2022
DOI: 10.1177/09544054221100320
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Specific force map for smart machining applications with rotating tools

Abstract: Industry 4.0 is the need of the hour in current global market scenario and all the processes are moving toward automation and smart manufacturing. In machining, smart techniques implementation depends on developing a database for decision-making, which is the case for stack drilling in aerospace industry. In this application, choosing one optimal condition for several materials is a challenge due to their different machinability. Hence, material identification techniques are suitable approaches for adapting th… Show more

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“…The following subsections present the cutting power, cutting forces monitored during helical milling of stacks and estimated specific force coefficients data map using cutting power. The data maps of specific coefficients show distinct data points indicating different materials and can be advantageous for material identification especially at interface layers of different material [25]. Cutting power is monitored by utilizing machine internal sensors while cutting forces is monitored by external sensor (Dynamometer) simultaneously, However, specific coefficients are estimated from cutting power signal and this is to verify the possibility of utilising spindle power for material identification.…”
Section: Resultsmentioning
confidence: 99%
“…The following subsections present the cutting power, cutting forces monitored during helical milling of stacks and estimated specific force coefficients data map using cutting power. The data maps of specific coefficients show distinct data points indicating different materials and can be advantageous for material identification especially at interface layers of different material [25]. Cutting power is monitored by utilizing machine internal sensors while cutting forces is monitored by external sensor (Dynamometer) simultaneously, However, specific coefficients are estimated from cutting power signal and this is to verify the possibility of utilising spindle power for material identification.…”
Section: Resultsmentioning
confidence: 99%