Case Study Production Network Optimization

An application case study of the production network optimization model is reported in Chapter 5. In this context the integration of the optimization model into a planning tool to support interactive explorations of the solution space is demonstrated and guidance on how to develop the data required for quantitative strategic network design analyses is provided. Additionally, important analyses that can be performed using the proposed optimization model are introduced and improvement potentials identified in the course of a pilot application in industry are explained. 

Three model areas can be distinguished. Model areas allow defining separated areas in the value chain network to be optimized separately. Model areas can be defined by clustered resources and/or products that have clear interfaces. Defining model area eases the implementation of a comprehensive value chain planning optimization model for a complex value chain network the optimization model can be tested for parts of the value chain network with limited data complexity before extending the model to the entire network. Three model areas are defined in the industry case study ... 

The optimization model presented in this chapter was developed to design a supply chain distribution network for a consumer goods company located on a Caribbean island. This company is a major global competitor in its area, selling approximately 20 billion per year worldwide. The company has markets in more than 150 countries, and its brands are in first or second position in most of these markets. The country analyzed in this case study has sales of approximately 86 million per year. Its market includes 71 customers (66 retailers and 5 independent distributors), and it receives products from four manufacturing plants (all outside this country). To distribute the demand in this region, the company owns one distribution center located on this island. 

The framework was evaluated with a case study focusing on design of a lignocellulosic biorefmery. The results showed that the tool could find new optimal processing paths for different scenarios (objective functions) which provide a better, more efficient production process and less utility, waste, investment, and operating costs using the expanded biorefinery network. The optimal biorefmery pathways were further analyzed with respect to sustainability and environmental impact, which revealed further options for sustainability... 

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