Flexible disassembly planning considering product conditions

To increase the economic benefit of product recovery at the end of life of a consumer product, the profit margins should be augmented. This can be realised by utilising the existing flexibility of today’s mostly manually-conducted disassembly processes. Moreover, with increased economic benefits, the recovery becomes even more attractive, which is also beneficial to the environment. A key component of product recovery is disassembly. Allowing different disassembly states (or levels) per core (i.e. recovered product) increases flexibility in planning. This should result in higher profits, as long as the flexibility is still manageable for the companies. This study focuses on flexible disassembly planning, i.e. the integration of sequencing aspects into disassembly (process) planning. In addition, we further incorporate the condition of items in the core, item damaging, purity requirements, special treatment of hazardous items and several limitations like core availability, item, module and material distribution, disposal and labour time limit. We base our developed mixed integer linear programme on graphs, such as the disassembly state graph for sequencing, and a hypergraph to model the core condition. Lastly, our considerations are illustrated by a numerical example.     

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.     

Interactive AR-assisted product disassembly sequence planning (ARDIS)

This paper presents a proof-of-concept novel near real-time interactive AR-assisted product disassembly sequence planning system (ARDIS) based on product information, such as interference matrix and 3D models. The system is developed using Unity and consists of three modules, including an intelligent disassembly sequence planning module, an automatic content authoring module and an intuitive augmented reality (AR) user interface (UI) with various features, such as a virtual panel for customisation and an option panel for sequence regeneration. Given the retrieval targets specified by a user, optimised disassembly sequences are computed using an evolutionary computing algorithm. For the sequences computed, the respective AR disassembly instruction sequences, such as 2D text instructions and animated 3D models, are generated dynamically based on a taxonomy that links each disassembly step in a sequence with the corresponding Unity templates that have been created beforehand. Hence, the need for manual authoring to provide AR disassembly guidance is reduced. If necessary, the user can request for alternative disassembly sequences which can be re-computed in near real-time. Several case studies have been carried out to demonstrate and evaluate the performance of the system within the laboratory environment.     

Eco-architecture analysis for end-of-life decision making

In order to improve ease of disassembly and recycling of a product at its retirement stage, it is essential to design a product architecture that allows for easy disassembly and recycling. In this paper, a novel concept of eco-architecture is introduced, and the eco-architecture analysis, a design approach supporting the end-of-life decision making process, is proposed. The eco-architecture is the product architecture described from the end-of-life (EOL) viewpoint, in which a product is represented as an assembly of end-of-life modules. Not only does it prescribe an EOL strategy, but it also gives information about the connections and arrangement among EOL modules. Therefore, understanding the eco-architecture is helpful in enhancing the disassembly and recycling capabilities of an architecture design. The proposed eco-architecture analysis supports architecture improvement; it helps designers to derive the most desirable eco-architecture which entails the optimal end-of-life strategy. It also facilitates the extraction of meaningful redesign guidelines which make it possible to improve an architecture in an efficient and effective manner.     

Dynamic disassembly planning for remanufacturing of multiple types of products

With the increased need for remanufacturing of end-of-life products, achieving economic efficiency in remanufacturing is urgently needed. The purpose of this study was to devise a cost-minimisation plan for disassembly and remanufacturing of end-of-life products returned by consumers. A returned end-of-life product is disassembled into remanufacturable parts, which are supposed to be used for new products after being remanufactured. Each end-of-life product is disassembled into parts at variable levels and through variable sequences as needed, taking into account not only disassembly but also manufacturing, remanufacturing, and holding inventory of remanufacturable parts. This study proposes a mixed integer linear programming (MILP) model for derivation of the optimal disassembly plan for each returned product, under deterministically known demand and return flows. For the purposes of an illustrative example, the proposed model was applied to the formulation of an optimal disassembly and remanufacturing plan of ‘fuser assembly’ of laser printers. The solution reveals that variable-level disassembly of products saves a significant remanufacturing cost compared with full disassembly.     

Disassembly process planning algorithms for end-of-life product recovery and environmentally conscious disposal

Disassembly process planning is an act of preparing detailed operation instructions for disassembling used or an end-of-life (EOL) product to recover or dispose of its constituent parts or subassemblies. The main decisions are: (a) disassembly level; (b) disassembly sequence; and (c) EOL options such as reuse, remanufacturing, recycling, incineration, landfill, etc. This study deals with the three decision variables simultaneously in the parallel disassembly environment for the objective of maximising the profit. Unlike previous studies, we consider practical constraints, i.e., reuse probability and environmental impacts of parts or subassemblies, sequence-dependent setup costs, regulation on recovery rate, and incineration capacity. To represent and solve the problem, we develop an extended AND/OR graph, and then suggest a two-phase algorithm. To show the effectiveness of the proposed algorithm, two case studies have been carried out on an automatic pencil and a telephone. Also, test results on other general product structures are reported.     

An improved co-evolutionary algorithm for green manufacturing by integration of recovery option selection and disassembly planning for end-of-life products

There is a strong need for recovery decision-making for end-of-life (EOL) products to satisfy sustainable manufacturing requirements. This paper develops and tests a profit maximisation model by simultaneously integrating recovery option selection and disassembly planning. The proposed model considers the quality of EOL components. This paper utilises an integrated method of multi-target reverse recursion and partial topological sorting to generate a feasible EOL solution that also reduces the complexity of genetic constraints handling. In order to determine recovery options, disassembly level and disassembly sequence simultaneously, this paper develops an improved co-evolutionary algorithm (ICA) to search for an optimal EOL solution. The proposed algorithm adopts the evolutionary mechanism of localised interaction and endosymbiotic competition. Further, an advanced local search operator is introduced to improve convergence performance, and a global disturbance strategy is also suggested to prevent premature convergence. Finally, this paper conducts a series of computational experiments under various scenarios to validate the meta-heuristic integrated decision-making model proposed and the superiority of the developed ICA. The results show that the proposed approach offers a strong and flexible decision support tool for intelligent recovery management in a ubiquitous information environment. We discuss the theoretical and practical contributions of this paper and implications for future research.     

Optimising end-of-life system dismantling strategy

The management of end-of-life systems is becoming a major concern for systems manufacturers, as the negative impact of these systems on the environment is a matter of increasing public awareness, and their appropriate treatment offers economic opportunities. In this context, the disassembly of these systems in order to recycle their components is a possible and sound option that can make it possible to sustain economical progress while respecting environment requirements. The work undertaken in this paper considers modelling and optimising issues of such disassembly activities. An integrated approach is proposed to model and optimise the selection of valuable components of end-of-life systems, their recycling options and the way to obtain them. Because the framework of such problems is highly uncertain, we propose the use of Bayesian networks and their extension in terms of influence diagrams as mathematical tools for structuring and managing uncertainties. With this approach, one can take into account uncertainties rising from different sources on one hand and as a support for optimisation on the other hand.     

Quantitative evaluation of product disassembly for recycling

This paper presents a method for evaluating the ease-of-disassembly of products. Its primary use is in designing products for recycling, but it also facilitates consideration of servicing and maintenance, and making environmentally-related decisions. The method is developed and discussed in the context of relatively small products that can be disassembled by a seated person using hand-held tools. The evaluation procedure is centered around a spreadsheet-like chart and uses a catalog of task difficulty scores. The scores were derived from work-measurement analyses of standard disassembly tasks, and provide a means of identifying weaknesses in the design and comparing alternatives quantitatively. The structure of the evaluation chart and the derivation of difficulty scores are explained, followed by a demonstration of analyzing a computer central processing unit. The limitations of the method and future extensions are outlined.     

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.     

A two-stage robust programming approach to demand-driven disassembly planning for a closed-loop supply chain system

The closed-loop supply chain system, which integrates forward and reverse logistics, is a desirable policy for retaining recoverable resources and extending the life cycles of products. In this study, we propose a methodology to contend with a demand-driven disassembly planning problem under a closed-loop supply chain system. A two-stage robust programming model is developed correspondingly, such that multiple products with a hierarchical product's structure are disassembled to satisfy uncertain demands in multiple periods. The objective of the model is to determine a robust decision for recycle volume and timing of each type of end-of-life (EOL) product, as well as recovery strategies. The results provide two-stage decisions by considering future scenarios of periodic demands at the beginning of a planning horizon. The first-stage decision is to determine a compromise solution that is close to the optimal solution for every scenario while retaining a certain level of infeasibility of constraints, such as unsatisfied demand. Afterward, when the outcome of a scenario has been realised, the second-stage decision, such as, inventory volume, is conducted to become a buffer for mitigating uncertain impacts. Furthermore, the computational results confirm the trade-off relationship between solution robustness and model robustness, which are core results of the robust model apart from expected profit. The different types of decision makers’ preferences toward risk can be accounted for to determine a compromise robust solution.     

An improved gravitational search algorithm for profit-oriented partial disassembly line balancing problem

Disassembly is indispensable to recycle and remanufacture end-of-life products, and a disassembly line-balancing problem (DLBP) is studied frequently. Recent research on disassembly lines has focused on a complete disassembly for optimising the balancing ability of lines. However, a partial disassembly process is widely applied in the current industry practice, which aims at reusing valuable components and maximising the profit (or minimising the cost). In this paper, we consider a profit-oriented partial disassembly line-balancing problem (PPDLBP), and a mathematical model of this problem is established, which is to achieve the maximisation of profit for dismantling a product in DLBP. The PPDLBP is NP-complete since DLBP is proven to be a NP-complete problem, which is usually handled by a metaheuristics. Therefore, a novel efficient approach based on gravitational search algorithm (GSA) is proposed to solve the PPDLBP. GSA is an optimisation technique that is inspired by the Newtonian gravity and the laws of motion. Also, two different scale cases are used to test on the proposed algorithm, and some comparisons with the CPLEX method, particle swarm optimisation, differential evolution and artificial bee colony algorithms are presented to demonstrate the excellence of the proposed approach.     

Automatic derivation of transition matrix for end-of-life decision making

Recently strengthened environmental regulations have obligated manufacturing companies to treat end-of-life (EOL) products both environmentally consciously and economically. EOL treatment begins with disassembling a product into recyclable or disposable sub-assemblies. Therefore, the economic value of an EOL product is largely a function of the plan for its disassembly: the means by which it is to be disassembled into smaller sub-assemblies, and the choice of sub-assemblies to be disassembled first. In order to make these decisions, a disassembly structure describing every possible sub-assembly division and its disassembly path from the original product has to be presented in a typical form. A widely used form of such a structure is a transition matrix. A transition matrix shows all feasible sub-assemblies and their disassembly hierarchy. Whereas it can be easily transformed into mathematical disassembly planning problem, the tedious work required for its generation limits its practical use. In this paper, we propose an algorithm for automatic derivation of a transition matrix. The proposed algorithm provides an efficient way to derive a transition matrix based on a product's architectural information, which includes the product's physical connections and the relative geometric locations between individual parts. The algorithm was validated in deriving a transition matrix of a car door-trim. Our algorithm can significantly expand the applicability of transition-matrix-based disassembly planning research.     

An approach for estimating the end-of-life product disassembly effort and cost

Disassembly is the process of physically separating a product into its parts or subassembly pieces. The overall economics of the disassembly process, and in particular the cost to disassemble, is still not well understood. In this paper our goal is to introduce a methodology that will support and facilitate the economic analysis of the disassembly activity. We present a multi-factor model to compute the disassembly effort index (DEI) score, which is representative of the total operating cost to disassemble a product. The DEI score can then be compared against the projected market value of the disassembled parts and subassemblies to get an economic measure. To develop the DEI model we surveyed a variety of commercial disassembly facilities. Based on these surveys we propose a multifactor weighted estimation scheme. The seven factors are (i) time, (ii) tools, (iii) fixture, (iv) access, (v) instruct, (vi) hazard, and (vii) force requirements. The DEI scale is defined in the 0 to 100 range. This range is assigned on a weighted basis to each of the seven factors. For each factor, an independent utility scale is formulated, using the assigned range as anchors. Using a conversion scale the DEI score is used to derive an estimate of disassembly cost and the disassembly return on investment. An example is presented.     

A heuristic procedure for the automobile assembly-line sequencing problem considering multiple product options

Mixed-model assembly nowadays is a common practice in the automobile industry. In an automobile assembly plant, many car options often need to be considered in sequencing an assembly line, for example, the multiple sequencing objectives that consider a pattern, blocking, spacing, and smoothing of options. A general heuristic procedure is developed in this paper for sequencing automobile assembly lines considering multiple options. The procedure obtains an initial sequence by an enhanced constructive procedure, swaps orders for the most deteriorating category of objectives, and performs re-sequencing attempting to improve the swapped sequence. The heuristic procedure was shown to frequently improve the initial sequences by swapping and re-sequencing when swapping opportunities exist. A further improvement step is also proposed to perform a limited search based on the swapped solution. The limited-search improvement step was shown to be effective in further improving solutions from the heuristic procedure in the computational experimentation. Solutions from the heuristic procedure in conjunction with the limited-search improvement step were compared to those from the simulated annealing procedure for large-size problems and showed relatively positive results.     

Integrated approach for disassembly processes generation and recycling evaluation of an end-of-life product

An integrated approach for noble recycling is presented that puts forward the functional value of products and components. In a first step, the approach determines all feasible automatic disassembly sequences and in a second step all applicable recycling activities. This allows one to determine the most appropriate recycling process for an end-of-life product considering concurrent recycling techniques. The feasible automatic disassembly sequences are established by simulation in a virtual environment. The required generic disassembly product model, as well as the generic disassembly activity model, is presented by means of static and dynamic object-oriented diagrams. The recycling evaluation establishes an efficient solution responding to economic and ecological decision criteria. It is calculated applying a Goal-Programming approach transforming the multi-objective linear problem into a monocriteria linear program. The techno-economic decision model applied is Linear Activity Analysis. It allows one to integrate the generated disassembly processes based on single disassembly activities as well as other recycling techniques.