Modeling automatic assembly and disassembly operations for virtualmanufacturing

A system for evaluating products in their design phase has been developed for virtual manufacturing. It is integrated into a CAD/CAM environment to calculate the cost for assembling and disassembling parts. In our earlier work, a generic assembly and disassembly model was developed to represent operations required for product manufacturing and de-manufacturing. To be useful, the model requires a method for translating high-level instructions from product designers into low-level assembly and disassembly instructions. This paper presents a set of rules for accomplishing this task. The developed rules are used for manipulating strings representing parts and handlers in binary assembly and disassembly operations. A telephone assembly and disassembly simulation is used to illustrate the developed system     

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.     

Comments on the erratum to “Supply planning model for remanufacturing system in reverse logistics environment” [Comput. Ind. Eng. 51 (2006) 279–287]

To maximize the total cost of savings, a mixed-integer programming model for remanufacturing proposed by Kim et al. [Kim, K., Song, I., Kim, J., & Jeong, B. (2006). Supply planning model for remanufacturing system in reverse logistics environment. Computers & Industrial Engineering, 51, 279–287] was published in Computers & Industrial Engineering journal to decide optimally the quantity of parts to be processed at each remanufacturing facilities, the number of purchased parts from subcontractor. In this work, comments and suggestions are given to the published model of Kim, Song, Kim, and Jeong (2006). Comments like partial and complete disassembly, disassembly cost, optimum level of disassembly and finally, the modification of constraints are suggested in this work.     

Issues in environmentally conscious manufacturing and product recovery: a survey

Environmentally Conscious Manufacturing and Product Recovery (ECMPRO) has become an obligation to the environment and to the society itself, enforced primarily by governmental regulations and customer perspective on environmental issues. This is mainly driven by the escalating deterioration of the environment, e.g. diminishing raw material resources, overflowing waste sites and increasing levels of pollution. ECMPRO involves integrating environmental thinking into new product development including design, material selection, manufacturing processes and delivery of the product to the consumers, plus the end-of-life management of the product after its useful life. ECMPRO related issues have found a large following in industry and academia who aim to find solutions to the problems that arise in this newly emerged research area. Problems are widespread including the ones related to life cycle of products, disassembly, material recovery, remanufacturing and pollution prevention. In this paper, we present the development of research in ECMPRO and provide a state-of-the-art survey of published work.     

再制造/制造系统集成物流网络扩展模型研究

研究了再制造／制造系统集成的物流网络扩展模型，给出了其选址一分配模型．该模型特点是：网络结构为闭环网络；正向物流中统筹考虑再生品和新产品的物流分配，再生品和新产品不能相互替代；解决了新建装配厂、存储批发商及拆解中心的选址问题．     

Production planning and control for remanufacturing: a state-of-the-art survey

Remanufacturing is rapidly emerging as an important form of waste prevention and environmentally conscious manufacturing. Firms are discovering it to be a profitable approach while at the same time enhancing their image as environmentally responsible, for a wide range of products. In this paper the characteristics of the remanufacturing environment are discussed first to distinguish this environment from other manufacturing environments. The production planning and control function of the remanufacturing firm is examined in this environment. The research in the various decision-making areas that comprise the production planning and control function is evaluated. There are many areas where the research is still scant. The lack of any overall integrated framework and models for the production planning and control function is noted. It is also pointed out that most firms are still grappling with these problems and do not have any formal mechanisms in place. There is a need to develop models and frameworks grounded in the problems and needs of these remanufacturing firms.     

A path-relinking approach for a bi-criteria disassembly sequencing problem

The first crucial step of product recovery is disassembly. Some product disassembly is almost always needed in remanufacturing, recycling, and disposal. Since disassembly tends to be expensive, disassembly sequence planning becomes important in minimizing resources (time and money) invested in disassembly and maximizing the level of automation. A disassembly sequence plan (DSP) is a sequence of disassembly tasks, which begins with a product to be disassembled and terminates in a state where all of the parts of interest are separated. The decision version of the problem of finding the optimal DSP is an NP-complete problem and therefore complex and challenging to solve. Often one has to resort to heuristic and metaheuristic techniques for solving such problems. In this paper, we seek a DSP that addresses two criteria in order. First, we look for a sequence, the cost of which is close to our cost aspiration. Second, we look for a sequence that prioritizes some selected parts to be disassembled as early as possible. We propose a greedy randomized adaptive search procedure (GRASP) and path-relinking-based heuristic methodology specifically developed to solve such bi-criteria type of disassembly problem. An example is considered to illustrate the implementation of the methodology. Conclusions drawn include the consistent generation of near-optimal solutions, the ability to preserve precedence, the superior speed of the metaheuristic, and its practicality due to its ease of implementation.     

Stochastic models and numerical solutions for manufacturing/remanufacturing systems with applications to the printer cartridge industry

This paper investigates the production rates control of a hybrid manufacturing/remanufacturing system in a closed-loop environment, with application to the printer cartridge industrial sector. The system studied comprises manufacturing and remanufacturing factories working in parallel, and subject to random failures and repairs. The failure rate of the manufacturing factory depends on its production rate, while the failure rate is constant for the remanufacturing factory. Given the dependence of the failure rate on the production rate of the manufacturing factory, a non-homogeneous Markov process is used to describe the dynamics of the overall production system. The objective of the control problem concerns the minimization of a cost function which penalizes the presence of waiting customers, the inventory of finished parts, and the inventory of parts returned from customers upon reaching the end of their lives. Using a real business case study adapted from a leading European company producing printer cartridges, we obtain the optimal production policies for the both factories. Sensitivity analyses are conducted to illustrate the usefulness of the proposed approach and its applicability to other cases.     

Disassembly sequence planning using discrete Bees algorithm for human-robot collaboration in remanufacturing

Remanufacturing helps to improve the resource utilization rate and reduce the manufacturing cost. Disassembly is a key step of remanufacturing and is always finished by either manual labor or robots. Manual disassembly has low efficiency and high labor cost while robotic disassembly is not flexible enough to handle complex disassembly tasks. Therefore, human-robot collaboration for disassembly (HRCD) is proposed to flexibly and efficiently finish the disassembly process in remanufacturing. Before the execution of the disassembly process, disassembly sequence planning (DSP), which is to find the optimal disassembly sequence, helps to improve the disassembly efficiency. In this paper, DSP for human-robot collaboration (HRC) is solved by the modified discrete Bees algorithm based on Pareto (MDBA-Pareto). Firstly, the disassembly model is built to generate feasible disassembly sequences. Then, the disassembly tasks are classified according to the disassembly difficulty. Afterward, the solutions of DSP for HRC are generated and evaluated. To minimize the disassembly time, disassembly cost and disassembly difficulty, MDBA-Pareto is proposed to search the optimal solutions. Based on a simplified computer case, case studies are conducted to verify the proposed method. The results show the proposed method can solve DSP for HRC in remanufacturing and outperforms the other three optimization algorithms in solution quality.     

增材再制造产业的现状与发展

增材再制造基于增材制造技术,能实现零部件损伤部位尺寸恢复和零部件性能恢复或提升,是一种颠覆性新加工技术.该技术对关键产业起到赋能作用,能够促进产业高质量发展.针对金属增材再制造技术,具体阐述了激光增材再制造、电弧增材再制造和电子束增材再制造技术的工艺特点,并详细地分析了增材再制造技术在钢铁冶金、船舶、航空航天、电力、交...     

Disassembly sequence structure graphs: An optimal approach for multiple-target selective disassembly sequence planning

Modern green products must be easy to disassemble. Specific target components must be accessed and removed for repair, reuse, recycling, or remanufacturing. Prior studies describe various methods for removing selective targets from a product. However, solution quality, model complexity, and searching time have not been considered thoroughly. The goal of this study is to improve solution quality, minimize model complexity, and reduce searching time. To achieve the goal, this study introduces a new ‘disassembly sequence structure graph’ (DSSG) model for multiple-target selective disassembly sequence planning, an approach for creating DSSGs, and methods for searching DSSGs. The DSSG model contains a minimum set of parts that must be removed to remove selected targets, with an order and direction for removing each part. The approach uses expert rules to choose parts, part order, and part disassembly directions, based upon physical constraints. The searching methods use rules to remove all parts, in order, from the DSSG. The DSSG approach is an optimal approach. The approach creates a high quality minimum-size model, in minimum time. The approach finds high quality, practical, realistic, physically feasible solutions, in minimum time. The solutions are optimized for number of removed parts, part order, part disassembly directions, and reorientations. The solutions remove parts in practical order. The solutions remove parts in realistic directions. The solutions consider contact, motion, and fastener constraints. The study also presents eight new design rules. The study results can be used to improve the product design process, increase product life-cycle quality, and reduce product environmental impact.     

Disassembly Sequence Planning: A Survey

It is well-recognized that obsolete or discarded products can cause serious environmental pollution if they are poorly be handled. They contain reusable resource that can be recycled and used to generate desired economic benefits. Therefore, performing their efficient disassembly is highly important in green manufacturing and sustainable economic development. Their typical examples are electronic appliances and electromechanical/mechanical products. This paper presents a survey on the state of the art of disassembly sequence planning. It can help new researchers or decision makers to search for the right solution for optimal disassembly planning. It reviews the disassembly theory and methods that are applied for the processing, repair, and maintenance of obsolete/discarded products. This paper discusses the recent progress of disassembly sequencing planning in four major aspects: product disassembly modeling methods, mathematical programming methods, artificial intelligence methods, and uncertainty handling. This survey should stimulate readers to be engaged in the research, development and applications of disassembly and remanufacturing methodologies in the Industry 4.0 era.      

A study on remanufacturing possibility of a product

With the intensification of Globalization, customers’ environment-friendly attitude and stringent environmental regulations, the manufacturers have been orienting their manufacturing and other value additive processes towards the development of more environment-friendly products and use of relevant processes including taking back of used products after their end-of-use or end-of-life from the end users. Remanufacturing is one of the prominent and popular options. Remanufacturing perhaps has drawn maximum attention because of its economic viability and environmental cleanliness. The remanufacturing operation depends upon the quality and quantity of the used. Better the quality lesser the remanufacturing cost. A remanufacturer is unaware about the condition of used product before its acquisition. It may also be noted that the remanufactured product may be taken after a period of its use by users. So it is really difficult to judge how many cycles does the product go for remanufacturing. This has drawn the attention of the authors and the problem is studied with developing some mechanism on the possible frequency of the remanufacturing of a new product. This paper is a study report on this area of research which is expected to contribute immensely to the remanufacturing business.

     

基于可变长工序编码的再制造生产调度优化方法*

回收品质量、数量以及拆卸过程中的不确定性因素使再制造生产调度问题更加复杂。针对工件加工路径的可变性特点,建立了再制造生产中的job-shop调度模型,提出了一种基于可变长工序编码方法的改进遗传算法,设计了异常染色体的识别和重构方法,以及相应的遗传算子。在参数矩阵的指导下,该算法可以实现随机工序数目和随机工序顺序情况下再制造生产调度问题的优化求解。仿真实验证明了该算法的有效性和可行性。     

A new environment-aware scheduling method for remanufacturing system with non-dedicated reprocessing lines using improved flower pollination algorithm

As the resource crisis and environmental pollution become increasingly prominent, remanufacturing is currently a popular research field for addressing these issues. However, scheduling for remanufacturing is more difficult than that for traditional manufacturing because the entire remanufacturing system (RMS) involves three cooperative subsystems: disassembly, reprocessing, and reassembly. Few studies have focused on the scheduling of the entire RMS and addressed the quality differences of defective components using non-dedicated reprocessing lines. Thus, this paper proposes a new environment-aware scheduling model for RMS, which considers not only three subsystems simultaneously, but also the non-dedicated reprocessing lines related to the recycled quality of defective components. The proposed model also integrates environmental factors by considering the carbon emissions of machines to take advantage of the environmental benefits in remanufacturing. To solve the proposed model, an improved flower pollination algorithm with new two-dimensional representation scheme is employed, which not only utilizes the self-adaptive parameter but also integrates path relinking technique, local search strategy, and elite replacement strategy. Experiments are performed to illustrate the effectiveness of the proposed algorithm for solving the remanufacturing scheduling problem by comparing it with six baseline algorithms.     

Multi-objective partial disassembly optimization based on sequence feasibility

A sustainable manufacturing system integrates production systems, consumer usage behavior, and End-of-Life (EoL) product value recovery activities. Facilitating multi-objective disassembly planning can be a step toward analyzing the tradeoffs between the environmental impact and profitability of value recovery. In this paper, a Genetic Algorithm (GA) heuristic is developed to optimize partial disassembly sequences based on disassembly operation costs, recovery reprocessing costs, revenues, and environmental impacts. EoL products may not warrant disassembly past a unique disassembly level due to limited recovered component market demand, minimal material recovery value, or minimal functional recovery value. The effectiveness of the proposed GA is first verified and tested using a simple disassembly problem and then applied to the traditional coffee maker disassembly case study. Analyses are disaggregated into multiple disassembly network optimization problems, one for each product subassembly, resulting in a bottom-up approach to EoL product partial disassembly sequence optimization.     

A virtual prototyping approach to product disassembly reasoning

An important aspect of Design for the Life Cycle is assessing the disassemblability of products. After an artifact has completed its useful life, it must be disassembled then recycled, remanufactured or scrapped. Disassemblability of a product can be evaluated by performing disassembly activities on prototypes. Virtual prototyping (VP) is an alternative to hardware prototyping in which analysis of designs can be done without manufacturing physical samples. In recent years, disassembly processes have been generated either by using interactive or automated approaches, but these approaches have limitations. Interactive approaches require extensive user input usually in the form of answering questions, whereas automated approaches can only be used to generate disassembly processes for products with simple component configuration and geometry. In this paper automated and interactive techniques are combined, using VP, to generate complete disassembly processes of a product design. To support generation of disassembly processes of a product, a virtual environment and VP method were developed that will support disassembly activities performed by a designer. The product model of the virtual prototype is generated from the CAD model. The disassembly process model for the prototype is generated using automated reasoning techniques and is completed by interactively disassembling the product in the virtual environment. Extensions to automatic reasoning techniques to compute ranges of feasible directions of component removal were developed to facilitate the generation of the disassembly process. A scheme to represent the disassembly process for disassemblability evaluation was developed and implemented. In this paper a Chrysler LHS center console has been used to illustrate our approach of generating disassembly processes via VP.     

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.     

Service Platform for Robotic Disassembly Planning in Remanufacturing

Remanufacturing is being paid much attention due to environmental protection and resource re-utilization. Disassembly is an inevitable step of remanufacturing and it is always finished by the manual labor. Robotic disassembly helps to improve the automation of disassembly process, while robotic disassembly planning helps to improve the efficiency of robotic disassembly. However, the existing research on robotic disassembly planning seldom integrates the physical industrial robots and then provides convenient services for the users. In this paper, the framework of service platform for robotic disassembly planning in remanufacturing is studied. The database of the service platform is designed, and the data communication method between the software system and KUKA industrial robots is studied. After that, based on the physical facilities, this service platform is implemented using MyEclipse software. The developed service platform is convenient for the users to access the methods of robotic disassembly planning and the connected industrial robots can also execute the optimal disassembly solutions through the data communication method after the optimal disassembly solutions are obtained. Finally, case study based on an idler shaft is conducted to verify the developed service platform for robotic disassembly planning.     

Heuristics for demand-driven disassembly planning

Remanufacturing of used products has become accepted as an advantageous disposition option within the field of reverse logistics. Remanufacturing, where a firm takes returned products at the end of their life and disassembles them to obtain parts which are reassembled into “good as new” products, may require so-called demand-driven- disassembly, where a specific amount of returned products must be disassembled to yield parts which are either demanded externally, or used in the remanufacturing operation. While in its simplest form, the solution can be merely calculated, more realistically complex product structures require a more powerful solution method. The first choice, integer programming (IP) can be used to arrive at an optimal solution, with the disadvantage that the time required to solve the problem explodes with increasingly complex product structures and longer time horizons. Another possible method, heuristics which were presented in a previous work on this problem [Taleb and Gupta (Computers & Industrial Engineering 1997; 32(4): 949–61], offer a faster, easier solution with the disadvantage that it is not necessarily optimal, and under certain circumstances may deliver an infeasible result. In this work, this problem was corrected and the heuristic was extended in several important ways to deal with holding costs and external procurement of items. The methodology is illustrated by an example. Another advantage of the heuristic is that it can be programmed into code and executed via spreadsheet application, which will facilitate its application. A performance study reveals that the new heuristic performs quite well for a wide spectrum of randomly generated problem test instances.