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Summary The remaining value within end‐of‐use/life hard disk drives (EoU/L HDDs) is often not optimally recovered. The improper collection and recovery of HDDs contribute not only to rising environmental and social concerns worldwide, but also to the transformation of the economy and a significant loss of value. Currently, the most preferred treatment option for used hard drives is to recover the metals with the highest recycling effectiveness, such as steel and aluminum, via a shredding‐based recycling process that results in both value and material leakages. The complexity of retrieving the remaining values within EoU/L HDDs demands a larger view of the global supply of HDDs available for recovery. The aim of this paper is to first identify the geographical patterns of transboundary global shipments of new and used HDDs between developing and developed regions, and then capture and quantify the value leakage by bringing several unique perspectives. Two analyses have been conducted. First, the loss of value due to the insufficient recovery of neodymium (Nd) at the global level is quantified. Second, the value leakage as a result of the delay on on‐time reuse of HDDs is captured. Furthermore, the central challenges toward proper recovery of HDDs, where consumer electronic industry can make significant contributions, have been identified. HDDs are well positioned to contribute important insights to the recovery of other electronic devices, so the findings from HDDs can be adopted for other types of electronics. 

This study used the unrealized potential of citizen science as an innovative educational tool with the aim of enhancing research and learning experience of students in several engineering design and manufacturing courses with a particular focus on sustainability-related topics. Citizen science has been employed as a data collection and educational tool in two engineering courses at the University at Buffalo in which students were tasked with reporting examples of good and bad designs they observe in their everyday life. The results revealed the significant potential of citizen scientists to report innovative and informative design and manufacturing ideas. 

Mobile phones have become ‘essential-to-have’ devices for information-gathering and social communication. They are being technologically advanced, while they are readily available at affordable prices. This motivates consumers to upgrade their mobile phones more frequently. Given these considerations and the lack of accessible repair services, mobile phones have a relatively short life span. The underuse of mobile phones, despite the fact that they are made durable, may result in losses or value leakage. In this study, a probabilistic approach is proposed to quantify the value leakage that may occur due to consumer’s decision to not repair broken mobile phones and simply replace them with new ones. A group of 208 mobile phone users has been surveyed to capture consumer’s time-dependent willingness-to-pay for repair services. Then, consumer’s repair behavior is combined with manufacturer’s repair service pricing strategies to calculate the probability of repair or replacement decisions over the life span of mobile phones. Finally, the total expected leakage risk is derived for both consumers and manufacturers. For illustrative purposes, it is shown that a manufacturer may lose up to 331 million dollars over a period of five years due to consumers’ decisions to not repair their cracked-screen mobile phones and switch to another brand. 

Efficient disassembly operation is considered a promising approach toward waste reduction and End-of-Use (EOU) product recovery. However, many kinds of uncertainty exist during the product lifecycle which make disassembly decision a complicated process. The optimum disassembly sequence may vary at different milestones depending on the purpose of disassembly (repair, maintenance, reuse and recovery), product quality conditions and external factors such as consumer preference, and the market value of EOU components. A disassembly sequence which is optimum for one purpose may not be optimum in future life cycles or other purposes. Therefore, there is a need for incorporating the requirements of the entire product life-cycle when obtaining the optimum disassembly sequence. This paper applies a fuzzy method to quantify the probability that each feasible disassembly transition will be needed during the entire product lifecycle. Further, the probability values have been used in an optimization model to find the disassembly sequence with maximum likelihood. An example of vacuum cleaner is used to show how the proposed method can be applied to quantify different users’ evaluation on the relative importance of disassembly selection criteria as well as the probability of each disassembly operation. 

This paper carries out an analysis of various trade-in programs available for cellphones in the United States. Product trade-in is one of the methods to recover End-of-Life (EoL) products from consumers. Currently, there is a lack of knowledge amongst consumers about such programs. The study aims to determine the factors which influence the product trade-in price. Cell phone trade-in programs of the following types of companies are studied: Phone network operator, online retailer and recycler, and educational institution. Apple’s iPhone was selected to carry out a case study to analyze various features of the trade-in programs. Age of the cell phone model, memory size of the phone, cellphone condition and phone carrier were found to be the most significant factors of a cell phone trade-in program. Newer phone models and higher memory size capacity phones were found to be offered higher price to the consumer. Cellphones of one particular phone carrier and unlocked cell phones were found to obtain the highest price quote. An attempt is made to evaluate and discuss the prospect of trade-in programs as an effective end of life recovery method. Product recovery by trade-in programs and conventional methods is compared based on factors drawn from consumer behavior studies. Improvements in trade-in programs are suggested, followed by a discussion on ways in which data from trade-in programs can benefit product designers. 

As electronic waste (e-waste) becomes one of the fastest growing environmental concerns, remanufacturing is considered as a promising solution. However, the profitability of take back systems is hampered by several factors including the lack of information on the quantity and timing of to-be-returned used products to a remanufacturing facility. Product design features, consumers’ awareness of recycling opportunities, socio-demographic information, peer pressure, and the tendency of customer to keep used items in storage are among contributing factors in increasing uncertainties in the waste stream. Predicting customer choice decisions on returning back used products, including both the time in which the customer will stop using the product and the end-of-use decisions (e.g. storage, resell, through away, and return to the waste stream) could help manufacturers have a better estimation of the return trend. The objective of this paper is to develop an Agent Based Simulation (ABS) model integrated with Discrete Choice Analysis (DCA) technique to predict consumer decisions on the End-of-Use (EOU) products. The proposed simulation tool aims at investigating the impact of design features, interaction among individual consumers and socio-demographic characteristics of end users on the number of returns. A numerical example of cellphone take-back system has been provided to show the application of the model.