- Computer Science
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Semiconductor manufacturing is a capital-intensive industry that capital utilization rate significantly affect the capacity effectiveness and final profit. Capacity portfolio planning strategy must coordinate capacity expansion and migration decisions in balance for utility maximization for smart production and supply chain effectiveness. Manufacturers have to determine capital investments based on various demand forecasts of products in advance for long lead time in manufacturing process. Rapid development in semiconductor technology makes it difficult for companies to estimate future tool requirement especially for new-generation products planning decisions. This study aims to develop an uncertain multi-objective decision (UMD) strategy framework based on uncertainty theory for capacity expansion and migration problem. The objective of proposed model is to minimize the potential loss of capacity oversupply or shortage under uncertain environment. An empirical study was conducted for validation and the results showed practical viability of the proposed approach. The proposed model performs better than existing approach in minimizing the capacity cost loss of shortage, surplus, and migration. Therefore, the proposed approach can be employed as embedded decision support mechanism for smart production solutions for Industry 4.0.