Integration of process monitoring and machine condition diagnostics to improve quality prediction in grinding

Autor:	Martin Gustafsson, Pär Marklund, Kim Berglund, Muhammad Ahmer
Rok vydání:	2021
Předmět:	Bearing (mechanical) Computer science media_common.quotation_subject Process (computing) Condition monitoring Control engineering Grinding law.invention Data-driven law General Earth and Planetary Sciences Quality (business) Control parameters General Environmental Science media_common
Zdroj:	Procedia CIRP. 101:170-173
ISSN:	2212-8271
DOI:	10.1016/j.procir.2021.02.019
Popis:	Bearing ring grinding incorporates sensors to control the grinding cycle in real time. Prediction of output quality is difficult due to the complex combination of process settings and machine characteristics. Causal relationship of machine performance with varying operating conditions was studied with reference to the produced quality by adding condition monitoring setup to the machine. Data driven diagnostics of machine condition through integration of condition and process monitoring sensor data at the completion of the grinding cycle improves quality cognisance. This can be used to tune control parameters to achieve more predictable quality in successive cycles.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::72171086f34874b3cebb5333088428e4 https://doi.org/10.1016/j.procir.2021.02.019 Zobrazit plný text záznamu