Warranty and Maintainability Analysis for Sensor Embedded Remanufactured Products in Reverse Supply Chain Environment

Remanufactured products are very popular with consumers due to their appeal to offer the latest technology with lower prices compared to brand new products. The quality of a remanufactured product induces hesitation for many consumers, in regards to its efficacy and reliability. One stratagem that remanufacturers could employ to encourage customer security are product warranties. This paper studies and scrutinizes the impact that would be had by offering renewing warranties on remanufactured products. This study was able to determine the optimal costs of warranty for two-dimensional non-renewable warranty offered on remanufactured products using the simulation model and design of experiments

Coping with disassembly yield uncertainty in remanufacturing using sensor embedded products

© 2011, Ilgin et al; licensee Springer.This paper proposes and investigates the use of embedding sensors in products when designing and manufacturing them to improve the efficiency during their end-of-life (EOL) processing. First, separate design of experiments studies based on orthogonal arrays are carried out for conventional products (CPs) and sensor embedded products (SEPs). In order to calculate the response values for each experiment, detailed discrete event simulation models of both cases are developed considering the precedence relationships among the components together with the routing of different appliance types through the disassembly line. Then, pair-wise t-tests are conducted to compare the two cases based on different performance measures. The results showed that sensor embedded products improve revenue and profit while achieving significant reductions in backorder, disassembly, disposal, holding, testing and transportation costs. While the paper addresses the EOL processing of dish washers and dryers, the approach provided could be extended to any other industrial product

Robotic disassembly of electronic components to support end‐of‐life recycling of electric vehicles

This thesis reports on the research undertaken to analyse the factors affecting End-of-Life (EoL) recycling of future Electric Vehicles (EVs). The principle objective of the research is to generate an understanding of challenges and opportunities for the development and implementation of an automated robotic disassembly approach to aid with EoL management of electrical and electronic components within EVs. The research contributions are considered in three main parts. The first part contains a review of advancement in the development of automotive technology, and in particular the alternative fuel vehicles. A review of existing industrial recycling technologies and processes has been conducted which highlighted a number of key challenges in the adoption of current recycling technologies for EVs. The review concludes that there is a need to develop novel recycling technologies and processes to deal with the increased part complexity and material mixture in such vehicles. In this context, the second part of the research details a framework for EoL management of EV components. This framework presents a comprehensive automated robotic disassembly approach in which three specific steps are defined, namely manual disassembly to develop an understanding of product design, initial automated disassembly to test process capability, and optimisation and validation to improve repeatability and efficiency of the robotic disassembly operations. The framework also includes the development of a multi-criteria decision-making tool that assesses the environmental, technological and economic benefits of such robotic disassembly approach. The applicability of the research concepts has been demonstrated via three case studies. The results have highlighted the applicability of the automated robotic disassembly approach in a variety of scenarios of different design complexity and recovery rate. The results indicate that the adoption of this robotic disassembly enhances the pre-concentration of Strategically Important Materials (SIMs) and leads to minimisation of environmental impacts and increased material recovery value

Robotic disassembly for increased recovery of strategically important materials from electrical vehicles

© 2017 Elsevier Ltd. The rapid growth of market share of Electrical Vehicles (EVs) and their increasing amount of electric and electronic components have introduced difficult challenges for future recycling of such vehicles. End of Life Vehicles (ELVs), together with Waste Electric and Electronic Equipment (WEEE), are renowned as an important source of secondary raw materials. In addition, a significant proportion of the hidden value at the End-of-Life (EoL) of the EVs is embedded in the light fractions containing complex material mixtures, i.e. the management of electronic components that has been rarely considered in the scientific literature. The purpose of this paper is to fill this gap through the use of an innovative disassembly approach to identify the profitability of recycling such electronic components. The novel approach, based on the utilisation of a robotic system, disassembles and extracts Strategically Important Materials (SIMs) from EV components, thereby improving the concentration of these materials prior to final recycling and refining processes. This paper presents the challenges in the robotic disassembly of Electrical and Electronic (E & E) components. A case study has also been included to demonstrate that an average 95% of the materials and their associated recovery value could be achieved

TRANSFORMING A CIRCULAR ECONOMY INTO A HELICAL ECONOMY FOR ADVANCING SUSTAINABLE MANUFACTURING

The U.N. projects the world population to reach nearly 10 billion people by 2050, which will cause demand for manufactured goods to reach unforeseen levels. In order for us to produce the goods to support an equitable future, the methods in which we manufacture those goods must radically change. The emerging Circular Economy (CE) concept for production systems has promised to drastically increase economic/business value by significantly reducing the world’s resource consumption and negative environmental impacts. However, CE is inherently limited because of its emphasis on recycling and reuse of materials. CE does not address the holistic changes needed across all of the fundamental elements of manufacturing: products, processes, and systems. Therefore, a paradigm shift is required for moving from sustainment to sustainability to “produce more with less” through smart, innovative and transformative convergent manufacturing approaches rooted in redesigning next generation manufacturing infrastructure. This PhD research proposes the Helical Economy (HE) concept as a novel extension to CE. The proposed HE concepts shift the CE’s status quo paradigm away from post-use recovery for recycling and reuse and towards redesigning manufacturing infrastructure at product, process, and system levels, while leveraging IoT-enabled data infrastructures and an upskilled workforce. This research starts with the conceptual overview and a framework for implementing HE in the discrete product manufacturing domain by establishing the future state vision of the Helical Economy Manufacturing Method (HEMM). The work then analyzes two components of the framework in detail: designing next-generation products and next-generation IoT-enabled data infrastructures. The major research problems that need to be solved in these subcomponents are identified in order to make near-term progress towards the HEMM. The work then proceeds with the development and discussion of initial methods for addressing these challenges. Each method is demonstrated using an illustrative industry example. Collectively, this initial work establishes the foundational body of knowledge for the HE and the HEMM, provides implementation methods at the product and IoT-enabled data infrastructure levels, and it shows a great potential for HE’s ability to create and maximize sustainable value, optimize resource consumption, and ensure continued technological progress with significant economic growth and innovation. This research work then presents an outlook on the future work needed, as well as calls for industry to support the continued refinement and development of the HEMM through relevant prototype development and subsequent applications

Active disassembly applied to end of life vehicles

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Active Disassembly is technology that has been developed to allow assemblies to readily separate for recycling when they are exposed to certain triggering conditions. It is based around fasteners that use `Smart' Materials, typically Shape Memory Alloys (SMA) or Shape Memory Polymers (SMP). This has led to research in the field to be known as Active Disassembly Using Smart Materials (ADSM). Particularly within the context of the EU End of Life Vehicle (ELV) legislation, ADSM has the potential to enable the achievement of the recycling levels required. In this thesis, active disassembly solutions have been developed which have focused on the disassembly of the Instrument Panel, and the glazing within a vehicle. To achieve this, a number of novel Smart fastening devices have been developed, two of which are triggered by integral heating elements. This investigation also led to the creation of a new releasable hook and loop fastening system, known as `Shape Memory Hook and Loop Fasteners' (SM-HALF). SM-HALF is a repositionable fastening system that can be released remotely under a thermal stimulus. Research into the residual energy content of ELV batteries has been a significant part of the investigation. It has been found that it is possible to use the energy from `dead' car batteries to power at least 16 shape-memory alloy devices constructed from 25-micron diameter wire, at End of Life. No external energy input is required for disassembly. This research is timely as it provides a means of reclaiming 10% of a vehicle that would otherwise be lost to the shredder. The technology can: increase the number of parts available for recycling and reuse, separate waste streams, decrease shredder residue otherwise destined for landfill and increase economic returns for either the vehicle dismantling yards or shredder operator

Development of Gen2 RFID-based Closed-loop Supply Chain Management System

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 산업·조선공학부, 2018. 2. 박진우.With the extended producer responsibility, which is a countermeasure for environmental problems such as resource depletion in manufacturing industries, responsibility of manufacturers who produce automotive, electrical and electronic equipment has been extended beyond production, retailing, to collection and recycling of the end-of-life products. Particularly in the case of recycling, a legal system has been introduced that enforces recycling at a certain rate or more on a mass basis. In this background, scope of the supply chain management also has been extended beyond forward process, which consists of sourcing, producing, and delivery, to reverse process. It is called closed-loop supply chain in terms of constantly using the resources that have been put into the manufacturing ecosystem. Proper operation of the closed-loop supply chain can maximize economic profit by value creation along with whole product lifecycle as well as complying with environmental legislation. However, chronic uncertainties of reverse process cause inefficiency in terms of overall performance of closed-loop supply chain. In terms of physical flow, the timing and quantity of end-of-life product return is difficult to predict. Moreover, recycling network is complex because there are many participants in reverse process. In terms of product lifecycle, residual values of returned products are all different due to the factors like usage environments, user behaviors, and so forth. Moreover, this problem becomes even worse at component level. Many research efforts have been proved that real-information gathering can solve this problem. In this context, a system framework that minimizes uncertainties and facilitates various positive effects along with the product lifecycle by using the internet-of-things including radio frequency identification (RFID) and sensors, will be proposed in this dissertation. Unlike the existing approaches that only tag products, component-level individual tagging that tags not only products but also components will be proposed for more detailed lifecycle information management. Especially, encoding the family relationships among the components, by using user memory that is provided by Gen2 RFID protocol, will be proposed to extract new contribution. Information system including RFID tag encoding scheme, will be designed to strictly comply with the established standards to ensure compatibility within the industries in the future. Additionally, potential effects will be examined. Real-time monitoring and maintenance (RMM) and counterfeit prevention scheme, which are intangible effects in terms of product service in the middle-of-life phase, will be introduced. Especially, sweeping scan approach to prevent structural counterfeits of products by using the family relations in the user memory, will be introduced. Also it will be shown that the proposed system is valuable for remanufacturing process streamlining and hybrid remanufacturing/manufacturing production planning with numerical studies.1. Introduction 1 1.1. Product Recycling 1 1.2. Closed-loop Supply Chain 4 1.3. Internet-of-Things 8 1.4. Goal and Scope 10 2. Literature/Technology Review 15 2.1. Literature Review 15 2.2. Technology Review: RFID and Gen2 Standard 21 3. Analysis of Korean ELV Remanufacturing Industry 24 3.1. Overview 24 3.2. Problem Extraction and Classification 26 4. Design of the Proposed System 32 4.1. Lifecycle Information Gathering and Component-level Tagging 32 4.2. Information System Framework and Lifecycle Implications 37 4.3. Design of Data Architecture 46 4.4. Database Transactions for Potential Effects 57 5. System Implementation in the MOL Phase 61 5.1. Real-time Monitoring and Maintenance 61 5.2. Counterfeit Prevention 66 6. Remanufacturing Process Streamlining 70 6.1. Elimination of the Unnecessary Loop 70 6.2. A Requisite for Enhancement 77 7. Hybrid Production Planning for a Remanufacturing/Manufacturing System 87 7.1. Conceptual Modeling 87 7.2. Mathematical Modeling 94 7.3. Computational Results 101 7.4. Sensitivity Analysis 110 8. Conclusion 126 8.1. Summary 126 8.2. Limitations and Future Research Direction 129 Appendix. Numerical Experiment Settings 131 Bibliography 138 국문초록 149Docto

An interactive product development model in remanufacturing environment: a chaos-based artificial bee colony approach

This research presents an interactive product development model in re-manufacturing environment. The product development model defined a quantitative value model considering product design and development tasks and their value attributes responsible to describe functions of the product. At the last stage of the product development process, re-manufacturing feasibility of used components is incorporated. The consummate feature of this consideration lies in considering variability in cost, weight, and size of the constituted components depending on its types and physical states. Further, this research focuses on reverse logistics paradigm to drive environmental management and economic concerns of the manufacturing industry after the product launching and selling in the market. Moreover, the model is extended by integrating it with RFID technology. This RFID embedded model is aimed at analyzing the economical impact on the account of having advantage of a real time system with reduced inventory shrinkage, reduced processing time, reduced labor cost, process accuracy, and other directly measurable benefits. Consideration the computational complexity involved in product development process reverse logistics, this research proposes; Self-Guided Algorithms & Control (S-CAG) approach for the product development model, and Chaos-based Interactive Artificial Bee Colony (CI-ABC) approach for re-manufacturing model. Illustrative Examples has been presented to test the efficacy of the models. Numerical results from using the S-CAG and CI-ABC for optimal performance are presented and analyzed. The results clearly reveal the efficacy of proposed algorithms when applied to the underlying problems. --Abstract, page iv