Yazui Liu, Haodong Shen, Gang Zhao, Xishuang Jing, Xiaoxiao Du
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Improved Jacobian-Torsor model for optimizing mechanical product quality
The quality of an assembly largely depends on the predictive accuracy of the assembly deviation model in the selective assembly process. Presently, three-dimensional deviation analysis methods only offer tolerances that indicate the overall deviation of a part feature. This limitation fails to accurately represent the fit of the parts during the assembly process, resulting in initial inaccuracies in the selective assembly model. To address this issue, an improved Jacobian-Torsor model is proposed that incorporates measured data from part assembly features into the deviation analysis model. Initially, the actual contact state of the assembly is determined by measuring the contact surface of the plane fit and the shaft-hole fit. Next, the Jacobian matrix, representing the transmission path of assembly deviation, is constructed by analyzing the assembly connection diagram. Subsequently, by integrating the actual contact state characterized by small displacement torsor (SDT) into the unified Jacobian-Torsor model, the advantage of high credibility tolerance propagation is provided. Finally, the feasibility of the proposed improved Jacobian-Torsor model is verified using the double-joint manipulator.
期刊介绍:
Manufacturing industries throughout the world are changing very rapidly. New concepts and methods are being developed and exploited to enable efficient and effective manufacturing. Existing manufacturing processes are being improved to meet the requirements of lean and agile manufacturing. The aim of the Journal of Engineering Manufacture is to provide a focus for these developments in engineering manufacture by publishing original papers and review papers covering technological and scientific research, developments and management implementation in manufacturing. This journal is also peer reviewed.
Contributions are welcomed in the broad areas of manufacturing processes, manufacturing technology and factory automation, digital manufacturing, design and manufacturing systems including management relevant to engineering manufacture. Of particular interest at the present time would be papers concerned with digital manufacturing, metrology enabled manufacturing, smart factory, additive manufacturing and composites as well as specialist manufacturing fields like nanotechnology, sustainable & clean manufacturing and bio-manufacturing.
Articles may be Research Papers, Reviews, Technical Notes, or Short Communications.