We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Research on tool change time and the dynamic reliability of the machining process based on sensitivity analysis.
- Authors
Wang, Xingang; Wang, Baoyan; LV, Chunmei; Chen, Xiaoming; Zhang, Yimin
- Abstract
Tool changing is on the basis of tool wear failure and breakage failure. Utilization rate of the tool is low, which cannot guarantee the reliability of the whole machining system. In machining process, as the number of parts produced increases, tool wear is constantly increasing, which will contribute to the reduction of the reliability of the cutting tool. That account for processing of substandard products. Combining the moment estimation with the maximum likelihood estimation with the dynamic reliability analysis method, the study builds a mathematical model of the dynamic reliability for machining process under the premise of regarding cutting parameters as random variables. The reliability of overall machining process is lower than a given target; the proposed model can identify the tool which has the biggest failure rate quickly and accurately. The failure rate formula of each tool involved in each operation is deduced as well. Based on failure rate, an algorithm for defining the critical tool and its corresponding tool change time is proposed. Beyond that, for maximizing the utilization of every tool, the given model can pick up the cutting parameter which has the largest sensitive degree to the reliability via sensitivity analysis method. Then, the selection of relevant stock removal should be changed so as to improve the reliability of cutting tool and the whole process system, as well as enabling the cutter continue to work and delaying tool change time finally. Ultimately, the manufacturing process can maximize the cutters' potential and thus reduce the number of tool changes, as well as the production costs.
- Subjects
MACHINING; RELIABILITY in engineering; SENSITIVITY analysis; STRUCTURAL failures; MECHANICAL wear testing; MAXIMUM likelihood statistics
- Publication
International Journal of Advanced Manufacturing Technology, 2017, Vol 89, Issue 5-8, p1535
- ISSN
0268-3768
- Publication type
Article
- DOI
10.1007/s00170-016-9177-0