Three-dimensional variation propagation modeling for multistage turning process of rotary workpieces

Du, Shichang; Yao, Xufeng; Huang, Delin; Wang, Meng

doi:10.1016/j.cie.2015.01.010

Cited by 33 publications

(11 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Du et al established a three-dimensional change transmission model of rotating work pieces, which described benchmark errors, fixture errors, etc. [30]. Wang et al established a new variation transmission model in multistage machining processes for general shape work pieces.…”

Section: Literature Reviewmentioning

confidence: 99%

Quality Risk Propagation of Complex Product Collaborative Manufacturing Supply Chain Network Based on CN and SoV

Chen

Yuan

et al. 2020

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

The collaborative development of complex products has gradually developed into a “main manufacturer-suppliers” mode, under which the manufacturing enterprises form a complex product collaborative manufacturing supply chain network. Quality risks which bring enormous hidden danger to the product quality can be propagated and accumulate along the supply chain. It is of great significance to quantify the propagation mechanism of quality risk between supply chain network nodes and identify the key quality risk factor that causes fluctuation of product quality. This study for the first time applies the SoV into the research on quality risk propagation of complex product collaborative manufacturing supply chain network. Firstly, this paper uses the CN to construct a complex product collaborative manufacturing supply chain network according to its characteristics. Secondly, on the basis of SoV, the quality risk propagation model is established. Thirdly, we put forward a method to identify the key quality risk factors of supply chain network based on the risk propagation effect. Lastly, a numerical simulation is given to verify the effectiveness of the model and its identification method. The results reveal that the quality risk propagation includes the vertical propagation within enterprises and the horizontal propagation from the lower-level enterprises to the upper-level enterprises of the supply chain. The quality risks of an enterprise are determined by its own quality risk factors and the quality risk passed by the lower-level enterprises.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Quality Risk Propagation of Complex Product Collaborative Manufacturing Supply Chain Network Based on CN and SoV

Chen

Yuan

et al. 2020

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

show abstract

“…The point-based variation propagation model integrated the effects of locating errors, geometric errors of machine tool, and tool deflection on workpiece deviation. Based on differential motion vectors for datum error and fixture error expressions, Du et al 22 built a three-dimensional variation propagation modeling for Multistage Turning Processes of rotary workpieces. To analyze the quality propagation of MMP with remote quality information feedback (i.e.…”

Section: Literature Reviewmentioning

confidence: 99%

An extended machining error propagation network model for small-batch machining process control of aircraft landing gear parts

Wang

Jiang

2016

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

The complex structure and small-batch nature of aircraft landing gear parts lead to complex machining error propagation mechanism and manufacturing complexity. An Extended Machining Error Propagation Network model is presented to quantitatively analyze the complex coupling relationship in the Small-batch Multistage Machining Process of aircraft landing gear parts. Firstly, to depict the coupling relationship quantitatively, the Quality Features are defined to describe the machining precision information of Machining Form Features, and the State Elements are defined to describe the running state information of Machining Elements. Then, Machining Form Features, Machining Elements, Quality Features, and State Elements are identified as different network nodes, and the coupling relationships (such as evolving, locating, machining, and attribute) among these nodes are mapped into network edges. Based on the in-process measuring and sensing data of each machining stage, the topological and physical metrics of the network are explored to analyze the error propagation characteristics. Finally, the machining process of an outer cylinder part from aircraft landing gear is studied to verify the proposed methods.

show abstract

“…Feature recognition is to extract and recognize form features of a three-dimensional (3D) computer-aided design (CAD) part model. The feature recognition results are helpful to product designing, 1–3 process planning, 4–10 and numerical control (NC) programming. 11–17 Thus, it is regarded as the premier technic for the integrated representation of product lifecycle data.…”

Section: Introductionmentioning

confidence: 99%

An oriented feature extraction and recognition approach for concave-convex mixed interacting features in cast-then-machined parts

Wang

Zhang

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

Feature recognition is an important technology of computer-aided design/computer-aided engineering/computer-aided process planning/computer-aided manufacturing integration in cast-then-machined part manufacturing. Graph-based approach is one of the most popular feature recognition methods; however, it cannot still solve concave-convex mixed interacting feature recognition problem, which is a common problem in feature recognition of cast-then-machined parts. In this study, an oriented feature extraction and recognition approach is proposed for concave-convex mixed interacting features. The method first extracts predefined features directionally according to the rules generated from attributed adjacency graphs–based feature library and peels off them from part model layer by layer. Sub-features in an interacting feature are associated via hints and organized as a feature tree. The time cost is reduced to less than [Formula: see text] by eliminating subgraph isomorphism and matching operations. Oriented feature extraction and recognition approach recognizes non-freeform-surface features directionally regardless of the part structure. Hence, its application scope can be extended to multiple kinds of non-freeform-surface parts by customizing. Based on our findings, implementations on prismatic, plate, fork, axlebox, linkage, and cast-then-machined parts prove that the proposed approach is applicable on non-freeform-surface parts and effectively recognize concave-convex mixed interacting feature in various mechanical parts.

show abstract

Three-dimensional variation propagation modeling for multistage turning process of rotary workpieces

Cited by 33 publications

References 21 publications

Quality Risk Propagation of Complex Product Collaborative Manufacturing Supply Chain Network Based on CN and SoV

Quality Risk Propagation of Complex Product Collaborative Manufacturing Supply Chain Network Based on CN and SoV

An extended machining error propagation network model for small-batch machining process control of aircraft landing gear parts

An oriented feature extraction and recognition approach for concave-convex mixed interacting features in cast-then-machined parts

Contact Info

Product

Resources

About