Planning and Scheduling in the Automotive Industry

What it is about

You learn how planning and control systems in the automotive industry work and how quantitative methods are applied to solve concrete operational problems. By the end you can apply modelling and optimization approaches for production networks, ramp-ups, MRP, lot sizing, and assembly lines, and use modern software tools (e.g., CPLEX, R, Python AI libraries) to solve real cases.

What you will be able to do

• Overview of different manufacturing environments and supply chain management in the automotive sector
• Modelling strategies for aligning customer demand and order-to-delivery processes
• Linking product variety with order fulfilment strategies
• Definition and application of mass-customization strategies
• Application of Bayesian forecasting, AI- and deep-learning models as well as error measures
• Use of optimization techniques (e.g., linear and mixed-integer programming)
• Use of stochastic models for uncertain planning cases
• Calculation of complex product launch and ramp-up scenarios
• Application of Material Requirements Planning and understanding of the procurement cascade
• Application of balancing and sequencing methods for assembly lines

What the module consists of

• LectureDelivery of the fundamental content through lectures and presentations
• Integrated exercisesApplication of what has been learned to case tasks and discussion of results in the course

Teaching method

• Lecture with integrated exercisesDelivery of content and direct application in case studies for deepening
• Self-study of the proposed literatureTo consolidate and extend the knowledge covered in the sessions