Development and implementation of product sustainment simulator utilizing fuzzy cognitive map (FCM)

Purpose – Managing product life cycle data is important for achieving design excellence, product continued operational performance, customer satisfaction and sustainment. As a result, it is important to develop a sustainment simulator to transform life cycle data into actionable design metrics. Currently, there is apparent lack of technologies and tools to synthesize product life time data. The purpose of this paper is to provide a description of how a product sustainment simulator was developed using fuzzy cognitive map (FCM). As a proof of concept, and to demonstrate the utility of the simulator, an implementation example utilizing product life time data as input was demonstrated. Design/methodology/approach – The sustainment simulator was developed using visual basic. The simulation experiment was accomplished using a FCM. The Statistical Analytical Software tool was used to run structural equation model programs that provided the initial input into the FCM and the simulator. Product life data were used as input to the simulator. Findings – There is an apparent lack of technologies and tools to synthesize product life time data. This constitutes an impediment to designing the next generation of sustainable products. Modern tools, technologies and techniques must be used if the goal of removing product design and sustainment disablers is to be achieved. Product sustainment can, therefore, be achieved using the simulator. Research limitations/implications – The sustainment simulator is a tool that demonstrates in a practical way how a product life time generated data can be transformed into actionable design parameters. This paper includes analysis of a sample generated using random numbers. The lack of actual data set is primarily due to reluctance of organizations to avail the public of actual product life time data. However, this paper provides a good demonstration of how product life time data can be transformed to ensure product sustainment. Practical implications – The technique used in this research paper would be very useful to product designers, engineers and research and development teams in developing data manipulation tools to improve product operational and sustainable life cycle performance. Sustainment conscious organizations will, no doubt, benefit from a strong comparative and competitive advantage over rivals. Originality/value – Utilizing the simulator to transform product life time data into actionable design metrics through the help of an efficient decision support tool like the FCM constitutes a step in supporting product life cycle management. The outcome of this paper alerts product designers on parameters which should be taken into account when designing a new generation of a given product(s).