Waste electronics and electrical equipment disassembly and recycling using Petri net analysis: Considering the economic value and environmental impacts

The Industry Council for Electronic Equipment Recycling (ICER) has published estimates of waste generation based on both assumptions and analysis regarding the relationship between the market sales of Electrical and Electronic Equipment (EEE) in a given year and the expected lifetime of products as well as by employing market saturation factors. Waste EEE (WEEE) has an adverse impact on the environment. Therefore, it is important to reduce the quantity of WEEE through recycling. While attempting to improve the recycling rate of WEEE by enhancing the disassembly processes, two issues must be considered simultaneously—economy and safety. In this paper, a Petri Net (PN) based analysis approach is proposed to deal with the disassembly and recycling problems in End-Of-Life (EOL) WEEE. By using the PN analysis, the optimal tradeoff between the cost and environmental effectiveness of the disassembly processes is determined. A case study is used to illustrate the proposed analysis method.     

Selective disassembly planning for waste electrical and electronic equipment with case studies on liquid crystaldisplays

Waste Electrical and Electronic Equipments (WEEEs) are one of the most significant waste streams in modern societies. In the past decade, disassembly of WEEE to support remanufacturing and recycling has been growingly adopted by industries. With the increasing customisation and diversity of Electrical and Electronic Equipment (EEE) and more complex assembly processes, full disassembly of WEEE is rarely an ideal solution due to high disassembly cost. Selective disassembly, which prioritises operations for partial disassembly according to the legislative and economic considerations of specific stakeholders, is becoming an important but still a challenging research topic in recent years. In order to address the issue effectively, in this paper, a Particle Swarm Optimisation (PSO)-based selective disassembly planning method embedded with customisable decision making models and a novel generic constraint handling algorithm has been developed. With multi-criteria and adaptive decision making models, the developed method is flexible to handle WEEE to meet the various requirements of stakeholders. Based on the generic constraint handling and intelligent optimisation algorithms, the developed research is capable to process complex constraints and achieve optimised selective disassembly plans. Industrial cases on Liquid Crystal Display (LCD) televisions have been used to verify and demonstrate the effectiveness and robustness of the research in different application scenarios.     

Developing a bi-objective model of the closed-loop supply chain network with green supplier selection and disassembly of products: The impact of parts reliability and product greenness on the recovery network

Closed-loop supply chain network (CLSCN) design aims to incorporate environmental considerations into the traditional supply chain design by including recycling, disassembly and reuse activities. A CLSCN incorporates the use and reuse of environmentally friendly products and materials supported by the design of an appropriate recovery, disassembly, and refurbishing network. In the design process, a trade-off must often be made between the need to maximize profit and maximize greenness. The latter is considered for several reasons including regulatory requirements, corporate responsibility and corporate image. In this paper, a bi-objective mixed integer programming model is developed and solved for a forward/reverse logistic network including three echelons in the forward direction (suppliers, assembly centers and customer zones) and two echelons in the reverse direction (disassembly and recycling center). A set of Pareto optimal solutions is obtained to show the trade-off between the profit and the greenness objectives. Some useful managerial insights are developed through various computational experiments.     

A Kano model,AHP and M-TOPSIS method-based technique for disassembly line balancing under fuzzy environment

Recovery, recycling or remanufacturing of post-consumed products are viable alternatives for reducing the environmental problems resulting from the huge amounts of waste currently arriving at landfills. Disassembly operations are inevitable for product recovery therefore the disassembly line is an appropriate choice to carry out the same. A disassembly line balancing problem is how to streamline the disassembly activities, so that the total disassembly time required at each workstation is approximately the same. The assignment of jobs to workstations in a disassembly environment has been the matter of concern to researchers because the product, which has to be disassembled, have different types of materials. The main aim of a disassembly process is to reuse components and reduce undesirable impact on the environment. This paper applies a Kano model, fuzzy-AHP, and M-TOPSIS-based technique, shown to successfully find the optimal order of component removal using AND/OR precedence relation. The tasks are assigned to the disassembly workstations according to their priority rank and precedence relations. The proposed technique has been illustrated with an example and the results show improvements in the performance in comparison with other techniques.     

Intelligent decision making in disassembly process based on fuzzy reasoning Petri nets

Practical disassembly process planning is extremely important for efficient material recycling and components reuse. The research work for the process planning in literature focuses on the generation of optimal sequences based on the predictive information of products. The used products, unfortunately, exhibit high uncertainty since products may experience very different conditions during their use stage. The indeterminate characteristics associated to used products often makes the predetermined plan unrealistic. Their disassembly process has to be decided dynamically adaptive to the products' specific status. To be able to deal with uncertainty in a dynamic decision making process, this paper presents a fuzzy reasoning Petri net (FRPN) model to represent related decision making rules in disassembly process. Using the proposed fuzzy reasoning algorithm based on the FRPN model, the multicriterion disassembly rules can be considered in the parallel way to make the decision automatically and quickly. Instead of producing the disassembly sequences before disassembling a whole product, the proposed method makes intelligent decisions based on dynamically updated status of components in the product at each disassembly step. Therefore, it is adaptive to the changes that arise during the process. Finally, an example is used to illustrate the application of the proposed methodology.     

The strategic role of recycling centres for environmental performance of waste management systems

This paper analyses how different actors influence the sorting quality of waste at recycling centres. Users (i.e. citizens) play an essential role since they conduct the actual sorting. They have difficulties sorting many of their discarded products, leading to decreased performance of the entire waste management system of which recycling centres are a part. Several measures addressing this problem are identified such as product design, improved terminology for labelling waste and increased manning at recycling centres. A fundamental task for managers and employees is to further develop information and guidance for users, both at home and at recycling centres. Several obstacles for improvements are also discussed, including working conditions and the economy of recycling centres, as well as the routines for communication and quality assurance among actors in the recycling business.     

Disassembly information model incorporating dynamic capabilities for disassembly sequence generation

Industrial recycling and reusing is becoming more and more important due to the environmental and economic pressures. It involves disassembly activities to retrieve all the parts or selected parts. An information modeling for the disassembly and optimal disassembly sequence generation based on the information model becomes critical. Unlike the traditional graph based representation of product structure, this paper introduces an efficient and machine readable disassembly information model and then discusses a linear programming based optimization model for obtaining the optimal disassembly sequence from the proposed disassembly information model. A key feature of this approach is the incorporation and use of dynamic capabilities in its information model processing technique. Dynamic capabilities are added into the information model to handle state-dependent information such as parts' disassembly directions which may change after each disassembly operation. The overall information model is built in UML, and dynamic capabilities are represented as events in UML. The proposed method has been illustrated using an electrical–mechanical device.     

Human–robot collaborative partial destruction disassembly sequence planning method for end-of-life product driven by multi-failures

Partial destructive disassembly (PDD) of large complex products often requires human–robot collaborative disassembly (HRCD). Therefore, a human–robot collaboration partial destructive disassembly sequence planning (HRCPDDSP) method of end-of-life products driven by multiple failures is proposed to obtain the optimal disassembly sequence to improve disassembly efficiency and degree of automation. Based on the product disassembly priority and part failure characteristics, an information model of the HRCPDDSP method is constructed. Furthermore, the model is expressed as a constraint matrix and recycling decision matrix. A multi-layer chromosome coding method, including HRCD, destructive constraint, and node layers, is proposed of the characteristics of the HRCPDDSP method. The approximate optimal sequence of human–robot collaboration PDD is achieved by improving evolutionary mechanisms such as selection, crossing, and mutation. Finally, the model and algorithm are applied to solve a case of HRCPDDSP, and the feasibility and effectiveness of the proposed method are further verified by comparison with other disassembly modes.     

回收不确定下WEEE逆向物流网络鲁棒优化设计

电子电器废弃物（WEEE）存在对环境和人体健康的危害,有效对其进行回收能避免此类危害和提高资源的利用率。WEEE逆向物流回收网络的设计为实现这一目标起到了关键的作用。考虑WEEE逆向物流网络运作的不确定性,引入风险偏好系数和约束背离惩罚系数,建立了WEEE逆向物流网络的鲁棒优化模型。该模型能允许决策者对系统运作的鲁棒水平进行调节,同时能允许决策者对风险偏好进行调节。仿真结果表明建立的模型能有效抑制逆向物流系统运作的不确定性,使系统具有更低的风险。     

A novel approach to product modularity and product disassembly with the consideration of 3R-abilities

In recent years, the production of electrical and electronic equipment (EEE) has been one of the fastest growing areas of manufacturing. The recent European Community waste EEE directives aim to promote the recycling, reuse and reduction (3R) of such waste. The 3Rs are becoming increasingly important, due to current strict environmental regulations. However, research to enhance 3R-abilities with better design presents some difficulties: there is no present analysis of the impact of each of the 3Rs and analytical methods are often too complicated, so there is a need for practical and simple guidelines. To resolve these issues, this paper presents a novel approach that considers the relationships between product components and identifies the ideal product disassembly pattern and modularity by constructing a component matrix, with regard to product disassembly. The product disassembly, which identifies modules and disassembly pattern, also initiates a strategy to enhance 3R-abilities. Two cases are presented to show the effectiveness of the proposed approach.     

A hybrid metaheuristic algorithm for a profit-oriented and energy-efficient disassembly sequencing problem

Value recovery from end-of-life products plays a key role in sustainability and circular economy, which starts with disassembly of products into components for reuse, remanufacturing, or recycling. As the process is often complex, a disassembly sequencing problem (DSP) studies how to optimally disassemble products considering the physical constraints between subassemblies/disassembly tasks for maximum profit. With a growing attention on energy conservation, this paper addresses a profit-oriented and energy-efficient DSP (PEDSP), whereby not only the profit is maximized, but also energy consumption is accounted as an important decision criterion. In this work, a disassembly AND/OR graph (DAOG) is used to model a disassembly diagram for a product, in which the ‘AND’ and ‘OR’ relations illustrate precedence relationships between subassemblies. Based on the DAOG, we propose a hybrid multi-objective metaheuristic that integrates an artificial bee colony algorithm, a non-dominated sorting procedure, and a variable neighborhood search approach to solve the PEDSP for Pareto solutions. The proposed method is applied to real-world cases (i.e., a simple ballpoint pen and a relatively complex radio) and compared with other multi-objective algorithms. The results indicate that our method can quickly produce a Pareto front that outperforms the alternative approaches.     

北京市餐厨垃圾和废弃油脂监管体系的研究

随着"地沟油"问题越来越严重,食品安全问题引起人们的广泛关注。如何监管北京市六万多个餐饮服务单位,杜绝"地沟油"回流现象,成为日益严重的问题。由于倒卖地沟油有巨大的利润,正规企业处理餐厨垃圾及废弃油脂的成本较高,衍生物尚未形成产业链,衍生商品销量不大,资金回流困难。基于目前餐厨垃圾和废弃油脂管理困难的情况,本文提出了一种合理的餐厨垃圾和废弃油脂监控管理体系,利用信息化系统全程监管产生源头、运输和处理的过程;利用源头产生量的数据,建立合理的"奖"与"罚"制度;通过建立餐厨垃圾和废弃油脂电子政务网站,面向公众提供透明信息,使百姓可以参与监督、监管。     

Genetically optimised disassembly sequence for automotive component reuse

Environmental sustainability through end-of-life recovery has become the main items of contest in the automotive industries. Component reuse as one of the product recovery strategy is now gaining importance in view of its impact on the environment. Disassembly as one of the determinant factors for reuse is a very important and difficult process in life cycle engineering. To enable reuse, a certain level of disassembly of each component is necessary so that parts of the products that have arrived at their end-of life can be easily taken apart. Improvements to the disassembly process of products can be achieved at two levels: in the design phase, making choices that favours the ease of disassembly of the constructional system (design for disassembly) and planning at best and optimising the disassembly sequence (disassembly sequence planning). Hence, finding an optimal disassembly sequence is important to increase the reusability of the product. This paper presents the development work on an optimisation model for disassembly sequence using the genetic algorithms (GA) approach. GA is chosen to solve this optimisation model due to its capability in solving many large and complex optimisation problems compared with other heuristic methods. The fitness function of the GA in this study is dependent on the increment in disassembly time. Comparison of results using different combinatorial operators and tests with different probability factors are shown. This paper will present and discuss the disassembly sequence of an engine block, as a case example which achieves the minimum disassembly time.     

WEEE treatment strategies’ evaluation using fuzzy LINMAP method

Electrical and electronic equipments (EEE) have already begun to be accumulated at the garbage dumps. This garbage accumulation brings big danger to the environment and human health. That’s why one should look for exploring the ways to dispose of these wastes and emphasize the waste treatment strategies. Waste treatment strategies also contribute either to local or global economies by creating a new sector and employment opportunities, and by reducing use of scarce resources. In this paper, a linear programming technique for multidimensional analysis of preference (LINMAP) method for solving multi-attribute group decision making (MAGDM) problems with preference information on alternatives in fuzzy environment is developed. The aim is to develop a fuzzy LINMAP model for evaluation and select of a waste treatment strategy for EEE. Thus, three treatment strategy alternatives and eight criteria are determined. The best strategy is selected and the key criterion is found accordingly. The best alternative is found to be treating waste electrical and electronic equipments (WEEE) by reuse and recycling methods.     

Multi-objective partial parallel disassembly line balancing problem using hybrid group neighbourhood search algorithm

To reduce waste during disassembly production and improve disassembly efficiency, this study investigates a type of partial parallel disassembly line applicable for the simultaneous disassembly of different products. A multi-objective mathematical model for a partial parallel disassembly line balancing problem is built considering four optimisation goals, namely, the minimisation of the cycle time, number of workstations, idle index, and quantity of disassembly resources. In addition, a novel multi-objective hybrid group neighbourhood search algorithm is proposed. First, a certain set of neighbourhood individuals (from the current population of individuals) is generated via neighbourhood search mechanisms based on optimal embedding and exchange operations. Then, a Pareto filtering process is performed on a mixed population composed of the individuals of the current population and all neighbourhoods. Subsequently, the current population individuals are renewed based on the mixed population. To prevent the algorithm from falling into a local optimum and to enhance the algorithm’s global search performance, we conduct a local search strategy based on a simulated annealing operation on the newly generated population individuals. The effectiveness and superiority of the proposed algorithm are proven by solving two complete disassembly line balancing problems at different scales and a partial disassembly line balancing problem, and also by comparison with several algorithms investigated in existing literature. Finally, the proposed model and algorithm are applied to a partial parallel disassembly line designed for the simultaneous disassembly of two types of waste products in a household appliance disassembly enterprise. The results of the partial parallel disassembly line are compared with those of an initial single-product straight disassembly line, and the comparison results show that the solution results of the optimisation goals for the partial parallel disassembly line are more superior than those of the initial single-product straight disassembly line.     

Enhancing disassembly and recycling planning using life-cycle analysis

Both the general public and governmental agencies highly prioritize resource optimization (energy and material) and environmental issues such as ozone, acid rain and global warming in the life-cycle context. Disassembly and recycling are also increasingly important in most industrial countries due to the significant increase in the quantity of used products being discarded. Disassembly of used products has been recognized as necessary to make recycling economically viable in current state-of-the-art reprocessing technology. This emerging trend requires incorporating environmental considerations into design strategies. This study presents a graph-based heuristic method for disassembly analysis of end-of-life products, which incorporates the Eco-Design concept. Product components and their assembly relationships from the bill of material BOM are adopted to split the graph into sub-graphs denoting modular sub-assemblies. The life-cycle analysis LCA is then used to analyze disassembly trees, from which a disassembly sequence can be derived. Designers can use the analytical results to evaluate the dis-assemblability and recyclability of products when they are designed.     

Design for manufacture and design for ‘X’: concepts,applications, and perspectives

The implementations of design for assembly and design for manufacture (DFM) led to enormous benefits including simplification of products, reduction of assembly and manufacturing costs, improvement of quality, and reduction of time to market. More recently, environmental concerns required that disassembly and recycling issues should be considered during the design stages. The effort to reduce total life-cycle costs for a product through design innovation is becoming an essential part of the current manufacturing industry. Therefore, researchers begin to focus their attention on design for environment, design for recyclability, design for life-cycle (DFLC), etc. These studies are sometimes referred to as Design for X (DFX). Since the late 1990s, hundreds of papers have been published pertaining to DFX applications in manufacturing. Most of them are widely distributed over many different disciplines and publications. This makes it very difficult for one to locate all the information necessary for the application of DFX in manufacturing. A paper that can help researchers and practitioners applying this emerging technology is highly desirable. The objective of this paper is to present the concepts, applications, and perspectives of ‘DFX’ in manufacturing, thus providing some guidelines and references for future research and implementation.     

An integrated model for closed-loop supply chain configuration and supplier selection: Multi-objective approach

Reverse logistics consists of all operations related to the reuse of products. External suppliers are one of the important members of reverse logistics and closed loop supply chain (CLSC) networks. However in CLSC network configuration models, suppliers are assessed based on purchasing cost and other factors such as on-time delivery are ignored. In this research, a general closed loop supply chain network is examined that includes manufacturer, disassembly, refurbishing, and disposal sites. Meanwhile, it is managed by the manufacturer. We propose an integrated model which has two phases. In the first phase, a framework for supplier selection criteria in RL is proposed. Besides, a fuzzy method is designed to evaluate suppliers based on qualitative criteria. The output of this stage is the weight of each supplier according to each part. In the second phase, we propose a multi objective mixed-integer linear programming model to determine which suppliers and refurbishing sites should be selected (strategic decisions), and find out the optimal number of parts and products in CLSC network (tactical decisions). The objective functions maximize profit and weights of suppliers, and one of them minimizes defect rates. To our knowledge, this model is the first effort to consider supplier selection, order allocation, and CLSC network configuration, simultaneously. The mathematical programming model is validated through numerical analysis.     

离散鲸鱼算法求解拆解序列规划问题

工业产品的回收再制造有利于降低生产成本和保护环境, 而制定优秀的产品拆解序列规划提高拆解效率、降低回收成本为其关键. 针对回收设备在实际拆解中的因素, 建立一种基于离散鲸鱼算法(DWOA)的拆解序列规划模型. 该模型目标函数以位置改变为代价作为新的评价指标, 利用分层组合的方法快速生成初始群体. 离散鲸鱼算法具有优先保护约束交叉机制、启发式变异、优秀的全局和局部搜索能力. 以回收上橡皮板和空气围带进行对比实验, 结果表明在相同时间下, 离散鲸鱼算法的算法稳定性、寻优能力、收敛速度都要优于其他算法.