Thermal Stress Analysis and Optimization of Plastic Ball Grid Array Assembly

• Main Authors: Jian Shiang Juang, 莊建祥
• Other Authors: Yuan Mao Huang
• Format: Others
• Language: zh-TW
• Published: 2000
• Online Access: http://ndltd.ncl.edu.tw/handle/01274666111343577613

碩士 === 國立臺灣大學 === 機械工程學研究所 === 88 === A Plastic Ball Grid Array assembly(PBGA) is basically a composite structure consisting of different materials. Because each of these materials has different elastic modulus and coefficient of thermal expansion(CTE), thermal stresses are generated in the interfaces of these materials when the package is subjected to temperature change and this will result in warpage of structure. In recent years, many studies of PBGA had been carried out to investigate the impact of thermal stresses by those material properties in order to investigate the distribution and causes of failures. Introducing the concept of optimization into the design of PBGA will efficiently avoid possible failures and increase the working time and reliability. Simulated Annealing(SA) algorithm is one of the global optimization methods which can be used to solve problems including discrete variables. Finite element method was combined with SA to find the optimum solutions of materials and geometry which result in minimum stress of chip after the encapsulation process. Before carrying out optimization algorithm, finite element method and multi-layered theory were conducted to simulate the cooling of PBGA after encapsulation process to investigate the distribution of thermal stresses induced in the chip and the warpage of assembly. Furthermore, feasibility of simplifying 3D model into 2D model in finite element method analysis was evaluated and then the model used in the analysis of optimum design can be built up. 2D plane strain is chosen as the most suitable model of finite element method for the optimum design, and JEDEC guidelines are introduced to bound the conditions of variables. After the numerical computation of th optimum design problem has been implemented, optimum combinatorial solution can be found and the impact significance of each design variable on the design objective will also be discussed.