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Hierarchically integrating the production planning and scheduling to optimize the production planning process of a beverage compan

Horst, J. ter (2013) Hierarchically integrating the production planning and scheduling to optimize the production planning process of a beverage compan.

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Abstract:This research assesses the currently used production planning process of Vrumona, with the aim to improve the process. As the trade-off between production- and inventory costs is not known, Vrumona expects that the production planning process can be improved. Currently, the production planning software Advanced Planning (AP) constructs the production plan. The production plan is used by the production planner to construct the production schedule. AP uses cost priorities and takes the constraints of the Syrup- and Packaging department into account to construct the production plan. This production planning approach does not use the internally available inventory capacity as a restriction, making this planning approach not account for higher inventory costs when soft drinks need to be stored externally. The constructed production plans cannot fulfil the customer demand. Therefore, the production planner modifies the production plans, with the aim to meet the customer demand. The purpose of this research is to structurally improve the production planning approach and minimize the total production- and inventory costs, while maintaining the current service level of 99.5%. For this research we define the following research question: How can Vrumona structurally improve their production planning approach to minimize the production- and inventory costs, while maintaining a customer service level of 99.5%? This research focuses on two of the nine production lines. Production line 4 is selected, as this production line has limited available production capacity. Production line 10 is selected, as this production line has excessive production capacity. Production line 4 bottles 20cl glass bottles for the Out of Home industry and production line 10 bottles 1.5 litre cartons for the Retail industry. With these production lines, we can show how the planning approaches perform for both types of production capacities. To show how the production planning process can be improved, this research developed three planning approaches for the production planning process of the Supply Chain Planning department. The research compares these planning approaches with the currently used planning approach AP. The planning approaches focus on the tactical production planning problem. In order to compare these approaches, it is important to define how much changeover time the constructed production plans use. Therefore, we optimize the production sequence per production week of the production plans with a scheduling algorithm (SA) that uses sequence dependent changeover times. One of the developed planning approaches uses the algorithm of AP software, and uses real changeover- and inventory costs rather than the currently used cost priorities. The other two planning approaches use an Integrated Production Planning and Scheduling (IPPS) approach to construct a production plan. These IPPS approaches take product families into account, which make the approaches willing to combine soft drinks of the same product family in the same production week. This provides a better approximation of used changeover time in a week. Moreover, these planning approaches take into account the internal inventory capacity level, which defines when soft drinks need to be stored externally for higher storage costs. In addition, these planning approaches can extend the available production capacity, resulting in higher costs. The research compares the following four planning approaches: Current (AP/SA): Software Advanced Planning (AP) The current planning approach uses the Advanced Planning software, which uses cost priorities. Alternative 1 (MILP/SA): Mixed Integer Linear Programming (MILP) approach This planning approach uses the mathematical optimisation technique that attempts to construct a production plan within the defined constraints with the lowest costs. Alternative 2 (AS/SA): Adaptive Search (AS) and Simulated Annealing (SA) approach This planning approach constructs an initial production plan (AS), where the lot-sizes are computed with the Economic Production Quantity (EPQ). The Simulated Annealing (SA) algorithm optimizes the initial production plan to lower the total costs. Alternative 3 (AP/SA real costs): Software Advanced Planning (AP) with actual costs This planning approach uses AP, but uses actual changeover- and inventory costs instead of the currently used cost priorities.
Item Type:Essay (Master)
Vrumona, the Netherlands
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Industrial Engineering and Management MSc (60029)
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