PRODUCTION MONITORING SYSTEM WITH PREDICTIVE FUNCTIONALITY

Autor:	Eiskop, T., Snatkin, A., Kristo Karjust
Jazyk:	angličtina
Rok vydání:	2017
Předmět:	Artificial neural network Manufacturing execution system lcsh:TA1-2040 lcsh:Technology (General) lcsh:T1-995 Production monitoring system lcsh:Engineering (General). Civil engineering (General) Predictive functionality
Zdroj:	Journal of Engineering Science and Technology, Vol 12, Iss 9, Pp 2410-2425 (2017) Scopus-Elsevier
ISSN:	1823-4690
Popis:	The main objective of the current study is to analyse and develop production monitoring system (PMS) for small and medium enterprises (SME) with predictive functionality. The development of planned PMS covers design of hardware architecture, building data analysis and prediction tools. New tool wear forecast model has been developed. The proposed model extends traditional widely used models by introducing the effects of working regimes and multiple passes on tool/component wear.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::83dc9bedd6356a638f3c47589abc5be3 Zobrazit plný text záznamu