Date of Graduation
Statler College of Engineering and Mineral Resources
Industrial and Managements Systems Engineering
The development of technologies which enable resource efficient production is of paramount importance for the continued advancement of the manufacturing industry. In order to ensure a sustainable and clean energy future, manufacturers should be able to contrast and validate existing manufacturing technologies on a sustainability basis. In the post COVID-19 era of enterprise management, the use of artificial intelligence to simulate human expert decision making abilities will open new doors to achieving heightened levels of productivity and efficiency. The introduction of innovative technologies such as CNC machining and 3D printing to production systems has redefined the manufacturing landscape in a way that has compelled users to investigate into their sustainability. For the purposes of this study, cost effectiveness, energy and auxiliary material usage efficiency have been considered to be key indicators of manufacturing process sustainability. The objective of this research study is to develop a set of expert systems which can aid metal manufacturing facilities in selecting Binder Jetting, Direct Metal Laser Sintering or CNC Machining based on viable product, process, system parameters and inherent sustainability aspects. The expert systems have been developed using the knowledge automation software, Exsys CorvidÒ. Comprehensive knowledge bases pertaining to the objectives of each expert system have been created using literature reviews and communications with manufacturing experts. An interactive environment which mimics the expertise of a human expert has been developed by the application of suitable logical rules and backward chaining. The programs have been verified by analyzing and comparing the sustainability impacts of Binder Jetting and CNC Machining during fabrication of a stainless steel 316L component. According to the results of the study, Binder Jetting is deemed to be characterized by more favorable indicators of sustainability in comparison to CNC Machining, for fabrication of components feasible for each technology.
Perera, Josage Chathura Pamuditha, "Sustainability-Based Expert System for Additive Manufacturing and CNC Machining" (2020). Graduate Theses, Dissertations, and Problem Reports. 7719.