Mathematical Model to Optimize the Energy Consumed by a Semiconductors Manufacturing Industry – An Application

  • Mayra Méndez-Piñero University of Puerto Rico
  • Melitza Colón-Vázquez University of Puerto Rico

Abstract

A recently developed mathematical model to optimize energy consumption in manufacturing companies was used in a semiconductor industry to generate alternatives for the illumination and air conditioning systems. To solve the algorithm, the software Lingo 12.0 was used and the feasible alternatives were identified. The results of the mixed integer linear program guided the company in the selection of cost-effective equipment to reduce the energy consumed. Additional recommendations regarding the logistics of their daily operations were considered to increase the expected savings in energy for the illumination and air conditioning systems. Potential savings in energy consumption were found and recommended to company management. This application showed the usability of mathematical modeling to solve enormous problems (i.e., utilities cost) in manufacturing industries that create a burden in their product cost. Results presented to management showed the different recommendations analyzed and their impact in energy cost reduction depending on the alternatives they chose. Potential savings would fluctuate from over $28,000 to over $58,000 per year depending on recommendations chosen by company management. The use of the mathematical model to solve the energy cost problem demonstrated how real world variables and constraints can be used to analyze day to day problems and help manufacturing industries to be cost competitive.
Published
Dec 16, 2013
How to Cite
MÉNDEZ-PIÑERO, Mayra; COLÓN-VÁZQUEZ, Melitza. Mathematical Model to Optimize the Energy Consumed by a Semiconductors Manufacturing Industry – An Application. Journal of Mathematical Modelling and Application, [S.l.], v. 1, n. 8, p. 78-83, dec. 2013. ISSN 2178-2423. Available at: <https://proxy.furb.br/ojs/index.php/modelling/article/view/3131>. Date accessed: 16 oct. 2021.

Keywords

energy cost reduction; energy consumption optimization; semiconductors industry