Resource (machine) optimization and line balancing in area of machine loading problems and Semiconductor industry capacity planning, scheduling and wip-in-progress (WIP)
The main interest is to investigate and propose the algorithm to optimize the capacity planning under demand uncertainty environment in semiconductor industry. The nature of the business requires the algorithm to be robust to the changes of demand which volatile in nature. The main impact of the volatility of demand will be on the resources which are prepared in advance to meet the demand such as the machines and tools.
The use of optimization technique is proposed in meeting the forecasted demand with the resources available. In addition, the technique should be able to detect the bottle-neck areas for capacity expansion. Stochastic programming such as Stochastic Linear Programming (SLP) has been recognized as an effective approach in dealing with uncertainty environment. Besides, revolutionary approaches such as Genetic Algorithm (GA) and Ant Colony Optimization (ACO) will be studied to optimize the resources used in the manufacturing
Database Design and Management, Web Engineering and Technologies
