@article{ahmer_unified_2020,
	series = {53rd {CIRP} {Conference} on {Manufacturing} {Systems} 2020},
	title = {A unified approach towards performance monitoring and condition-based maintenance in grinding machines},
	volume = {93},
	issn = {2212-8271},
	url = {http://www.sciencedirect.com/science/article/pii/S2212827120307289},
	doi = {10.1016/j.procir.2020.04.094},
	abstract = {The process controller in a precision grinder for bearing rings puts high performance demands on the machine to achieve desired quality in production. This paper presents a unique approach of adding additional sensors for machine condition monitoring for the purpose of learning and using high fidelity condition indicators. The consolidation of real-time sensor data and the process control signals yields high-dimensional dataset. Automatic segmentation helps optimize the amount of data for processing and data mining ahead of fault diagnosis. The proposed setup is state of the art for prognostics as part of condition-based maintenance in a production machine.},
	language = {en},
	urldate = {2020-10-05},
	journal = {Procedia CIRP},
	author = {Ahmer, Muhammad and Marklund, Pär and Gustafsson, Martin and Berglund, Kim},
	month = jan,
	year = {2020},
	keywords = {Analytics, Automation, Condition monitoring, Grinding, Machining, Maintenance, Manufacturing, Measurement, Process Monitoring, Sensor},
	pages = {1388--1393},
}

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