The online quality control methods for the assembling of remanufactured engines’ cylinder block and cover under uncertainty

Ge, Maogen; Liu, Conghu; Liu, Mingzhou

doi:10.1007/s00170-014-5971-8

Cited by 16 publications

(10 citation statements)

References 23 publications

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“…In view of this, this paper is based on information entropy to quantify a description of the uncertainty of remanufactured parts, and the entropy is substituted by the assembly dimension chain to measure the uncertainty Entropy 2016, 18, 348 3 of 11 of the remanufacturing assembly. Related research literature [5][6][7][8]10,11] shows that the value of the uncertainty of remanufacturing assembly is a quantitative description of the reassembly precision in the remanufacturing process, which largely reflects the quality of the remanufactured products.…”

Section: General Overviewmentioning

confidence: 99%

“…Related research literature [5][6][7][8]10,11] shows that the value of the uncertainty of remanufacturing assembly is a quantitative description of the reassembly precision in the remanufacturing process, which largely reflects the quality of the remanufactured products. In the remanufacturing assembly process, the reused parts, remanufactured parts and original parts in terms of quality and cost are different.…”

Section: General Overviewmentioning

confidence: 99%

“…The study of assembly control in remanufacturing is as follows: Ge [8] studied the online quality control methods in the reassembly process for remanufactured engines' cylinder blocks and covers. The optimal control strategy of product reorganization in the remanufacturing system with variable quality returns was studied by Jin [9].…”

Section: Introductionmentioning

confidence: 99%

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Tolerance Redistributing of the Reassembly Dimensional Chain on Measure of Uncertainty

Liu

2016

Entropy

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How to use the limited precision of remanufactured parts to assemble higher-quality remanufactured products is a challenge for remanufacturing engineering under uncertainty. On the basis of analyzing the uncertainty of remanufacturing parts, this paper takes tolerance redistributing of the reassembly (remanufactured assembly) dimensional chain as the research object. An entropy model to measure the uncertainty of assembly dimensional is built, and we quantify the degree of the uncertainty gap between reassembly and assembly. Then, in order to make sure the uncertainty of reassembly is not lower than that of assembly, the tolerance redistribution optimization model of the reassembly dimensional chain is proposed which is based on the tolerance of the grading allocation method. Finally, this paper takes the remanufactured gearbox assembly dimension chain as an example. The redistribution optimization model saves 19.11% of the cost with the assembly precision of remanufactured products. It provides new technical and theoretical support to expand the utilization rate of remanufactured parts and improve reassembly precision.

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Section: General Overviewmentioning

confidence: 99%

Section: General Overviewmentioning

confidence: 99%

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Tolerance Redistributing of the Reassembly Dimensional Chain on Measure of Uncertainty

Liu

2016

Entropy

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“…Complex mechanical products (CMPs) consist of a large number of different types of components and parts, featuring complex design, long R&D cycles, complex coupling between parts, and high manufacturing costs . At present, many studies have performed in‐depth research on the design, remanufacturing, and assembly of CMPs, which often involve the study of influential components and parts . Research on the influential parts of a CMP shows that the influential parts are the core of the product architecture and are of great importance to the reliability of a CMP.…”

Section: Introductionmentioning

confidence: 99%

Identification of the influential parts in a complex mechanical product from a reliability perspective using complex network theory

Yin

Dong

et al. 2019

Quality & Reliability Eng

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Due to the difference in the numbers and strengths of physical relationships among parts, complex mechanical products (CMPs) have community structure characteristics. There are often some influential parts in the community. Failures of these influential parts spread rapidly along the physical relationships between parts in the community, which seriously affects the reliability of a product. Therefore, identifying the influential parts in the community and adopting targeted measures can effectively improve the reliability and service life of a product. However, identifying the influential parts within each community in a collection of parts with complex relationships is very difficult. Thus, from the perspective of reliability, a method for identifying the influential parts of a CMP based on complex network theory is proposed and used to identify the influential parts in each community of products. First, weighted complex network (WCN) theory is employed to construct a CMP into a WCN model. Second, the complex network community detection method is employed to detect the community structure of the WCN model. Third, a modified LocalRank algorithm is employed to identify the influential nodes in each community, ie, the influential parts in each community of a CMP. Fourth, a modified susceptible‐infectious‐recovered (SIR) model is employed to evaluate the impacts of the influential parts. An analysis of a company's DC drill planetary gearbox shows that the proposed method is accurate and effective.

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“…In the study of the uncertainty of reassembly, Liu et al (2015) studied the uncertainty measure method of remanufacturing crankshaft surface roughness and established the uncertainty and the quality of the engine gray relational mapping model. Subsequently, GE et al (2014) built the uncertainty measurement model for the key factors of the airtightness of remanufacturing engine cylinder head and put forward the online quality control method of remanufacturing engine cylinder head seal. Hu et al (2016) established a remanufacturing assembly precision control method based on the state space model.…”

Section: Introductionmentioning

confidence: 99%

The coupling mechanism of reassembly quality with uncertainty of remanufactured parts

Zhang

Liu

et al. 2019

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Purpose The uncertainty of remanufacturing parts is a key factor affecting the quality of remanufactured products. Therefore, the purpose of this paper is to measure the uncertainty of remanufactured parts and study the coupling mechanism of reassembly quality. Design/methodology/approach First, uncertainty of remanufactured parts is analyzed, and the uncertainty measure model for remanufacturing parts based on entropy is constructed. Second, the nonlinear mapping model between the uncertainty and reassembly quality were studied using Gauss-Newton iterative method to reveal the coupling mechanism between uncertainty of remanufacturing parts and reassembly quality. Finally, the model is verified in the reassembly process of remanufacturing cylinder head. Findings The method can guide reassembly operations to improve the reassembly quality with uncertainty of remanufactured parts. Originality/value This study provides practical implications by developing a multivariate nonlinear mapping model for reassembly quality based on entropy to determine the uncertainty factors that affect the reassembly quality significantly and then correct the reassembly operation to better optimize the allocation of remanufacturing production resources. The study also theoretically contributes to reveal the coupling mechanism of reassembly quality with the uncertainty of remanufactured parts.

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The online quality control methods for the assembling of remanufactured engines’ cylinder block and cover under uncertainty

Cited by 16 publications

References 23 publications

Tolerance Redistributing of the Reassembly Dimensional Chain on Measure of Uncertainty

Tolerance Redistributing of the Reassembly Dimensional Chain on Measure of Uncertainty

Identification of the influential parts in a complex mechanical product from a reliability perspective using complex network theory

The coupling mechanism of reassembly quality with uncertainty of remanufactured parts

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