GOALI: Data Driven Remanufacturing: Foundation for Modeling the Impact of Product Middle-of-Life Data on End-of-Life Recovery Decisions

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1705621 (Behdad). The objective of this research is to create a framework for application of middle-of-life product data toward making sustainable product end-of-use recovery and reuse/recycle/etc. decisions. The framework to be developed has three main components: 1) Data collection: the definitions of different types of data that are generated over the middle-of-life phase of the product, particularly from the consumers' usage behavior, and also the types of uncertainty included in the data; 2) Data analytics: the evaluation of future reusability of consumer electronics based on usage profiles; and 3) Decision-making techniques: the identification of the best End of Use (EOU) options (e.g., reuse, recycle, remanufacture, refurbish, and disposal) not only based on product reusability, but also planned-obsolescence and market acceptance. Several application areas will be studied with the help of an industry partner. The focus will be on collecting consumer usage data for charge and discharge usage of lithium-ion laptop batteries and Hard Disk Drives (HDDs) data from home-run and office-run personal computers. This research is targeted to allow information flow to go beyond the first product lifecycle and to feed the information gathered in the first lifecycle to remanufacturing decisions being made at the start of the future lifecycles. Particularly, a prognostic method will be developed that predicts the future reusability of different components of a product, aggregates the data together and further optimizes the appropriate EOU option.The research will include three major activities: 1) Characterizing product usage behavior of consumers to identify general product usage patterns. Data will be collected from surveys and information collected by industry partners on the specific category of electronic devices to quantify the conditions under which certain electronics have been used; 2) Creating a new class of predictive modeling techniques to quantify the future reusability of products based on the lifecycle profile and consumer usage behavior, and developing a set of decision models in the form of prognostic algorithms to determine the best EOU recovery option for used products incorporating the reusability assessment as well as the information from product technical life, market life, design life and physical life; and finally 3) Evaluating the proposed decision-making methods. This research has potential in facilitating the reusability of consumer electronics. These practices are essential for responding to the growing global hunger for electronic devices in newly industrialized countries that lack the sufficient systems, policies and infrastructure for appropriate management and recovery of electronic waste (e-waste). With the help of an industry partner, the project seeks to advance remanufacturing by providing massive and heterogeneous industry data in a challenging e-waste application area.