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

1705621(Behda)。这项研究的目标是创建一个框架，用于应用中年产品数据，以制定可持续的产品最终使用回收和再利用/再循环/等决策。要开发的框架有三个主要组成部分：1)数据收集：定义在产品生命中期阶段产生的不同类型的数据，特别是从消费者的使用行为产生的数据，以及数据中包含的不确定性类型；2)数据分析：基于使用概况对消费电子产品未来的可重用性进行评估；以及3)决策技术：不仅基于产品的可重用性，而且基于计划报废和市场接受程度确定最佳使用终端(EOU)选项(例如，重用、回收、再制造、翻新和处置)。将在行业合作伙伴的帮助下研究几个应用领域。重点将是从家庭运行和办公室运行的个人计算机收集锂离子笔记本电脑电池和硬盘驱动器(HDD)充放电使用的消费者使用数据。这项研究的目标是让信息流超越第一个产品生命周期，并将第一个生命周期中收集的信息提供给在未来生命周期开始时做出的再制造决策。特别是，将开发一种预测方法，预测产品不同组件的未来可重用性，将数据聚合在一起，并进一步优化适当的EOU选项。研究将包括三个主要活动：1)表征消费者的产品使用行为，以确定一般产品使用模式。数据将从行业合作伙伴收集的关于特定类别电子设备的调查和信息中收集，以量化某些电子设备在何种条件下被使用；2)创建一类新的预测建模技术，以便根据产品的生命周期概况和消费者的使用行为来量化产品的未来可重用性，并开发一套以预测算法形式的决策模型，以确定二手产品的最佳EOU回收选项，其中包括可重用性评估以及来自产品技术寿命、市场寿命、设计寿命和物理寿命的信息；最后，3)评估拟议的决策方法。这项研究在促进消费电子产品的可重用性方面具有潜力。这些做法对于应对新兴工业化国家日益增长的全球对电子设备的渴求至关重要，这些国家缺乏适当管理和回收电子废物(电子废物)的充分系统、政策和基础设施。在行业合作伙伴的帮助下，该项目寻求通过在具有挑战性的电子垃圾应用领域提供海量和不同种类的行业数据来推进再制造。

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.