UC Berkeley

Energy and resource efficient manufacturing is becoming increasingly important due to scarcity of natural resources, stricter regulations and increasing customer demand for sustainable products. According to the Energy Information Administration, the industrial sector accounted for about one-third of total U.S. energy consumption in 2017. Research has shown that machine tool design is responsible for 40% of energy use while machining processes demand 22% of total energy consumption. The manufacturing sector is a significant contributor to environmental damage and resource use, and therefore there is ample opportunity for improving energy and resource efficiency. To address these issues, this dissertation proposes approaches to evaluate and quantify resource use of manufacturing across three hierarchical levels: process, machine tool, and production facility; these methods are used to assess current performance and provide effective approaches to reduce future resource consumption.

Depending on the scale of the system considered, different strategies can be applied to optimize the efficiency of manufacturing systems. In order to offer a systematic study, this dissertation is structured according to increasing system scale: First, at the individual process level, the design of experiments (DOE) method was applied to study the effect of the main machining parameter such as feed rate, spindle speed and drill diameter. A case study of drilling operations on multi-layer printed circuit boards (PCBs) was conducted to find the optimal cutting parameters for achieving high cutting performance that can avoid additional deburring process. A plan of experiments was performed to investigate the burr formation mechanism. In the end, a micro-drilling burr control chart was proposed for process planning.

The second part of this work focuses on machine tool level solutions. Changing the cutting parameters alone will not result in an optimal solution since there are other components in the production equipment that consume resources. Therefore, the scope moves from process planning to the machine tool level. A lot of studies tried to quantify the energy consumption of machine tools, but few of them have looked into other resources such as water. To fill this gap, a water footprint assessment of the milling machine tool was conducted, following ISO 14046 standards. A case study of face-milling on aluminum alloy was examined. The water inventory of a milling machine was calculated, and a water scarcity footprint was estimated to assess the associated impacts. Uncertainty analysis was conducted to assess the potential bias from different plant locations.

The third part of this work focuses on factory level solutions. Numerous studies have implemented value stream mapping to improve the production facility in terms of productivity, but energy information is often left out. Therefore, a construction of an environmental value stream map (E-VSM), which integrates environmental metrics into conventional value stream mapping, is presented. Through the construction of an E-VSM, a case study evaluates the performance of a cover glass manufacturing facility in China. Improvement strategies have been provided to increase productivity, as well as reduce environmental impact. Uncertainty analysis was carried out to find out how geographic locations might affect the results.

This research has developed and evaluated effective approaches for the analysis of energy, water, and other resource use in manufacturing systems on different levels. The presented work allows manufacturers to better understand the resource consumption of manufacturing activities, and provides effective strategies to reduce the associated impacts.