Nowadays, the condition-based maintenance (CBM), in which repairs are triggered by the heuristic symptoms of the component faults, is finding increasing applications in the industrial fields. However, for the high-precision machine tools, the conventional CBM might not be the optimal option, which is uneconomic and incapable of ensuring their machining accuracy. In order to overcome these shortcomings, this paper propose the manufacturing-error-based maintenance (MEBM), where the repairs are initiated based on the manufacturing errors instead of the heuristic symptoms. In MEBM, repairs are taken properly at the occurrence of the excessive machining errors, and therefore, the premature and redundant maintenance can be avoided and the maintenance cost can be minimized; what is more, the machining errors are controlled in the closed loops, and therefore, the machining accuracy can be guaranteed. Based on the principles of the MEBM, a prototype maintenance system—the transient backlash error (TBE)-based maintenance system—is established. To achieve this aim, first, the width of the backlash in the mechanical chain is measured by utilizing the built-in encoders and the analytical mapping relationship between the backlash width and the TBE is derived. Relying on these foundations, the TBE can be indirectly estimated. Then, the warning threshold of the TBE is customized according to the permissible roundness error of the workpiece. Thus, the maintenance actions can be precisely implemented: when the monitored TBE exceeds its warning threshold, maintenance workers will be notified to lessen the backlash width, and meanwhile, the permissible maximal size for the backlash will also be informed.
The International Journal of Advanced Manufacturing Technology – Springer Journals
Published: Oct 16, 2017
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera