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This is a report of a workshop held in mid-August of 2002 at Northwestern University, Evanston, Illinois, to explore what it takes to make a decision regarding environmental systems in the US. The participants in the workshop represented federal government, industry, non-governmental organizations and academia. During the two and a half day workshop, discussions were held on the policy drivers, the strategies and tactics (through a SWOT analysis), the decisions the automotive industry is facing today and the tools available to support decision making.

The National Science Foundation recently sponsored a Workshop on Environmentally Benign Manufacturing (EBM) for the Transportation Industries. The objective of the workshop was to determine future directions of research in the EBM area and to construct a roadmap for development of future research programs. While research in the fields of Design for the Environment (DfE) and Life Cycle Analysis (LCA) have focused on the product and product life cycles, an additional focus is needed to find and develop processes with less environmental impact within the manufacturing environment. This workshop explored EBM issues with respect to the enterprise, the products, the processes and the materials.

A pilot model using Simulink™ of three interlinked industrial sectors leading to painted automotive bodies was constructed for the purpose of observing time based effects on an Life Cycle Analysis (LCA). Current LCA neglects time under an implicit assumption that material inventory data is steady state. In this study, process models were built which included time as a parameter in addition to LCA material inventory data. The results show that time is a critical factor in the overall material inventory. If the transient behavior due to demand or regulatory control results in an industry instability, material supplies may be interrupted or overproduced depending on the timing and strength of the control. Furthermore, potentially greater inventories of undesirable materials could occur. These effects are not currently captured by LCA Inventory Analysis procedures. However, this paper shows that use of dynamic modeling can correct this situation.

In terms of manufacturing processes and systems, decision-makers may encounter difficulty in making environmentally friendly choices. This difficulty arises largely because of the nascency of environmentally responsible manufacturing. There is a sparsity of environmental information on processes and a variety of seemingly unconnected tools, methods, concepts, etc. To help decisions-makers understand the nature of a process and identify the appropriate tools/methods that may be most suited to reducing environmental impact, a classification system for manufacturing processes is established. Methods and tools for environmentally responsible manufacturing are then identified for each class. Two examples are presented to show how the new classification system may be applied in environmentally responsible manufacturing.

The drive of Design for the Environment is to reduce the environmental impact of both design and manufacturing processes. The most frequent method recommended is to substitute better materials and processes. However, there are processes that will continue to have undesirable environmental impacts due to the lack of knowledge of better methods. These processes are critical to manufacturing of products and can not be eliminated. All possible substitutions appear to have worse impacts. This paper explores modeling these processes and imposing a control method which permits an improvement of the environmental impact.

The framework for environmentally conscious manufacturing in industry is the life cycle assessment structure developed by the Society of Environmental Toxicology and Chemistry and incorporated into ISO 14000 Environmental Management Systems. Plant managers subject to this standard have the responsibility for environmental improvement projects. Often, applying these projects creates significant risks, particularly if the project is unsuccessful or requires a new technology that has not been widely applied. Plant managers are inherently risk adverse. Thus plant managers need to know not only how a project will succeed but also what could happen if the project fails or results in a state different than intended. Based on that knowledge, plants managers prepare contingency plans. This paper illustrates a method by which the optimum plan and all possible contingency plans can be selected based upon minimizing project cost while maximizing project success to arrive at an improvement goal.

A major task of road and airfield maintenance for transportation departments in the Northern United States and in cold regions globally is snow removal. In addition, there is a service industry built on snowplow equipped light trucks to remove snow from vehicle serviceways and parking lots. Thus, a source of stresses on a truck frame are the forces applied by the plow. Unfortunately, very little research has been performed to provide design models that will predict these forces. In this paper, both theoretical and experimental work on developing expressions for snowplow forces will be discussed.

As the pool of existing non-renewable natural resources continues to shrink, it will be necessary for government and industrial leaders to achieve a workable strategy for the intelligent allocation of scarce resources. In this paper, a method of quantifying the environmental and resource impacts of product redesign is proposed. This new method utilizes Input Output Analysis coupled with the Markovian decision making into a single matrix-based tool. The benefit of a fully developed tool would be the ability to make informed pre-production decisions leading to optimum product and process designs with minimal environmental impact. This paper illustrates this technique with an example based upon real industry data and extrapolated effects.

The current trend in the automotive industry is to minimize/eliminate cutting fluid use in most machining operations. Research is required prior to achieving dry or semi-dry machining. Issues such as heat generation and transfer, thermal deformation and fluid lubricity related effects on tool life and surface roughness determine the feasibility of dry machining. This paper discusses recent advances in achieving dry/semi-dry machining. As the first step, research has been conducted to investigate the actual role of fluids (if any) in various machining operations. A predictive heat generation model for orthogonal cutting of visco-plastic material was created. A control volume approach allowed development of a thermal model for convective heat transfer during machining. The heat transfer performance of an air jet in dry machining was explored. The influence of machining process variables and cutting fluid presence on chip morphology was investigated through designed experiments.