Rules modification on a Fuzzy-based modular architecture for medical device design and development

Abstract

Medical devices have a very high failure rate in their first prototype tests. According to the international testing body Intertek, out of every ten medical devices, nine fail in their first prototype tests—a 90% failure rate. In addition to the cost implication, quality is a key issue. To address this, we present an integrated, collaborative modular architecture method for medical device design and development. The methodology focuses on analyzing the input of stakeholder data from existing products and components to achieve an optimal number of modules. The objective of this research is to investigate the effect of rules modification on the final number of product modules. The methodology starts by defining a product's functional and physical decompositions. Next, product parameters are selected and prioritized using an analytical hierarchy process (AHP) to determine the medical device manufacturers’ focus area(s). Candidate modules are evaluated by acquiring stakeholder data and converting them to crisp values by applying the fuzzy-based Sugeno method. Optimal module values are then determined using a multi-optimization goal programming model. Finally, we analyse the effect of changing the number of fuzzy rules on the optimal number of modules and minimum deviation, ‘d’. A typical glucometer is used for a proof of concept. The implication of this work is the determination that the optimal number of product modules is affected by the rules changes.