Application: Energy Consumption Management, Close-Loop Supply Chain, Design for Product End of Life Recovery, Life Cycle Decision Making, and Design of New Service Business Models.
An Investigation of Used Electronics Return Flows: Capture Consumers Storage and
Utilization Behavior: Consumers often have a tendency to store their used, old or un-functional
electronics for a period of time before they discard them and return them back to the waste stream.
These types of behaviors are influenced by several product and consumer-related factors such as consumers'
traits and lifestyles, technology evolution, product design features, product market value, and pro-environmental stimuli.
This study aims at providing insightful analysis of Electronic Waste (e-waste) dynamic nature by studying the effects of design characteristics,
brand and consumer type on the electronics usage time and end of use time-in-storage.
Suppported by NSF Engineering and Systems Design grant research "GOALI: Remediating E-waste Problems by Considering Consumer Behavior in Design for Multiple Life Cycles and Design for Ease of Return.
Reusability assessment of Lithium-ion laptop batteries based on consumers
actual usage behavior: Product reuse is a recommended action toward sustainability.
However, the profitable reusability of End-of-Use or End-of-Life (EoU/L) products depends on how consumers have used them over the initial lifecycles
and what are their EoU conditions. In addition to consumers' behavior, product design features such as
product durability has an impact on the future reusability. In this project, a data set of Lithium-ion laptop
batteries has been studied with the aim of investigating the potential reusability of laptop batteries.
This type of rechargeable batteries is popular due to their energy efficiency and higher reliability.
Therefore, understanding the lifetime of these batteries and improving the recycling process is becoming important.
The reusability assessment is linked to the consumer behavior and degradation process simultaneously
through monitoring the performance of batteries over their lifetimes. After capturing the utilization behavior,
the performance-based stability time of batteries is approximately derived. Consequently, the Reusability Likelihood
of batteries is quantified using the number of cycles that the battery can be charged with the aim of facilitating
future remarketing and recovery opportunities.