Simulation of Product Performance Based on Real Product-Usage Information: First Results of Practical Application to Domestic Refrigerators

Abstract

Today’s connected products increasingly allow us to collect and analyze information on how they are actually used. An engineering activity where usage data can prove particularly useful, and be converted to actionable engineering knowledge, is simulation: user behavior is often hard to model, and collected data representing real user interactions as simulation input can increase realism of simulations. This is especially useful for (i) investigating use-related phenomena that influence the product’s performance and (ii) evaluating design variations on how they succeed in coping with real users and their behaviors. In this paper we explored time-stamped usage data from connected refrigerators, investigating the influence of door openings on energy consumption and evaluating control-related design variations envisaged to mitigate negative effects of door openings. We used a fast-executing simulation setup that allowed us to simulate much faster than real time and investigate usage over a longer time. According to our first outcomes, door openings do not affect energy consumption as much as some literature suggests. Through what-if studies we could evaluate three design variations and nevertheless point out that particular solution elements resulted in better ways of dealing with door openings in terms of energy consumption.

Simulations Based on Product-Usage Information From Connected Products to Support Redesign for Improved Performance: Exploration of Practical Application to Domestic Fridge-Freezers

“…Inclusion of these in Ref. [8] explains some differences in the results presented here. six what-if alternatives to be simulated, and to be combined to represent the fridge-freezer as a whole.…”

“…1.3 Structure of the Article. This article elaborates on a paper we presented at the ASME-CIE 2018 conference [8] and is structured as follows. In Sec.…”

A Systematic Procedure for Utilization of Product Usage Information in Product Development

“…Regarding the usage and analysis methodology of PUI, the reviewed application cases often use data science methods and tools (e.g., machine learning, text and data mining, and statistic analysis) to derive useful knowledge or models for development tasks. In some cases, researchers use a set of integrated PUI directly for, for example, simulation analysis [28].…”