## 4 Applying the Model for Production Control to the Metallurgical Industry through Simulation
### Model Formulation  
Later, the logical differences between the models are to be described. Both models have the same assumptions as well as the same framework conditions:  
* Time horizon: The tasks are assigned according to their temporal relevance at different planning levels. According to the St. Gallen management model, the strategic planning level has a planning horizon of several years [29] (p. 80). Based on it, five years were chosen for the simulation of the two models. * Production mix: Seven different production families with 12 different production routes were considered. * Finite capacity for all production steps. Production capacity as the sum of the capacities of the machines within a machine group. * Processing times depend on the product family, on the variant of product family and on the weight of the production unit. * Same transport times between buffers and machine independently of the product family. * Infinite transport capacity between machines along the production process. * Infinite stock capacity before, along, and at the end of the production process. * Raw and operating materials are always available for the production process. * Assumed that in 3 weeks a batch for a steel type can be produced. * Quality problems or rework lead times are not considered. * Personal planning not considered. * Depending on the machine group, 15 or 21 shifts per week. * Production units are the agents that flow along the production process. * If the load of a bottleneck is too high, the units wait to get a release date. If there are a certain number of units waiting for it, the manufacturer loses the demand that influencing the bottleneck until the number of units falls below the limit. Table 1 describes the main differences between both models. The push control starts the production in the steel mill, as far as the orders are in the order intake, since it follows the principle that the machines must not remain still. This causes the production orders to start too early or too late, usually too early, and as a consequence, the WIP increases. In addition, the delivery date determination is not determined on the basis of the bottleneck resources per product family. This, together with a local optimization in the individual production steps, leads to situations with high stock, long lead times and poor on-time delivery. On the other hand, in the pull control, order release into production is based on the load of the bottleneck resources. For each product family, there are certain typical bottleneck resources to analyze (e.g., indirect stock and direct stock before a machine group converted to processing hours). Indirect stock of a machine group is the stock that has to be processed by this machine group, which is already in production and that is not ready to initiate production in this machine group. By knowing the total amount of processing hours needed to process the direct stock and the indirect stock, the model can determine which one of the machine groups is a bottleneck resource. Therefore, delivery dates are determined by dynamic lead times, which are determined on the basis of the system load. The third difference is the introduction of a global priority rule, which forms the basis for sequencing before each production step. The priority of a position (%, as a percentage) is determined on the basis of the time consumption at the delivery date, the higher the priority the sooner the position has to be processed in that specific production step. This means that at every time period priorities are recalculated to create a list of next production units to be processed in each machine group to optimize the system globally by processing the critical units according to promised delivery date at first. The two models have moving bottlenecks depending on the product mix that are in a particular moment in production process. The pull-control model can anticipate the bottlenecks by knowing the processing time needed in the current bottleneck resources.