As machines and products increase in productivity while shrinking in size, issues of contamination related failures become a greater risk. Previously, common contaminants such as sand from sand casting, dust from the air, or chips from machining, were within generally allowable product tolerances. The semiconductor industry was first to encounter contamination related problems from dust on their micro sized features. Now, the automo- tive industry is discovering millimeter sized chips blocking lubrication valves and scoring precision surfaces. This report details an experimental investigation of how chip related contamination may be controlled by varying milling and drilling cutting parameters such as feed, speed, depth of cut, and lubrication. Based on the assumptions of this paper, where the optimal chip is likely short, lightweight, with a large wavelength, and few rota- tions, it is found that the optimal milling chip is produced with increased speed, increased lubrication, decreased feed, and decreased depth of cut. For drilling, the optimal chip is accomplished through increased lubrication, decreased speed, and increased feed. Future research is required to determine the optimal chip type.

Water use, energy use, and global warming potential (GWP) are investigated to assess the environmental impact of the manufacturing supply-chain in the interest of developing sustainable manufacturing systems. Because a major component of the supply chain is transportation, four methods of transportation are investigated: shipping, rail, trucking, and air freight. Additionally, location-specific manufacturing considerations such as water scarcity, resource availability, and energy mix are discussed. Finally, a tool is introduced to enable the visualization and computation of manufacturing supply-chain environmental impacts. This information enables decision making for designing and implementing sustainable supply-chain networks.

When a part is manufactured, different processing steps can introduce contaminants to the workpiece. One common form of contamination is the chips produced by machining, which often lodge in the crevices and pathways of the workpiece causing problems for both the accuracy of subsequent machining operations, and the usability of the part. To avoid such problems, it is important to both optimize the type of chip produced so it can be most easily removed from the workpiece, and to minimize the number of chips that remain. By varying process parameters such as feed, speed, depth of cut, and lubrication, some insight is gained as to how these parameters affect chip geometry and size. The results for drilling were mostly inconclusive, while the results for milling provided an important first step towards optimizing the chip form.

A 2-dimensional drilling burr control chart was developed by Jinsoo Kim (2000, 2001) which quantifies the effects of feed rate and speed on burr size; but, each chart is only useful for a specific type of material, and many materials have yet to be studied. What is needed is an understanding of how material properties and their dependence on temperature effect burr formation, to avoid the necessity of creating a burr control chart for every type of material. The goal is to use previous studies of material properties and burr formation to develop a third axis on the burr control chart. Ideally, one could create a dimensionless number that is a function of the material properties that most effect burr formation.

The manufacturing sector is a significant contributor to environmental damage and resource use, which has potential long-term implications if resources are overused and our air, water, and soil are altered irreversibly. To alleviate these impacts, the manufacturing research community has primarily focused on reducing the environmental impacts of specific manufacturing processes and systems within a factory; however there are opportunities for environmental impact reductions that emerge from a supply chain perspective. For example, researchers have recognized that by taking advantage of regional differences when locating facilities there is the opportunity to alleviate global water scarcity and reduce the human health effects of pollution. We add to this body of work by focusing on the opportunity to take advantage of regional variability to reduce supply chain GHG emissions.

Through the development of targeted environmental return-on-investment (ROI) metrics and hybrid life-cycle assessment techniques, we enable the minimization of global greenhouse gas emissions through informed supply chain design. Founded on the premise that GHG emissions are a global problem that can benefit from global optimization, we focus on the tradeoffs between transportation emissions and electricity emissions.

A three-pronged approach to management and reduction of GHG emissions in manufacturing is presented: (1) metric design for environmental decision-making (2) comprehensive, repeatable, and efficient life-cycle assessment using a hybrid approach (3) optimization of the system to take advantage of regional tradeoffs. This approach is demonstrated through a generic case study of automotive manufacturing and a case study of SolFocus Inc. concentrated solar photovoltaic panels.

The case-studies show that 30-40% of GHG emissions in the supply chain are from electricity and transportation and can be reduced by up to 50% through changes in supplier location. Furthermore, regional variability in electricity emissions means that local manufacturing is not always optimal. Finally, the incorporation of ROI metrics for the SolFocus system presented the most rapid path to global reductions in GHG emissions. Installation of solar technology in Australia results in a savings of nearly 20 kg-CO2eq for every kg-CO2eq emitted during production; whereas the savings from installation in Spain, Northern California, or Arizona is 7-8 kg-CO2eq.

This dissertation presents the following new contributions to the field (1) a method for global GHG reductions, separate from product re-design, through optimization of supply chain layout based on transportation and electricity GHG emissions tradeoffs; (2) development of effective and targeted ROI environmental metrics to guide decisions that promote the fastest route to reduce environmental impacts in manufacturing; (3) validation of the feasibility of using of iterative financial hybrid LCA to ensure a comprehensive LCA and guide regional input-output electricity estimates and tradeoffs in key areas; (4) demonstration and development of the greenhouse gas ROI metric, iterative hybrid LCA methodology, and supply chain layout decision-making for concentrator solar PV

We note that these supply chain efforts must occur in conjunction with efforts on sustainable product design such as design for remanufacture, improved use-phase efficiencies, or utilization of new materials.

Supply-chain greenhouse gas emissions and water scarcity are investigated as important components of sustainable manufacturing systems and a different impact reduction approach is suggested for each metric. Greenhouse gas emissions have a global impact regardless of emission location, which allows for supply-chain tradeoffs, whereas water scarcity is a local measure that is useful in predicting the long-term sustainability of a manufacturing location. Using publicly available data, greenhouse gas supply-chain tradeoffs are shown to exist between transportation distances, transportation mode, and regional electricity mix. This study sets the groundwork for designing and implementing reduced impact supply-chain networks.

The greenhouse gas return on investment (GROI) metric is introduced as a compliment to the energy return on investment (EROI). Unlike EROI, GROI accounts for the life cycle energy mix, the efficiency, circularity, and supply chain of energy distribution, and the energy offset by a new energy installation. The average greenhouse gas emissions of labor and electricity are calculated for multiple countries to be used in GROI calculations. GROI is applied to a case study of SolFocus Inc. solar panels, and the potential extension of GROI methodology to a modified EROI and to decision making beyond energy is discussed.

Multiple frameworks have been developed for sustainable or green manufacturing systems and products, which can be roughly divided into life cycle assessment methodologies and life-cycle assessment standards. Methodologies include process LCA, input-output LCA, and hybrid LCA; standards include the ISO14044 standard, the US EPA Life-Cycle Engineering Standard, and various emerging greenhouse gas protocols. We discuss in this paper the differences between these frameworks, and define the specific use cases where each framework is best suited. We achieve this by looking at manufacturing systems and processes across spatial and temporal levels of complexity and assess the suitability of existing frameworks at each level. The main questions addressed are: (1) what are appropriate LCA methodologies for different scales of manufacturing? (2) how do existing standards apply across various levels of manufacturing?

A sustainable manufacturing strategy requires metrics for decision making at all levels of the enterprise. In this paper, a methodology is developed for designing sustainable manufacturing metrics given the specific concerns to be addressed. A top-down approach is suggested that follows the framework of goal and scope definition: (1) goal- what are the concerns addressed and what is the appropriate metric type to achieve the goal (2) scope what is the appropriate geographic and manufacturing extent. In this methodology, a distinction is made between environmental cost metrics and sustainability metrics. Utilizing this methodology, metrics focused on energy use, global climate change, non-renewable resource consumption, and water consumption are developed.