Analyzing fuzziness in product quality and reliability information-flow during time-driven product-development-process

This paper provides a different angle to look at quality and reliability (Q&R) problem prediction in a time-driven product development process (PDP) where the Q&R information is highly uncertain. Through a case study, it is demonstrated that many of the critical Q&R problems in such a product development cannot be predicted due to highly fuzzy Q&R information. Therefore, a new tool, the reliability and quality matrix (RQM), was developed to overcome this difficulty. It is shown that RQM can not only quantitatively indicate the severity level of an identified Q&R problem but also reflect on its associated uncertainty level due to fuzzy Q&R information. RAM was developed as an enhancement of failure mode effect analysis (FMEA) or quality function deployment (QFD). If the quality of the input information is very good, RQM then presents only the results from FMEA or QFD. However, if uncertainty in the input information is obviously high, RQM can act as uncertainty/fuzziness reduction tool to strengthen the weakness of FMEA and QFD when dealing with fuzzy information.