Manufacturing process planning for industrial waste minimization

Francisco Javier Estrada-Orantes, University of Texas at El Paso

Abstract

Waste minimization/pollution prevention has become a strategic approach to industrial waste management in the 1990's. Traditionally, this problem has been addressed by proposing expensive waste remediation and treatment processes. This research offers a paradigm shift. It addresses the core of the problem: namely, the generation of waste itself. It looks into the development of an integrated production planning methodology that considers industrial waste as an important parameter (just as throughput, inventory levels, equipment capacity, etc.) during the planning stage. ^ In the first part of the study, an automotive instrument panel production process is studied with respect to hazardous and non-hazardous waste generation streams. On the second part of the research a planning methodology is applied and validated using this production scenario. The planning methodology is divided in four parts: Clustering procedure, planning methodology, scheduling procedure, and simulation models. Group technology principles are used to analyze the required production capacity, while looking very closely at machine setup times and waste generation. Then, a scheduling pattern or sequence is determined for each machine. A neural network is used to accomplish this task. Two scenarios with different scheduling patterns are then compared using simulation and statistical analysis. Results show that by using this methodology the generation of waste is reduced, and production requirements are still met. ^ This applied research is expected to contribute to the environmental health of the United States, while keeping its industries competitive. ^

Subject Area

Engineering, Industrial|Environmental Sciences|Engineering, Environmental

Recommended Citation

Estrada-Orantes, Francisco Javier, "Manufacturing process planning for industrial waste minimization" (2000). ETD Collection for University of Texas, El Paso. AAI9997669.
http://digitalcommons.utep.edu/dissertations/AAI9997669

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