Doctoral Dissertations

Date of Award


Degree Type


Degree Name

Doctor of Philosophy


Industrial Engineering

Major Professor

Rapinder Sawhney

Committee Members

John Kobza, James Simonton, John Bell


Human activities are the main sources of environmental pollution. Awareness about this fact, motivated us to make changes in different paradigms of our lives including industrial or personal activities. Environmental activities assumed to have conflict with financial objectives, in this study we try to align business requirements with environmental concerns.

Among all human activities, generating energy has the most negative impact on the environment. The major part of the generated energy will be consumed in transportation and industrial demand which makes them the most effective targets for the reduction of greenhouse gas emission. In a lean environment, small batch sizes increase the number of set-ups and consequently, energy consumption in manufacturing. On the other hand, small batch sizes increase the delivery rates and complexity of transportation. Therefore, the focus of this study will be on reducing the environmental impact of human activities in transportation and industrial loads as a part of lean supply chain.

The focus in transportation will be on trucking with gasoline or diesel as the source of energy. In industrial loads, the emerging opportunities after deregulation of the electricity market and incentive programs toward cleaner productions encouraged us to focus on electrical demand in the industry.

Despite motivations for reducing emissions in supply chain management, lack of knowledge and expertise in measuring, modeling and optimizing energy consumption is a barrier in production section. In this dissertation, a framework of a power measurement and simulation will be introduced. In the next section, a production planning model incorporating energy will be developed considering different states of electricity consumption (idle, startup, etc.).

As the next segment of the supply chain, a method for optimal carrier selection and routing will be developed and tested based on real world data. This model can use the advantage of geographically distributed carriers while utilizing private fleet at an acceptable level. Based on the insight developed in transportation and industrial loads, an experience based performance measure will be developed to quantify the performance and associated energy consumption in the supply chain.

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