Applying Fuzzy QFD McDm to Evaluate Musical Instruments

Abstract

This paper exhibits a method to improve the quality of musical instruments with the application of two Multi-Criteria Decision Making models, Technique of Order Preference by Similarity to Ideal Solution (TOPSIS) and Analytic Hierarchy Process (AHP) in a Quality Function Deployment (QFD) Environment. A fuzzy analysis approach was also included to accommodate qualitative data in music. The QFD was constructed with literature based on optimizing the manufacture of musical instruments. At this phase of the research, the paper focused on the physical parameters and perceived qualities of musical instruments. The proposed modified QFD was developed to identify the product features chosen by the market and aid the manufacture of musical instruments. A standard QFD recognized and scored factors to develop and manufacture musical instruments. It accommodated some core engineering variables for the musical instruments but overlooked some feature stakeholder needs. For example, the musician may not have 100% gratification while playing the instrument as the manufacturer fails to capture acoustic features to psychologically satisfy the musician’s audience. Using fuzzy logic, QFD and MCDM increased the model performance by expanding the data set. It offered the manufacturer of musical instruments a mode to capture and analyse behavioural linguistic data covering more customer requirements. Hence, the approach increased the range to correlate the physical features and psychological behaviours of musical instruments. It allowed non-technical persons to provide an improved form of reliable information. This modified QFD can also be applied to develop other products involving linguistic data.