Sustainable Design and Manufacturing

Business outcomes of repairable products

Product repair is a suggested post-purchase activity toward extending the useful lifespan of a product. However, repairability has not received sufficient attention by manufacturers. Even if the product repairability is not explicitly claimed by manufacturers, it is expected by consumers, thereby impacting their loyalty and future purchase recommendations. In this paper, the impact of consumers’ product repair experiences on their future purchase and recommendation decisions is investigated. The study is based on a survey consisting of 8403 consumers who have had personal repair experiences in year 2013. A bivariate ordered probit model is used to estimate two correlated variables that jointly represent the future product sale, namely ‘consumer future purchase decision’ and ‘purchase recommendations to friends and family’. It was found out that predictor factors such as usefulness of repair information, complexity of repair and consumers’ willingness to repair a broken product have significant effect on the future purchase decisions and recommendations.

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Heterogeneity in Consumers’ Usage Behavior

In this study, we have developed a framework for understanding the heterogeneity and uncertainties present in the usage phase of the product lifecycle through utilizing the capabilities of Agent Based Modeling (ABM) technique. An ABM framework has been developed to model consumers’ daily product usage decisions and to assess the corresponding electricity consumption patterns. The Theory of Planned Behavior (TPB) with the addition of the habit construct is used to model agents’ decision-making criteria. A case study is presented on the power management behavior of personal computer users and the possible benefits of using smart metering and feedback systems. The results of the simulation demonstrate that the utilization of smart metering and feedback systems can promote the energy conservation behaviors and reduce the total electricity consumption of households by 20 percent.  [photo credit goes to Orange Systemz]

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Current Trade-In Programs Available for Used Consumer Electronics

This study 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.  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. 

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Environmental Impacts of Industry 4.0

Smart manufacturing in an Industry 4.0 setting requires developing unique infrastructures for sensing, wired and wireless communications, cyber-space computations and information tracking. While an exponential growth in smart infrastructures may impose drastic burdens on the environment, the conventional Life Cycle Assessment (LCA) techniques are incapable of quantifying such impacts. Therefore, there is a gap between advances in the manufacturing domain and the environmental assessment field. The capabilities offered by smart manufacturing can be applied to LCA with the aim of providing advanced impact assessment, and decision-making mechanisms that match the needs of its manufacturing counterpart. 

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Environmental Evaluation of Product Design Alternatives

Consumers might be willing to repair their broken devices as long as the associated repair costs do not exceed an undesirable threshold. However, in many cases the technological obsolescence actuates consumers to retire old devices and replace them with new ones rather than extending the product lifecycle through repair. In this study, we investigated the impact of components’ deterioration profiles and consumers’ repair decisions on the lifespan of devices, and then assessed the anticipated life cycle environmental impacts. A simulation model has been developed to estimate the life cycle characteristics such as the average lifespan, the number of failed components’ replacement, and the total repair cost per cycle for a laptop computer. 

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Design Decisions and Consumer Decisions on Returning End-of-Use Products

Predicting customer choice decisions on returning 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, throw away, and return to the waste stream) could help manufacturers better estimate the return trend. In this study, we have developed  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. 

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