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Forecast for vehicle components demand and order planning

  • Surpluses
  • Reference: Forecast for vehicle components demand and order planning

Challenge

  • Development and operation of a system to support the planning process of vehicle properties (equipment characteristics)
  • Weekly provision of a model to forecast the demand quantities on component level with a 12-month time horizon
  • The model is to consistently integrate the following existing data:
    • Rules defined by sales and logistics
    • History of vehicles built in the past
    • Specifications based on capacities, orders, forecasts etc.

Solution

Markov networks integrate structural and probability information: 

  • The structure of the Markov network is determined based on logic and sales rules
  • The initial distribution of the network is “learned” based on the history of built vehicles (dependencies, relevance)
  • Planning specifications are consistently incorporated through changes to the probability distribution

Benefit

  • Forecasting demand quantities on component level is possible with high quality
  • Component requirement bottlenecks are detected at an early stage
  • Inconsistencies within the rules or between rules and specifications are detected
  • Inconsistencies in the planer specifications are automatically compensated for and can be analyzed
  • Order planning can be based on a consistent model

Your contact

Dragan Sunjka

Lead IT Consultant Automotive & Manufacturing

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