Identify Important Factors for Service Simulation Experiments Using QFD

Service design is a form of conceptual design, which involves the activity of planning and organizing people, infrastructure, communication and material components of a service in order to improve its performances. A simulation experiment models various scenarios of a service system. One of the aims of the designer is selecting appropriate factors for the determination of the simulation scenarios. The complete set of possible scenarios is huge, and it is often useful to obtain subjective input to help screen out some vital factors. Taguchi advocates a three‐stage design procedure for off‐line quality control: (i) system design; (ii) parameter design; and (iii) tolerance design. In the parameter design stage, which is the key stage in Taguchi method, factors affecting the performance of Y are categorized as controllable factors and noise factors. In this paper, a Quality Function Deployment matrix highlights controllable factors and noise factors to be considered when running a simulation experiment for a service system. It is assumed that interactions between the factors might be changed for each performance measure, that is, several roofs, corresponding to the number of rows in the Quality Function Deployment matrix. The mean square error criterion is utilized here for selecting the vital service factors to be examined in the simulation experiments.