An optimisation procedure to determine the coefficients of the extended Taylor's equation in machining

Modeling tool wear progression by using mixed effects modeling technique when end-milling AISI 4340 steel

“…They developed a first order and second order regression model for tool life prediction with different set of processing parameters for cutting speed, feed and depth of cut (DOC). Dos Santos et al (1999) used the extended Taylor tool life equation to predict tool life for face milling AISI 1045 cold rolled steel and AISI 304 stainless steel with triple TiN-TiC-TiN coated carbide inserts (ISO P45-M35 class) under dry machining conditions. Focus of their research was to determine the best set of processing parameters that yield the fastest convergence for the coefficients of the extended Taylor tool life equation using the minimum ratio between minimum and maximum singular values of the sensitivity matrix of tool life related to variation of parameters.…”

“…One of the major problems associated with tool wear modeling of end-milling under such machining conditions is the prevalence of non-uniform tool wear and notch wear (Alauddin and El Baradie, 1997;Alauddin et al, 1995;Dos Santos et al, 1999;Sharman et al, 2001). Under such conditions, tools interact with work piece material at high temperatures resulting in the development of non-uniform wear caused by adhesion, diffusion and chemical wear.…”

Machinability of Ni-rich NiTiHf high temperature shape memory alloy

“…Hence, it is difficult to isolate any of these parameters and determine the effect of any individual parameter [24]. The most effective parameters, nonetheless, are cutting speed, depth of cut and feed rate, and their relationship to the tool life is described by Taylor [25] as shown in equation (1) below [26],…”

Tool life prediction via SMB-enabled monitor based on BPNN coupling algorithms for sustainable manufacturing

“…The sharp stage is a rapid wear period that the wear rapidly increases with increasing cutting force which means that the cutting flank has a high failure risk due to the reducing cutting ability. For the practical changed rates of the tool life during the processing of three stages, the tool life correlation T l between the cutting speed V c , the feed speed f z , and the cutting depth b was formulated using modified Taylor's equation (Taylor, 1907; Dos Santos et al, 1999; Hosseinkhani and Ng, 2020), as follows:where C n is a constant coefficient of modified Taylor's equation. The index i , j, and k are the tool life exponents depending upon the tool-workpiece materials and the cutting environment.…”