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Probabilistic prediction of cutting and ploughing forces using extended kienzle force model in orthogonal turning process

Salehi, M.; Schmitz, T. L.; Copenhaver, R.; Haas, R.; Ovtcharova, J.

Abstract:
Probabilistic prediction of cutting and ploughing forces is performed by applying Bayesian inference to an extended Kienzle force model. Prior probabilities are established and posterior force predictions are completed. The results of the probabilistic force predictions are then verified using forces measured under other cutting conditions, as well as a simplified slip-line force model. Additionally, probabilistic simulation results are compared with the results of a non-linear least squares fitting technique to isolate the shearing and ploughing force components of the cutting force.

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Verlagsausgabe §
DOI: 10.5445/IR/1000088537
Veröffentlicht am 17.12.2018
Originalveröffentlichung
DOI: 10.1016/j.procir.2018.08.228
Scopus
Zitationen: 1
Zugehörige Institution(en) am KIT Institut für Informationsmanagement im Ingenieurwesen (IMI)
Publikationstyp Zeitschriftenaufsatz
Jahr 2018
Sprache Englisch
Identifikator ISSN: 2212-8271
urn:nbn:de:swb:90-885373
KITopen-ID: 1000088537
Erschienen in Procedia CIRP
Band 77
Seiten 90-93
Bemerkung zur Veröffentlichung 8th CIRP Conference on High Performance Cutting (HPC 2018)
Schlagworte Cutting force; Kienzle model; Ploughing force; Bayesian inference; MCMC
Nachgewiesen in Scopus
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