The mission
NETVIBES, a Dassault Systèmes brand, and Avencore have designed a solution combining industry expertise with data and Artificial Intelligence-based tools to enhance an automotive manufacturer’s resilience to market volatility.
- Anticipate the impacts of market volatility on product costs.
- Identify alternatives and purchasing savings opportunities to protect margins.
The challenges
In a context of high price volatility in markets (raw materials, energy, electronic components) and the pursuit of energy efficiency, the ability to aggregate and analyze energy and techno-economic data of automotive parts is a key factor in securing the cost and energy competitiveness of vehicles produced. However, most historical cost breakdown models do not consider the breakdown of materials x manufacturing processes, nor do they measure the energy consumption of parts.
The approach
Avencore and NETVIBES have created a data model that promotes transparency between suppliers and the client through:
- Breaking down parts by raw material and manufacturing processes first (by leveraging internal and external data) to analyze the consumption of raw materials, energy, and components.
- Then extrapolating the results to an entire product (vehicle) and a given supplier’s production site, thanks to an AI-based inference calculation.
The model makes it possible to quantify the impact of market volatility on the various costs.
The digital solution is the Virtual Twin of the product enriched by all existing value chain data (external data, internal company data, extended enterprise data).
The impacts
- Proof of Concept (POC) completed in 7 weeks on a selection of 4 suppliers covering over 3000 part references
- Identification of energy efficiency potentials between 5% and 10%
- Identification of a negotiation potential equivalent to 7.5% of the initial price increases demanded by suppliers
