Glass Tube is one of the main components for fluorescent lamps as it contains all the other components to generate light. Glass tube industry faces a decline in demand in Egypt. This is attributed to two factors: currency floating and new lighting technologies. In response, glass tube manufacturers decided to diversify their products. This required the integration of Make-to-Stock (MTS), which is used usually for glass tube manufacturing, and Make-to-Order (MTO) which is used to fulfill demands for diversified products. In this thesis, Production policy is proposed to plan for MTS & MTO production. This policy determines when to produce broken glass (cullet), MTS product or MTO product. Priority is given to Cullet which is used as raw material in glass making. The second choice is to produce MTS product, and excess capacity is used to produce MTO products. Once MTO order is fulfilled, the choice is made to either produce cullet or MTS product. The policy defines two levels for cullet inventory and MTS product inventory. If cullet inventory reaches the lower level, cullet will be produced until the inventory level reaches higher level. If the cullet reaches the higher level or the level is decreasing towards lower level, products will be produced. The type of product is determined according to the inventory level of MTS product. If the MTS inventory level is lower than high inventory level, MTS product will be produced. Once it reaches high inventory level, MTO product will be produced. A simulation model is developed to simulate glass tube production. The model is divided into three interconnected modules: production, order fulfillment and decision. The model was verified and validated through different cases. Based on the simulation model, an optimization algorithm is applied to select optimum parameters for proposed policy with the objective of minimizing total costs. The proposed production policy proved its effectiveness in reducing total cost in glass tube manufacturing. Sensitivity analysis was performed to show the effect of raw material prices and energy price on the solutions obtained by optimization algorithm. Increase in raw material prices has effect on production parameters; however, it has no effect policy parameters. Increase in energy prices has effect on production parameters and policy parameters
