Application of multi-fidelity simulation modelling to integrated circuit packaging. (2016)

• Record Type: Journal Article
• Authors: Hsieh, Liam Y.; Huang, Edward; Chen, Chun-Hung; Zhang, Si; Chang, Kuo-Hao
• Is Part Of: International journal of simulation and process modelling. Volume 11:Number 3/4(2016)
• Page Start: 259
• Page End: 269
• Publication Date: 2016
• Subjects: machine allocation -- semiconductor manufacturing -- multi-fidelity simulation -- simulation optimisation -- ordinal transformation -- optimal sampling -- modelling -- integrated circuits -- IC packaging -- time-to-market -- computing budget allocation; Management -- Computer simulation -- Periodicals; Mathematical models -- Periodicals; Operations research -- Periodicals; Simulation methods -- Periodicals; 003.05
• Languages: English
• ISSNs: 1740-2123

Abstract

In semiconductor manufacturing, time-to-market is critical to maintain a competitive advantage through achieving customer satisfaction. Inefficient ways of utilising production resources will lead to a long cycle time. Therefore, machine allocation becomes an essential production decision in many practical manufacturing systems, especially for integrated circuit (IC) packaging. IC packaging is the process of encasing the finished die in a package in order to prevent corrosion and physical damage. Advanced IC packaging techniques add even more complexity into the production system, so reliable average cycle time of this complex system becomes difficult to obtain. We propose a new simulation optimisation framework with multi-fidelity models to study an IC packaging case of the machine allocation problem to pursue a minimum average cycle time. This framework consists of two methodologies: ordinal transformation (OT) and optimal sampling (OS). The OT first employs the low-fidelity model to fast observe all designs, and extracts insightful information from this model by transforming the original design space into an ordinal space. It follows that OS efficiently allocates the computing budget for searching the best design via high-fidelity simulations. An empirical study based on real data was conducted to validate the practical viability of the proposed framework.