Aggregate Production Planning (APP) model with fuzzy demand and variable system capacity is proposed in this research for a practical APP problem. A conventional APP problem assumes crisp market demands and also limited capacity by fixed hardware. In the proposed model, the difficulty in estimation crisp demands is relaxed by using fuzzy demand which also increases the flexibility of estimation and obtains the better production plan that can increase profit. The new approach to handle the fuzzy demand by integrating the possibility level of demand is proposed. Moreover, the limitation of system capacity is resolved by allowing additional investment in small machines and equipment. This investment can increase the necessary production capacity and eliminate the bottleneck of the system. Three performance measures, based on the Theory of Constraints (TOC) concept, which are currently used in many organizations, are used to evaluate performance of the model. It is found that the proposed model can generate higher performance than conventional APP models. Significance: In medium range capacity planning, market demand is usually uncertain in nature and the limitation of the production capacity is not only limited by workforce level but also limited by hardware or equipment. The fuzzy APP model proposed herein is more flexible and realistic approach to solve APP problems than the conventional models based on TOC measures. [ABSTRACT FROM AUTHOR]