Machining informatics: A data guided research on interfacial tribology of machining
File(s)
Author(s)
Mia, Mozammel
Type
Thesis
Abstract
Data guidance is a new approach of finding scope and conducting research, especially in the manufacturing science and technology. Machining being one of the most established and long dated processes has its extensive usability in diverse selection of products, for instance, nano-scale machining to turning of big shafts of ships. An integration of data guidance and research of machining can be of high value to the academics and industries to discover potential scope of research and conduct research on it which could not be explored by conventional approach. The garnering of reliable data of machining processes stays as a big challenge, next to which is the methodology of processing and using the collected data as part of the data guided research. In recent time, the advent of the computation science, especially the data science containing the artificial intelligence and machine learning has made a remarkable progress with the newest innovation in manufacturing science. However, the sole dependence on the artificial intelligence-based approaches is criticised because of the lack of the physical meaning of the developed systems as well as it hardly adds value to the fundamentals of the machining science.
This thesis presents the concept of data guided research on the interfacial tribology of machining. The complete chain of the work i.e., the data collection, data processing, data analysis and data application constitute the framework of `Machining Informatics'. As a mean to collect reliable data of machining responses, the experimentally validated FEA models were considered as the sources of physics-guided data of machining. A new approach of reviewing data to find research scope, the digital characteristics were developed for the mechanical, thermal, and interfacial responses of machining...
This thesis presents the concept of data guided research on the interfacial tribology of machining. The complete chain of the work i.e., the data collection, data processing, data analysis and data application constitute the framework of `Machining Informatics'. As a mean to collect reliable data of machining responses, the experimentally validated FEA models were considered as the sources of physics-guided data of machining. A new approach of reviewing data to find research scope, the digital characteristics were developed for the mechanical, thermal, and interfacial responses of machining...
Version
Open Access
Date Issued
2023-05-15
Date Awarded
05/08/2023
License URL
Advisor
Wang, Liliang
Lin, Jianguo
Publisher Department
Department of Mechanical Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)