The frequently changing order stream and high product variety require robust planning and control approaches, as well as a flexible system structure in order to fulfill the highest possible customer service level and to keep the production costs on a reasonable level. In the paper, a combined production planning and capacity control method for assembly lines is proposed aiming at balancing the workload of the human operators and decreasing the overall production costs on a given time horizon. Instead of using the idealistic cycle times and simple manufacturing control rules, the proposed planning and control methodology is based on adaptive calculations taken from continuously updated historical production data. The manufacturing execution-level data is applied for building regression models predicting the capacity requirements of the future production scenarios. Besides, the historical data is also used as direct input of discrete-event simulations, to determine the proper control policies of human operator allocations for the different scenarios mentioned above. In order to calculate reliable and feasible production plans, the regression models and control policies are integrated in a mathematical programming model that minimizes a cost function representing the total production costs.
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