technical parameters for complex products and help to identify the technical parameters which need to be improved most urgently. By considering the operating environment of the complex products, a product requirement-performance-parameter correlation model is developed. Then, the ranking of technical parameters is derived by mapping the importance of performances, determined using the expert hesitant fuzzy linguistic preference relations, to the importance of technical parameters, using an improved causal chain analysis model. Finally, the effectiveness of the proposed method is verified by a case study, which identifies the most important technical parameters for optimizing the inlet adjustment mechanism of a combined cycle engine in high-speed aircraft.