Framework for prioritizing infrastructure user expectations using Quality Function Deployment (QFD)

Abstract

Abstract Customer involvement in infrastructure maintenance activities is a complex process due to various decision-making parameters surrounding maintenance. Compared to manufacturing and other disciplines where QFD is widely used, expectations of the infrastructure user as a customer are truly dynamic given the changing economic conditions, technologies, environmental regulations, etc. While such dynamic or changing customer expectations can be addressed by repeated surveys and constant communication, having indicators to predict customer response would be a valuable tool and aid the QFD decision-making process. In this study, a framework that utilizes hidden Markov model (HMM) is proposed for evaluating customer expectation by using probabilities of focus areas that are of interest to the infrastructure user as hidden parameters. The focus areas are based on sustainability parameters and include economic, social, technological, maintenance efficiency, safety and environmental conditions. Probabilities that represent the probability of transition from current state (of the focus area) to next possible state were generated based on expert opinion of the authors. Using the 2005 customer survey by California Transportation, a case study is presented in order to demonstrate the application which concludes that the proposed methodology can be successfully implemented for infrastructure maintenance.