Quality control of an unreliable random FMS: with Bernoulli and CSP sampling

It is widely recognized that disassembly-based product End-of-Life strategies, such as component reuse or simple fraction material recycling, are environmentally beneficial. However, current disassembly costs hinder a widespread application of these strategies. This paper quantifies the disassembly time reductions required to achieve economic feasibility of systematic product disassembly. A modelling framework, based on linear programming, is used to investigate the effect of reducing the expected disassembly time and cost on the selection of the optimal End-of-Life strategy. The problem is optimized from an End-of-Life treatment facility point of view. All findings are based on the Belgian cost and price information captured in spring 2004. The linear programming model shows that for small products from the Waste of Electric and Electrical Equipment (WEEE) category disassembly-based End-of-Life strategies will hardly become optimal, while for medium- and large-sized products, this scenario can be made optimal if a substantial disassembly time reduction is achieved. Possible strategies to realize such reduction are briefly sketched.     

Capacitated disassembly scheduling with parts commonality and start-up cost and its industrial application

This paper discusses the capacitated disassembly scheduling with parts commonality and start-up cost, which has broad applications in remanufacturing and many other production systems. The problem is formulated as a mixed-integer programming model. A Lagrangian heuristic is developed, where the lower bound problem reduces to a linear model, and the upper bound can be obtained with a two-stage procedure in polynomial time. The algorithm is tested on randomly generated problems. The results reveal that the approach outperforms CPLEX significantly for all the test instances, and for real-scale problem it provides sufficiently good solutions within acceptable time. Sensitivity studies on capacity, parts commonality and start-up cost are also conducted, which provide some useful insights for industrial managers. Moreover, a real-world case from a valve disassembly factory is studied, which illustrates the application of the proposed approach and gives managerial insights. Finally, conclusions are drawn and some potential extensions are discussed.     

Optimization of transit network layout and headway with a combined genetic algorithm and simulated annealing method

This article proposes a methodology for optimizing transit networks, including both route structures and headways. Given information on transit demand, transit fleet size and street network in the transit service area, the methodology seeks to minimize transfers and total user cost while maximizing service coverage. The goal is to provide an effective mathematical solution procedure with minimal reliance on heuristics to solve large-scale transit network optimization problems. This article describes the representation of the transit route network and the associated network search spaces, the representation of route network headways and the associated search spaces, the total user cost objective functions, and a stochastic global search scheme based on a combined genetic algorithm and simulated annealing search method. The methodology has been tested with published benchmark problems and applied to a large-scale realistic network optimization problem. The results show that the methodology is capable of producing improved solutions to large-scale transit network design problems.     

Evaluation model and algorithm of product disassembly process with stochastic feature

Disassembly planning is considered as the optimization of disassembly sequences with the target of the shortest disassembly time, the lowest disassembly cost, and the minimum disassembly energy consumption. However, obsolete products suffer from the influence of a variety of uncertainties, the disassembly process of products has the strong uncertain feature. Traditionally, to account for this uncertainty, each removal operation or removal task is assumed to be an activity or event with certain probability, and the determination of the optimal path of a disassembly process is merely a probabilistic planning problem based on this assumption. In this article, based on the established stochastic disassembly network graph, combined with different disassembly decision-making criterion, typical stochastic models for disassembly time analysis are developed. In addition, a two-phase approach is proposed to solve the typical stochastic models. Initially, according to different removal probability density functions, disassembly probability density functions of feasible disassembly paths are determined by a time-domain method or frequency-domain method, and additionally, after the disassembly probability density functions have been obtained, the quantitative evaluation of a product disassembly process and stochastic optimization of feasible disassembly paths are realized by a numerical solution method. Finally, a numerical example is illustrated to test the proposed concepts and the effectiveness of the proposed approach.     

Selective disassembly sequencing with random operation times in parallel disassembly environment

Selective disassembly sequencing is the problem of determining the sequence of disassembly operations to extract one or more target components of a product. This study considers the problem with random operation times in the parallel disassembly environment in which one or more components can be removed at the same time by a single disassembly operation. After representing all possible disassembly sequences using the extended process graph, a stochastic integer programming model is developed for the objective of minimising the sum of disassembly and penalty costs, where the disassembly costs consist of sequence-dependent set-up and operation costs and the penalty cost is the expectation of the costs incurred when the total disassembly time exceeds a threshold value. A sample average approximation-based solution algorithm is proposed that incorporates an optimal algorithm to solve the sample average approximating problem under a given set of scenarios for disassembly operation times. The algorithm is illustrated with a hand-light case and a large-sized random instance, and the results are reported.     

Integrated assembly and disassembly sequence planning using a GA approach

In a product life cycle, an assembly sequence is required to produce a new product at the start, whereas a disassembly sequence is needed at the end. In typical assembly and disassembly sequence planning approaches, the two are performed as two independent tasks. In this way, a good assembly sequence may contradict the cost considerations in the disassembly sequence, and vice versa. In this research, an integrated assembly and disassembly sequence planning model is presented. First, an assembly precedence graph (APG) and a disassembly precedence graph (DPG) are modelled. The two graphs are transformed into an assembly precedence matrix (APM) and a disassembly precedence matrix (DPM). Second, a two-loop genetic algorithm (GA) method is applied to generate and evaluate the solutions. The outer loop of the GA method performs assembly sequence planning. In the inner loop, the reverse order of the assembly sequence solution is used as the initial solution for disassembly sequence planning. A cost objective by integrating the assembly costs and disassembly costs is formulated as the fitness function. The test results show that the developed method using the GA approach is suitable and efficient for the integrated assembly and disassembly sequence planning. Example products are demonstrated and discussed.     

Analyzing the effects of inventory cost setting rules in a disassembly and recovery environment

In this study we consider a disassembly and recovery facility receiving end-of-life products and facing demand for a specific part that is disassembled from the product and then recovered. The disassembly and recovery operations can be either performed before hand, or upon customer arrival. In the latter case, a discount on the selling price is applied to compensate the customer for waiting for the completion of the disassembly and recovery operations. One of the difficulties faced in planning for such a system is the determination of the opportunity cost associated with carrying recovered parts inventory. The difficulty arises in seeking the value added to the part given the costs incurred for maintaining the product return, disassembly and recovery costs and revenue earned from the hulk, that is the remaining product after the disassembly of the part. The main objective of the study is to investigate the effect of different rules to determine this opportunity cost on the performance of the system. Six rules are considered in the study. The performance of the rules is assessed by a computational study under an approximate inventory control policy.     

Effects of an Inaccurate Sorting Procedure on Optimal Procurement and Production Decisions in a Remanufacturing System

Under the uncertainty of market demand and quality of returns, sorting prior to disassembly is effective for timely obtaining information about the remanufacturability of used products. In this article, we assume that the remanufacturable fraction of used products is a random variable and introduce an inaccurate sorting procedure of used products prior to disassembly. Then, three two-stage optimization models are formulated to maximize the expected profits of a remanufacturer in a single period with used products and/or new parts as inputs to meet the stochastic market demand. Moreover, the article provides a case study to explore the optimal decisions under different scenarios and analyzes the effects of parameters, such as the unit disassembly cost, unit sorting cost, and proportion of sorting errors. Finally, the results indicate that whether remanufacturing with sorting is more profitable than that without sorting mainly depends on the sorting accuracy and the relative value between disassembly cost and sorting cost. When considering or not considering a long lead time of new parts, the effects of sorting errors on procurement policies are different. A long lead time will result in lower expected profits. Finally, the diverse types of classification errors have different influences on procurement policies and corresponding expected profit.     

基于模糊推理的不确定环境下拆卸工艺规划

回收产品因磨损等原因其结构和质量会发生改变,拆卸序列规划存在不确定性,拆卸前很难确定产品最优拆卸序列。首先建立一个模糊拆卸Petri网模型表示产品可行拆卸序列和拆卸过程存在的不确定信息,为降低产品质量和拆卸能力的不确定性对拆卸序列优化的影响,建立一个自适应的模糊推理系统,利用模糊推理和反馈学习的方法对产品各拆卸步骤的成本进行预测,然后通过计算不同拆卸序列下拆卸的收益来得到产品最优拆卸序列,最后通过算例证明了方法的有效性。     

A robust cell formation approach for varying product demands

In cellular manufacturing environments, manufacturing cells are generally formed based on deterministic product demands. In this paper, we consider a system configuration problem with product demands expressed in a number of probabilistic scenarios. An optimization model integrating cell formation and part allocation is developed to generate a robust system configuration to minimize machine cost and expected inter-cell material handling cost. A two-stage Tabu search based heuristic algorithm is developed to find the optimal or near optimal solutions to the NP-hard problem. Numerical examples show that this model leads to an appropriate compromise between system configuration costs and expected material handling costs to meet the varying product demands. These example problems also show that the proposed algorithm is effective and computationally efficient for small or medium size problems.     

Reverse supply chain optimisation with disassembly line balancing

Due to responding environmental issues, conforming governmental legislations and providing economic benefits, there has been a growing interest in recycling activities through the supply chains. Reverse supply chain (RSC) optimisation problem has a great potential as an efficient tactic to achieve this goal. While disassembly, one of the main activities in RSC, enables reuse and recycling of products and prevents the overuse, disassembly line balancing problem involves determination of a line design in which used products are partially/completely disassembled to obtain available components. The aim of this study is to optimise a RSC, involving customers, collection/disassembly centres and plants, that minimises the transportation costs while balancing the disassembly lines, which minimises the total fixed costs of opened workstations, simultaneously. A non-linear mixed-integer programming model, which simultaneously determines: (i) optimal distribution between the facilities with minimum cost, (ii) the number of disassembly workstations that will be opened with minimum cost, (iii) the cycle time in each disassembly centre and (iv) optimal assignment of tasks to workstations, is developed. A numerical example is given to illustrate the applicability of the proposed model. Different scenarios have been conducted to show the effects of sensitivity analyses on the performance measures of the problem.     

基于改进社会工程算法的拆解线平衡多目标优化设计

目的 为了提高拆卸效率,减少拆卸成本和拆卸能耗,提出一种基于社会工程算法的优化方法。方法 首先根据社会工程算法的原理设计了编码和解码方式,然后引入交换子和交换序列的概念,对算法中的训练和再训练、发现攻击和响应攻击等步骤进行设计,最后选取一个高速电子套结机作为实验对象进行了验证。结果 与其他多目标优化算法相比,具有良好的寻优能力。结论 提出的算法有效地解决了拆解线平衡问题,与其他算法相比具有更好的性能。     

产品回收处理的财务模型及其应用

根据结点式拆卸树，构建了拆卸成本的递推算法；运用基于作业的成本分析法，全面论述了零部件再用、材料再生、安全处置等产品废弃处理策略的成本与效益，建立了回收处理的财务分析模型，从经济上考察设计方案回收环节的经济合理性；并以PC机为例，进行收益变化和成本变化的敏感性分析。这将有利于量化分析成本动因，寻找关键作业成本项，指导企业改进产品设计。     

Mathematical model and solution algorithms for selective disassembly sequencing with multiple target components and sequence-dependent setups

This study considers selective disassembly sequencing under the sequential disassembly environment in which one component is obtained at each disassembly operation. The problem is to determine the sequence of disassembly operations to obtain multiple target components of a used or end-of-life product for the purpose of repair, reuse, remanufacturing, disposal, etc. In particular, we consider sequence-dependent setups in which setup costs depend on the disassembly operation just completed and on the operation to be processed. The problem is represented as a disassembly precedence graph and then a new integer programming model is suggested for the objective of minimising the total disassembly cost. After it is proved that the problem is NP-hard, we suggest two types of heuristics: (1) branch and fathoming algorithm for small-to-medium-sized instances; and (2) priority-rule-based algorithm for large-sized instances. A series of computational experiments, i.e., effectiveness of the new integer programming model and performances of the two heuristic types, were done on various test instances, and the results are reported. In addition, to show the applicability of the mathematical model and the solution algorithms, a case study is reported on an end-of-life electronic calculator.     

Disassembly line design with multi-manned workstations: a novel heuristic optimisation approach

As the first and the most time consuming step of product recovery, disassembly is described as the systematic separation of constituent parts from end-of-life products through a series of operations. In this context, designing and balancing disassembly lines are critical in terms of the efficiency of product recovery. Recent research on disassembly line balancing (DLB) has focused on classical stations where only one worker is allocated. However, such a line results in larger space requirement and longer disassembly lead time. In this paper, disassembly line balancing problem (DLBP) with multi-manned stations is introduced to the relevant literature as a solution to overcome these disadvantages. A mixed integer linear programming (MILP) model and two novel framework heuristic algorithms are developed to minimise the number of workers and workstations. MILP model has been applied to a dishwasher disassembly system. The application results indicate the superiority of establishing multi-manned stations over classical disassembly system design with single-worker stations with shorter disassembly lead time (80.9%) and line length (60.2%). Moreover, the proposed heuristics have been compared on newly generated test problems (instances) for DLBP. The results validate that the heuristics provide acceptable solutions in a reasonable amount of time even for large-sized problems.     

Multimaterial multijoint topology optimization

In this paper, a methodology that solves multimaterial topology optimization problems while also optimizing the quantity and type of joints between dissimilar materials is proposed. Multimaterial topology optimization has become a popular design optimization technique since the enhanced design freedom typically leads to superior solutions; however, the conventional assumption that all elements are perfectly fused together as a single piece limits the usefulness of the approach since the mutual dependency between optimal multimaterial geometry and optimal joint design is not properly accounted for. The proposed methodology uses an effective decomposition approach to both determine the optimal topology of a structure using multiple materials and the optimal joint design using multiple joint types. By decomposing the problem into two smaller subproblems, gradient‐based optimization techniques can be used and large models that cannot be solved with nongradient approaches can be solved. Moreover, since the joining interfaces are interpreted directly from multimaterial topology optimization results, the shape of the joining interfaces and the quantity of joints connecting dissimilar materials do not need to be defined a priori. Three numerical examples, which demonstrate how the methodology optimizes the geometry of a multimaterial structure for both compliance and cost of joining, are presented.     

Determining end-of-life policy for recoverable products

We address a problem that arises for an original equipment manufacturer (OEM) who produces a product both in new and remanufactured forms. A remanufactured product is produced using the parts harvested from recovered products (cores) upon their disassembly, and it may contain some new parts while the excess good parts from cores are salvaged for profit. Other options are available to the OEM for handling cores that do not require disassembly. It follows that the per-unit remanufacturing cost is not constant and it may change depending on the number of recovered cores, good-part reclamation yields, and sales of remanufactured products. We present analytical results for determining an optimal solution with regard to: (i) quantity of cores to collect, (ii) end-of-life (EOL) options for the cores and (iii) product pricing of new and remanufactured products. Our analysis reveals existence of a ‘limiting part’ that dictates the number of cores to collect and a ‘key part’ that determines the number of remanufactured products to make as well as the fact that the availability of cores does not impact the EOL policy type for a product. Our analysis also enables mapping of product characteristics onto corresponding EOL policy types.     

Modelling material separation processes in bulk recycling

Increasing environmental concerns about the disposal of mass produced products have resulted in efforts to recover value from components and materials before discarding such products. Methods include incineration, disassembly or de-manufacturing and bulk recycling. This paper investigates several cases of the problem of selecting the best sequence for recovery of materials by bulk recycling. A solution procedure for determining the optimal sequence for isolating all target materials present in a given batch based on dynamic programming is presented. A modification for targeting specific materials in a batch is discussed. Additional constraints arising from the operation of such facilities are also discussed. The general problem of target material identification is presented and a procedure for selecting a profitable target material mix, along with a numerical illustration, is documented. Finally, the integrated consideration of bulk recycling and disassembly for evaluating product disposal costs is presented.     

Minimum cost design of framed structures by the mini-max dual method

Minimum cost design of a framed structure is considered by using the mini-mas dual method. Stress and/or displacement constraints are imposed as behavioural constraints. The minimum cost design problem has a discrete objective function and discrete design variables. A sequence of approximate optimization problems in created by using the first-order Taylor series expansion for displacements with respect to the reciprocals of cross-sectional areas and moments of inertia. Each approximate problem is solved in the dual space. Two simple structural examples are given to show the appropriateness and efficiency of the proposed procedure. Approximate solutions are obtained within five structural analysis.     

A quantitative evaluation model to measure the disassembly difficulty; application of the semi-destructive methods in aviation End-of-Life

Sustainable decommissioning of aircraft with a high content of metallic and non-metallic components is a current challenge in the industry. This process has historically appeared to be economically, environmentally and socially unviable. Literature indicates that, unlike entirely destructive and totally non-destructive techniques, semi-destructive disassembly may bring significant benefits. However, despite their use in a wide variety of applications, there are currently no feasible solutions on how to measure the associated physical difficulties and required efforts without any dependencies on expert views or filling out spreadsheet-like forms. In this paper, a new model is developed to accurately evaluate the disassembly easiness of an airframe quantitatively incorporating both product and process features. Based on a real disassembly of a passenger jet, the cutting and thrust force vectors are selected to evaluate and find the best operation sets. An airliner Horizontal Stabiliser is analysed as a case study. The results indicate that minor drilling, as a hybrid operation, can reduce the disassembly efforts significantly while offering an increased material recovery chance. Such quantitative evaluation can help to: proceed with a viable End-of-Life strategy; and implement newer approaches like automated disassembly by designing better disassembly robots, tool selection and process control.