| Summary: | 博士 === 國立清華大學 === 工業工程與工程管理學系 === 98 === The first purpose of this dissertation is to present a hierarchical planning framework for a thin film transistor–liquid crystal display (TFT-LCD) production chain in an assembly-to-order (ATO) environment. The TFT-LCD manufacturing process, or the TFT-LCD production chain, comprises three sequential steps, namely: the Array, Cell and Module processes. Many special characteristics and constraints, such as product grade constraints, site-eligibility constraints and key material availability constraints, are inherited in this production chain. The globally distributed nature of production planning and scheduling activities of TFT-LCD production leads to an urgent need for an integrated planning and scheduling framework to balance supply and demand problems. There are three main features of this integrated framework: (1) hierarchical planning (2) combined push-pull planning process (3) modular planning approach. A review of OR methods applied in TFT-LCD planning and scheduling for various planning modules are given and the importance of critical material planning and capacity planning is identified.
The second purpose of this dissertation is to study the critical material planning which is one of the most important planning modules in the proposed hierarchical planning framework. The module process is the material-oriented and discrete production environment that combines many critical materials such as integrated circuit (IC), printed circuit board (PCB), and backlight (BL) into the final TFT-LCD products according to different customer requirements and preferences. There exist many specific characteristics such as alternative bill of material (ABOM), customer preference for ABOM, and purchase quantity ratio occurring in the TFT-LCD industry. The traditional MRP mechanism that calculates the purchase quantity by exploding a fixed BOM structure is difficult to apply to CMP. In response to this challenge, this study formulates a single-period and multi-period CMP problem as nonlinear programming models represented by the network graph to optimize the purchase quantities of all suppliers under the existence of specific characteristics. Finally, a numerical example from a real TFT-LCD manufacturer is illustrated to clarify the multi-period CMP model and the managerial implications of the customer preference factors and the purchase quantity ratio are also correspondingly discussed.
The final purpose of this dissertation is to study the capacity planning problem in the hierarchical planning framework. Capacity planning is critical to TFT-LCD industry due to its complex product hierarchy and increasing product types; the coexistence of multiple generations of manufacturing technologies in a multi-site production environment; and the rapidly growing market demands. One key purpose of capacity planning is to simultaneously determine the profitable “product mix” and “production quantities” of each product group across various generation sites in a particular period and the optimal “capacity expansion quantity” of specific product groups at a certain site through the acquisition of new auxiliary tools. This study proposes a mixed integer linear programming model for the multi-site capacity planning. A shadow-price based heuristic is developed to find a near-optimal solution. Our computational study indicates that the proposed method performs better and is more robust than the conventional branch-and- bound (B&B) algorithm. In addition, since the demand forecasts faced by TFT-LCD manufacturers are usually inaccurate, we develop a scenario-based two-stage stochastic programming model to seek a robust capacity allocation and expansion policy against demand uncertainties. An expected shadow-price based decomposition is constructed to obtain a near-optimal solution in efficient manner. According to our numerical study using real industry cases, the stochastic capacity planning model significantly improve system robustness and outperforms traditional deterministic model under demand uncertainties.
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