Date of Award

December 2018

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Engineering

First Advisor

Chris Yuan

Committee Members

Anoop Dhingra, John Reisel, Benjamin Church, Wilkistart Otieno

Keywords

CNC Machining, compressed air compressor, energy conservation measures, energy efficiency, general model, integration model

Abstract

U.S. Manufacturing sector consumes remarkable amount of energy while the energy efficiency is quite low. Energy consumption of CNC machines is significant and various empirical models have been developed to model the Specific Energy Consumption (SEC) of CNC machines. However, most of the models are developed for specific machines, hence have limited applications in manufacturing industry. In this research, a general empirical SEC model for milling machine at certain power level is developed based on actual cutting experimental data. In this model, stand-by power and spindle power are used in the SEC model for the first time. The Material Removal Rate (MRR) is used to represent cutting parameter. The proposed model is fitted by regression analysis and validated using experimental data. Results show that the proposed model can be applied on various milling machines with an average absolute residual ratio of 6%. The model is also validated through a series of cutting experiments on a machine center, with an accuracy of 91.5%, for the SEC calculation.

Compressed Air Systems (CAS) are the 3rd energy source in industrial facilities and has a significant impact on the energy efficiency of manufacturing systems. This thesis provides an overview of all typical energy conservation measures (ECM) for CAS as well as all the energy savings calculations methods. To provide a simple guideline for decision maker, an economic benchmark analysis is presented for typical ECMs using the baseline conditions from Technical Reference Manuals (TRM) of multiple States in the US. Due to the ECMs correlate with each other, the comprehensive savings from multiple ECMs is not the simple summation of each individual measure. An integrated model is proposed to investigate the interrelationships of all measures and obtain combined savings. Meanwhile, the dryer’s impact to the other ECMs is included for the first time in the proposed model. CAS is a dynamic system with changing load, operations, and specifications etc. Therefore, the savings is a variable depending on system situations. The reliabilities of the ECMs are analyzed to obtain their dynamic characteristics. The optimization of the ECMs is discussed to demonstrate the interrelationships and dynamic of the savings mechanisms.

While the above studies focus on the energy modeling and savings of important system of manufacturing activities, it is important to have an overall understanding of the energy efficiency and saving potentials. Energy intensity is commonly used as an indicator for the energy efficiency. Encourage the implementation of proposed ECMs is the main strategy for energy efficiency improvement programs to influence the plant’s energy intensity. Study the trends of energy intensity of SMEs and the acceptance of proposed ECMs could draw outlines of the changes of energy usage, understand the flavor of plant managers towards energy savings projects and reflect the shift of technologies in the past decades. This thesis found that the industry structure of SMEs had limited effects on the energy usage while the fluctuation of producing activities and improvement of energy efficiency were the main contributors over the past three decades. Compared with the manufacturing plants with best energy efficient practices, an average of 15.71% of electricity and 14.51% of natural gas could be saved. However, the saving potentials of each subsectors varies dramatically due to the differences of production processes and energy use strategies. This discrepancy also reflected on the implementation of ECMs. Special planning and stimulations should be developed to accommodate the unique saving demands for different industries, ECM types and regions.

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