Abstract
The computer numerical control machine is important industrial equipment, and its reliability has been one of the most important symbols to measure the modernization of advanced manufacturing and it is critical in the aspects of reliability design improvement, fault monitoring, and fault repair for the computer numerical control machine. The computer numerical control machine’s assembly process is a significant part in its manufacturing process, and assembly operation is a major factor in determining the whole machine’s quality, and assembly process quality analysis is necessary for computer numerical control machines, in which reliability allocation is an essential part of its reliability design. In order to quickly locate the fault of computer numerical control machine tool and accurately judge the fault grade, a method of fault classification decision of computer numerical control machine tool based on motion micro-unit is proposed, which includes the following steps: (1) from the point of the decomposition of system function, the computer numerical control machine tool is decomposed layer by layer into the layer of micro-actions, and the conceptual model of motion unit is given; (2) from the level of action, the types of fault modes of motion units are comprehensively analyzed and summarized; and (3) combining grey clustering theory and rough set theory, a fast and accurate fault classification decision-making method is formed. Finally, the validity of this method is verified by an example analysis of motion micro-units of a computer numerical control machine rack. The contributions of this work can be summarized as (1) the proposed grey fixed weight clustering analysis, (2) the graded fault classification using the decision table approach, (3) the knowledge reduction of decision rules using the rough set theory, and (4) the quicker and accurater decision and effectiveness validated by the given study case.
Highlights
As an essential part of system reliability analysis, fault pattern classification analysis is critical in the aspects of reliability design improvement, fault monitoring, and fault repair
This article attempts to propose a numerical control machine fault classification decision-making method based on motion micro-units which combines grey clustering theory and rough set theory, and it is expected to provide the corresponding basis for the process control of the subsequent maintenance
Considering the incompleteness of the known data of the micro-action unit fault mode and the grey of clustering result, if we directly reduce the knowledge of the original decision table, it is likely to lead to the contradiction between the minimum decision algorithm and the actual meaning of the problem
Summary
As an essential part of system reliability analysis, fault pattern classification analysis is critical in the aspects of reliability design improvement, fault monitoring, and fault repair. This article attempts to propose a numerical control machine fault classification decision-making method based on motion micro-units which combines grey clustering theory and rough set theory, and it is expected to provide the corresponding basis for the process control of the subsequent maintenance. Why the CNC machine tool fails is because the microaction unit itself or the connection between the associated micro-action units have failed, which has an impact on the function or performance of CNC machine tools, and the form of these failures is called fault mode. 1. Establishment of the fault information matrix Suppose that one of the micro-action units of a CNC machine has n-type fault modes, there are a total of m evaluation indicators for these fault modes, and there are s grey decision-making. The value of decision weight hj can be determined by experts or determined by the method proposed in Xu,[25] which will not be repeated here
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