Measurement of surface characteristics of Ti6Al4V aerospace engineering components in mass finishing process

•A novel integrated computational approach is introduced for mass finishing process.•High accuracy of proposed model compared to traditional modeling techniques.•Abrasive media type is the most dominant process parameter in finishing process. Mass finishing is a secondary manufacturing process emplo...

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Veröffentlicht in:Measurement : journal of the International Measurement Confederation 2018-02, Vol.115, p.279-287
Hauptverfasser: Vijayaraghavan, V., Castagne, S.
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Castagne, S.
description •A novel integrated computational approach is introduced for mass finishing process.•High accuracy of proposed model compared to traditional modeling techniques.•Abrasive media type is the most dominant process parameter in finishing process. Mass finishing is a secondary manufacturing process employed in aerospace and automotive industries to obtain the required surface finish of engineering parts. The finishing process involves interaction of several input process parameters related to the finishing machine, abrasive media and the parts to be finished. A robust empirical model which can accurately predict the system behavior and capture the science of complex interactions between process variables would provide great insights on mass finishing process. To address this challenge, the authors have proposed a novel integrated data analytics model by combining two powerful evolutionary techniques, Gene Expression Programming and Adaptive Neuro-Fuzzy Inference system. The proposed integrated approach was able to capture the dynamics of mass finishing process more accurately compared to that of other commonly available data analytical models. Tribological analysis of the model showed that an optimal surface finish of mass finished part can be achieved in mass finishing process by regulating the process time and media type. It is anticipated that the proposed model can be useful for determining optimal parameters for achieving desired surface finish without the need to conduct experiments, thereby leading to considerable savings in materials and time.
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Mass finishing is a secondary manufacturing process employed in aerospace and automotive industries to obtain the required surface finish of engineering parts. The finishing process involves interaction of several input process parameters related to the finishing machine, abrasive media and the parts to be finished. A robust empirical model which can accurately predict the system behavior and capture the science of complex interactions between process variables would provide great insights on mass finishing process. To address this challenge, the authors have proposed a novel integrated data analytics model by combining two powerful evolutionary techniques, Gene Expression Programming and Adaptive Neuro-Fuzzy Inference system. The proposed integrated approach was able to capture the dynamics of mass finishing process more accurately compared to that of other commonly available data analytical models. Tribological analysis of the model showed that an optimal surface finish of mass finished part can be achieved in mass finishing process by regulating the process time and media type. 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source ScienceDirect Journals (5 years ago - present)
subjects Abrasive finishing
Abrasive machining
Adaptive systems
Aerospace engineering
Aerospace industry
Aircraft components
Analytics
Artificial neural networks
Automobile industry
Automotive engineering
Automotive parts
Complex variables
Data analysis
Data analytics
Empirical analysis
Fuzzy logic
Fuzzy systems
Gene expression
Mass finishing
Mathematical models
Optimization
Process parameters
Process variables
Surface finish
Surface properties
Titanium base alloys
Tribology
title Measurement of surface characteristics of Ti6Al4V aerospace engineering components in mass finishing process
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