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Theory And Method Research Of Mechanical Parts’ Remanufacturing Processing Quality Control Based On Uncertainty Measurement

Posted on:2016-10-06Degree:DoctorType:Dissertation
Country:ChinaCandidate:C Y LiuFull Text:PDF
GTID:1222330488492525Subject:Industrial Engineering
Abstract/Summary:PDF Full Text Request
Remanufacturing engineering is an optimal realization form to build circular economy and to realize social’s sustainable development. It is one of the efficient technologies that could deal with global environmental pollution and resource shortage in 21st century. "The quality of remanufactured product not less than the original one" is an important guarantee for the high-speed development of remanufacturing engineering. However, problems and deficiencies existing in the remanufactured product quality recently has become a bottleneck which restrict the further development of remanufacturing industry. Because of the particularity and complicacy of remanufacturing process, remanufacturing uncertainty is far more than traditional manufacturing process, which impacts the quality of remanufactured product ultimately and restricts service safety performance of remanufactured product. The research of uncertainty during remanufacturing has turned into one of the theoretical basis that to be solved for the large-scale development of remanufacturing industry. Given that, based on the exploration about connotation and measurement model of remanufacturing processing uncertainty, the remanufacturing processing quality control method of mechanical parts under uncertainty environment is researched to provide theory, method and technique support in guaranteeing the quality of remanufactured product.The major research contents of this paper are as follows:(1) Relevant research situations at home and abroad on the fundamental theory of remanufacturing, the remanufacturing processing uncertainty and the remanufacturing quality control are introduced. Then, the deficiency of remanufacturing quality control research is analyzed. After that, we describe the research background, research significance, and research contents.(2) Characteristic and origin of remanufacturing processing system’s uncertainty is studied, and the analysis model for remanufacturing processing system is established, which can carry on multilevel analyze and multidimensional analyze of its uncertainty. Taking "entropy" as uncertainty measurement, the uncertainty concept and measurement model for remanufacturing processing system is constructed.(3) Random uncertainty and fuzzy uncertainty measurement model of remanufacturing primitive features is researched. Based on the product space P×M method, the measurement scale integration is explored, and the recombination entropy model which quantitative describes the overall uncertainty of remanufacturing primitive features is given. Through nonlinear fitting model, the coupling mechanism between fundamental attribute uncertainty of remanufactured parts and remanufacturing processing quality attribute is studied. The effectiveness and feasibility of the method is verified by an instance of remanufactured crankshaft processing.(4) Remanufacturing process route model is established on the basis of GERT chart. Considering processing technology difficulty and processing state diversity factors, the uncertainty measurement model for remanufacturing processing is structured based on the generalized information entropy. Then, the remanufacturing processing control index is defined to realize assessment of remanufacturing processing control ability. Focus on the remanufacturing process of a certain remanufactured crankshaft, also, we assess the availability of remanufacturing process quality control.(5) Quality fluctuation is measured by using quality entropy. Taking minimum quality fluctuation as control target, the basic framework model for remanufacturing quality prediction control system is built. Next, we carry on remanufacturing quality modeling prediction by using wavelet Elman neural network. Then, the network training is conducted by adopting adaptive learning rate, meanwhile, the dynamic recursion gradient descent algorithm for training network is given. Finally, the prediction model is applied to the quality prediction of the remanufactured crankshaft.(6) The remanufacturing process quality control prototype system is developed and the system conceptual model is built. Then, the crucial enabling technology which contribute to system overall architecture and system realizing is provided.
Keywords/Search Tags:Remanufacturing proccssing, Uncertainty, Quality control, Information entropy, Wavelet Elman neural network
PDF Full Text Request
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