Discrete production control is associated with making numerous decisions related to task allocation to machines, resource configuration, cost and production time optimization, outsourcing, etc. These decisions often need to be made simultaneously, fulfilling multiple constraints of the production system, customer requirements, etc. The paper introduces an original mathematical decision support model for discrete production problems. It has been implemented in a mathematical programming environment for the production process of rolling bearings in an actual factory. Additionally, due to the high computational complexity of discrete models, a procedure for reducing the size of the modeled problem was proposed, resulting in reduced solution search times. Numerous computational experiments were also presented, confirming the utility of the proposed model.