Caires Moreira, Lorena

English

The goal of this thesis is to address the urgent industrial need for energy efficient Computer Numerical Control machining systems by developing effective empirical energy consumption models and optimisation approaches for energy efficient machining processes. In the thesis, a comprehensive literature survey has been conducted to identify industrial needs, the state-of-the-art energy consumption modelling and optimisation methods. Related research has been analysed and benchmarked. Based on the survey, research gaps have been identified. To develop effective energy consumption models is an essential step to achieve sustainable machining processes. Based on literature survey, it is recognised that there is a lack of models suitable for various types of machining processes, in particular, milling processes. In this thesis, based on Main Effect and Interaction Plots techniques, qualitative analysis has been made to establish relationships between critical machining parameters (including spindle speed, feed rate, depth of cut and width of cut) and the energy required for machining. Effective energy consumption models that can be configurable for various machining processes have been developed. Two different model structures are proposed according to the model selection criteria used. Application of sensible optimisation methods will be imperative for implementing energy efficient machining processes. In this thesis, based on the energy consumption models, two optimisation methods have been developed to identify optimal machining parameters to achieve the minimum energy consumption during machining processes. It is concluded that new and effective models and optimisation methods have been developed in the thesis. Future research directions have been summarised in the thesis.<br/

Coventry University Pure Portal

An innovative method for process planning for sustainable manufacturing

https://pure.coventry.ac.uk/ws/files/42355184/Moreira2016.pdf

An innovative method for process planning for sustainable manufacturing

Abstract

Similar works

Full text

Available Versions

Coventry University Pure Portal