M.S. Thesis Presentation by Scott Duncan
Wednesday, May 29, 2002

(Dr. Bert Bras, advisor)

"A Mass and Energy Data Collection System to Support Environmental and Economic Monitoring of a Coating Line in Carpet Manufacturing"


Today's manufacturing organizations need tools to help them identify how to reduce their environmental impact while simultaneously increasing competitiveness. In order to make environmentally conscious design and manufacturing decisions, companies must be able to a) assess, quantitatively, their full environmental load, b) relate their load to specific design and operations decisions, c) evaluate the economic impact of making different decisions, and d) do all of this in a timely, consistent fashion. Towards these goals, recent research efforts by Georgia Tech's Environmentally Conscious Design and Manufacture (ECDM) group have created an information system called The Dashboard, which provides browser-based access to historical data including mass and energy consumption and waste streams. The information system traces these environmental loads to specific products and processes using an extended version of Activity Based Costing (ABC), which also provides a link to economic performance. In the preliminary version of the Dashboard, data was entered manually from cost sheets, utility bills, production records, and other plant sources. To be competitive, however, a company will in some cases need to include consumption data measured directly from the manufacturing process to track true environmental load over time. Such data, when automatically collected and organized, improves the timeliness and accuracy of environmental impact and cost analysis.

The specific focus of this project is to implement a prototype system for collecting mass and energy consumption data from a latex coating and drying process, making it accessible to the existing Dashboard user interface. After pertinent environmental and quality performance indicators are identified, off-the-shelf industrial-grade sensors and submetering devices are selected to take process measurements. The data streaming from these devices is collected via Java-based networking hardware and stored in specially created database tables that augment the pre-existing Dashboard system. The main objectives for the project are (1) to learn lessons about what type of hardware and software is best suited to collect process data, including an assessment of the "cost of data", and (2) to evaluate the extent to which collected data can reliably be used as indicators for assessing and improving environmental performance. Suggestions about how to use the data and the Dashboard in an ISO 14031 environmental performance evaluation framework are provided.