The semiconductor industry is one of the largest end-users of energy. The Front-End is the most energy-intensive process along the supply chain due to its manufacturing equipment, cleanroom conditions, and subfab facilities. The Ion Implantation work center has been identified as the primary energy consumer within the FE. Therefore, this thesis evaluates the potential to improve the energy efficiency of this process by reducing the sequence-dependent setup times. To achieve this goal, two discrete event simulation models have been developed. While the first focuses on a single Ion Implantation work center, the second replicates an overall Front-End semiconductor fab to evaluate the influence on the overall fab performance when improving energy efficiency. Therefore, two heuristics, greedy search procedures and metaheuristics have been developed. While a combined Greedy Search Simulated Annealing procedure allowed for the highest energy savings in the work center approach, the Simulated Annealing performs most efficiently at the fab level while satisfying global and local constraints.     «

The semiconductor industry is one of the largest end-users of energy. The Front-End is the most energy-intensive process along the supply chain due to its manufacturing equipment, cleanroom conditions, and subfab facilities. The Ion Implantation work center has been identified as the primary energy consumer within the FE. Therefore, this thesis evaluates the potential to improve the energy efficiency of this process by reducing the sequence-dependent setup times. To achieve this goal, two discre...     »