AI4Cast

In the project ‘AI4Cast’ HOWest, Sirris and VIL have researched how Artificial Intelligence can be implemented for better forecast and planning of supply chains.

 

status: Closed | theme: Digital transformation | type: Regional

Supply chains are getting more and more complex. Just-in-time deliveries have become the norm. Unexpeted events cause problems that affect multiple companies in the logistics chain. The bull whip effect causes unnecessary stock in the supply chain.

Information about demand fluctuations or incidents are rarely shared with all parties involved, which leads to inadequate preparations. This causes extra costs, like extra transports, overtime, temporary employment and the rent of materials or spaces. Delays and decreasing quality lead to dissatisfied customers. The forecast and planning of supply chains must therefore be chain-wide and as accurate as possible.

Planning today is usually limited to the company or the direct service provider and problems are being moved up to the next link in the chain.

All companies involved, as well as the consumer will benefit from chain-wide, realtime and proactive supply chain forecast and planning. This will only be possible through chain-wide cooperation and the use of modern technologies.

GOAL AND OPPORTUNITIES

In this project HOWest, Sirris and VIL will research how modern technologies, like blockchain, new data encryption methods and Artificial Intelligence can contribute to sharing and analyzing data for chain-wide, realtime and proactive supply chain forecast and planning.

Results

  • Artificial Intelligence (AI) provides important support in making good forecasting in the supply chain
  • Quality data and willingness to collaborate are crucial to successfully deploy AI applications
  • In an ideal world, forecasting is not set up unilaterally but there is supply chain collaboration between companies that are part of the same supply chain
  • Standardization of data is of great importance
  • Algorithms are only as good as the data they can access. The right AI techniques applied to complete and valuable data minimize the margin of error in planning and forecasting. In addition to increased efficiency, they also yield cost savings
  • VIL has developed a roadmap for optimizing companies’ forecasting with AI

 

Practical

Start: March 2020
Total lead time: 24 months

Participating companies

14 companies: Atlas Copco Airpower, Colruyt Group, ECS, Eutraco, Foresightee, Globis, H.Essers, ICO, Let Us, Procter & Gamble, Rotom, The Grain, Trafuco and Unilin.

 

Would you like to know more?

Contact
Dirk Jocquet (dirk.jocquet@vil.be)

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T: +32 3 229 05 00
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