Predicting surface roughness in machining: a review

Benardos, PG; Vosniakos, GC

dc.contributor.author	Benardos, PG	en
dc.contributor.author	Vosniakos, GC	en
dc.date.accessioned	2014-03-01T11:44:35Z
dc.date.available	2014-03-01T11:44:35Z
dc.date.issued	2003	en
dc.identifier.issn	0890-6955	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/37019
dc.subject	surface roughness	en
dc.subject	surface roughness prediction	en
dc.subject	machining	en
dc.subject	review	en
dc.subject.classification	Engineering, Manufacturing	en
dc.subject.classification	Engineering, Mechanical	en
dc.subject.other	TURNING OPERATIONS	en
dc.subject.other	TOOL WEAR	en
dc.subject.other	RECOGNITION SYSTEM	en
dc.subject.other	FINISH	en
dc.subject.other	MODEL	en
dc.subject.other	STEEL	en
dc.subject.other	VIBRATIONS	en
dc.subject.other	OPTIMIZATION	en
dc.subject.other	PARAMETERS	en
dc.subject.other	SIMULATION	en
dc.title	Predicting surface roughness in machining: a review	en
heal.type	other	en
heal.identifier.primary	10.1016/S0890-6955(03)00059-2	en
heal.identifier.secondary	http://dx.doi.org/10.1016/S0890-6955(03)00059-2	en
heal.language	English	en
heal.publicationDate	2003	en
heal.abstract	The general manufacturing problem can be described as the achievement of a predefined product quality with given equipment, cost and time constraints. Unfortunately, for some quality characteristics of a product such as surface roughness it is hard to ensure that these requirements will be met. This paper aims at presenting the various methodologies and practices that are being employed for the prediction of surface roughness. The resulting benefits allow for the manufacturing process to become more productive and competitive and at the same time to reduce any re-processing of the machined workpiece so as to satisfy the technical specifications. Each approach with its advantages and disadvantages is outlined and the present and future trends are discussed. The approaches are classified into those based on machining theory, experimental investigation, designed experiments and artificial intelligence (AI). (C) 2003 Elsevier Science Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE	en
dc.identifier.doi	10.1016/S0890-6955(03)00059-2	en
dc.identifier.isi	ISI:000183033200009	en
dc.identifier.volume	43	en
dc.identifier.issue	8	en
dc.identifier.spage	833	en
dc.identifier.epage	844	en