A fuzzy decision-making approach for testing activity prioritisation and its application in an engine company

Abstract

Prioritising testing activities is essential for new product development to identify the most valuable tests and distinguish the critical ones from the trivial ones. Most research solves this prioritisation problem based on the high risks identified in Failure Mode and Effect Analysis (FMEA). However, an empirical case study on a UK-based engine manufacturer highlights that the aim of testing is not only to detect technical failures but also to validate customer requirements. Based on the findings identified from the empirical study, this paper proposes a systematic approach for testing activity prioritisation, where fuzzy relational decision matrices are established to link customer requirements, technical objectives and testing activities. An XOR Best–Worst Method (BWM) and an extended simple additive weighting (SAW) method are developed to calculate the weights of customer requirements and score the testing activities. The approach also handles two uncertainty scenarios during the prioritisation process, i.e. the subjective judgements of choosing from options and the linguistic vagueness of the decisions. The application in a case from the engine manufacturing company illustrates the methodological improvement in the prioritisation process. The proposed method ranks the testing activities, which suggests an order of effort distribution for the test plan.