An i-AHP&QFD warranty model

Purpose – The purpose of this paper is to present a new warranty model to improve warranty management. As a case study, the developed model has been applied on an industrial vehicle manufacturing company. The model is composed of quality function deployment (QFD) and interval-based analytical hierarchy process (i-AHP). The i-AHP is an extension of the concept of analytical hierarchy process (AHP) that takes the benefits of interval computations in order to mitigate the shortcomings of AHP and fuzzy AHP. Design/methodology/approach – Using a combination of i-AHP and QFD, the authors analyzed the several options and alternatives available, weighting each one by means of an interval pair-wise comparison. Using collected data, the authors have shown how to map the capability of each option against each alternative and thereby build a relationship matrix under the QFD approach based on interval computations. Findings – The use of i-AHP&QFD integrated methodology helps to identify the best options to solve several decision problems in diverse fields and could be applied successfully in warranty management. This methodology is especially useful when dealing with several options and equal numbers of alternatives for each warranty option. Research limitations/implications – The case study includes competitiveness analysis at the first house of quality (HOQ), but not at the subsequent HOQ, due to a lack of information from the relevant competitors. However, the paper demonstrates the kind of competitiveness analysis at the first HOQ which can be extended to all subsequent HOQs. Practical implications – The research would be useful to academics and practitioners in developing integrated versions of the QFD and i-AHP methodologies to improve warranties. Originality/value – This study contributes to the diffusion of a new form of integrated warranty model, through the presentation of practical examples of industrial vehicle warranty management. Also, the model presents the i-AHP in order to quantify and compare variables via the use of geometrical averages and to synthesize a subsequent solution.