A knowledge-based method for eco-efficiency upgrading of remanufacturing process planning

Chen, Daojia; Jiang, Zhigang; Zhu, Shuo; Zhang, Hua

doi:10.1007/s00170-020-05025-2

Cited by 16 publications

(10 citation statements)

References 23 publications

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“…Remanufacturing is a green manufacturing technology that can effectively utilize used products and has become an important contributor to the development of a circular economy [1]. The remanufacturing of used products provides products of the same quality as new ones, and effectively reduces economic input, resource consumption and environmental pollution [2]. However, the current raw materials for remanufacturing (cores) are mainly derived from scrapped products, which denotes typical end-of-life cycle remanufacturing [3].…”

Section: Introductionmentioning

confidence: 99%

Timing Decision for Active Remanufacturing Based on 3E Analysis of Product Life Cycle

et al. 2022

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Active remanufacturing is an important technique that is used to reduce the uncertainty of the quality of remanufactured cores. However, the implementation of active remanufacturing too early or late will lead to a reduction in economic benefits and an increase in environmental impact during the whole life cycle of the product. To this end, an active-remanufacturing-timing decision method is proposed based on an economic, energy and environmental (3E) analysis of product life cycle. In this method, the quantitative function of the cost, energy consumption and environmental emissions of used products in the manufacturing stage, service stage, and remanufacturing stage are firstly constructed based on life-cycle assessment (LCA) and life-cycle cost (LCC). Then, a multi-objective optimization method and the particle swarm algorithm are utilized to obtain active-remanufacturing timing with the optimal economic and environmental benefits of remanufacturing. Finally, a case study on remanufacturing on used engines is demonstrated to validate the proposed method.

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Section: Introductionmentioning

confidence: 99%

Timing Decision for Active Remanufacturing Based on 3E Analysis of Product Life Cycle

et al. 2022

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“…As customer demand becomes more personalized, modern manufacturing prefers the production mode with multiple varieties and small batches. Hence, industries require a more efficient process planning method to rapidly respond to changing market demands [1], [2].…”

Section: Introductionmentioning

confidence: 99%

“…This constraint is also called the quantity constraint. (2) The radius of a cluster, i.e., the maximal distance between the process route and its exemplar in one cluster, should be smaller than ε, which is the maximum radius of a valid process route cluster. This constraint is also called the size constraint.…”

Section: Introductionmentioning

confidence: 99%

A Novel Operation Sequence Similarity-Based Approach for Typical Process Route Knowledge Discovery

Wang

2021

IEEE Access

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A typical process route essentially represents the commonly used process planning-related knowledge and can be modified to generate new process routes easily. Hence, its quality directly affects the performance of newly generated process routes and thereby the goodness of products. To effectively discover typical process route knowledge, a reasonable similarity measure and a clustering method specifically for process routes are required. However, existing operation sequence similarity coefficients often assign coarse-grained similarities, which leads to inaccurate clustering results. For the clustering problem, most researchers have not considered the practical constraints during typical process route discovery. In this paper, an operation sequence similarity-based discovery method is presented. First, the characteristics and information requirements of the operation sequence similarity problem are analysed, and a novel comprehensive similarity coefficient combined with a modified pseudo-longest-commonsubsequence (pseudo-LCS) and Jaccard similarity coefficient is proposed based on this analysis. This coefficient considers the precedence relationship, the number of common operations, and the operation similarity simultaneously to handle all the potential similarity situations. Second, two soft constraints, namely, quantity constraint and size constraint, are introduced in the traditional process route clustering problem to ensure the quality and validity of the discovered typical process routes. To solve this more practical problem and achieve a balance between these two conflicting constraints, the K-medoids method is improved with an adjustment mechanism to generate valid results under these two soft constraints. Finally, numerical illustrations are presented to verify the effectiveness of the proposed methods. The results show that compared with existing similarity coefficients, the proposed comprehensive similarity coefficient is more sensitive and much better at distinguishing the tiny difference between the process routes. In addition, the modified K-medoids method can perform much better than existing methods on process route discovery data sets under two conflicting soft constraints.

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“…In general, the common failure modes of used parts include fracture, wear, and deformation, which account for more than 75% of the total failures of parts [8,9]. Owing to the long-term service, wear, and loss of technical documentation, it is difficult to obtain the technical information of the parts, which results in differences in remanufacturing schemes and affects the quality of remanufacturing [10][11][12][13][14]. At present, the design of remanufacturing schemes is still based on personnel experience and manuals, which leads to difficulties in remanufacturing efficiency, cost, and energy consumption, and there are a series of scientific problems that need to be solved [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Remanufacturing Scheme Design for Used Parts Based on Incomplete Information Reconstruction

Huang

Jiang

Wang

et al. 2020

Chin. J. Mech. Eng.

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The different conditions of use of a component result in a variety of damage levels. Therefore, excluding differences in shape and size, used parts show a high degree of uncertainty regarding failure characteristics, quality conditions, and remaining life, which seriously affects the efficiency of a remanufacturing scheme design. Aiming to address this problem, a remanufacturing scheme design method based on the reconstruction of incomplete information of used parts is proposed. First, the remaining life of the reconstructed model is predicted by finite element analysis, and the demand for the next life cycle is determined. Second, the scanned 3D damage point cloud data are registered with the original point cloud data using the integral iterative method to construct a missing point cloud model to achieve the restoration of geometric information. Then, according to reverse engineering and laser cladding remanufacturing, the tool remanufacturing process path can be generated by the tool contact point path section line method. Finally, the proposed method is adopted for turbine blades to evaluate the effectiveness and feasibility of the proposed scheme. This study proposes a remanufacturing scheme design method based on the incomplete reconstruction of used part information to solve the uncertain and highly personalized problems in remanufacturing.

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A knowledge-based method for eco-efficiency upgrading of remanufacturing process planning

Cited by 16 publications

References 23 publications

Timing Decision for Active Remanufacturing Based on 3E Analysis of Product Life Cycle

Timing Decision for Active Remanufacturing Based on 3E Analysis of Product Life Cycle

A Novel Operation Sequence Similarity-Based Approach for Typical Process Route Knowledge Discovery

Remanufacturing Scheme Design for Used Parts Based on Incomplete Information Reconstruction

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