A global leader in the transport and mobility industry with a commitment to creating value through sustainable vehicle design and mobility services, the company’s transformation strategy harnesses the virtual twin experience to connect data across the product lifecycle. Extending these data science capabilities to costing and purchasing functions would equip the organization to better navigate volatile materials markets and ensure an agile supply chain.
The company adopted the NETVIBES Material Cost Intelligence solution as part of its virtual twin, which is based on the Dassault Systèmes 3DEXPERIENCE© platform on the cloud. The solution provides contextualized insights by aggregating business and design data around a unique point of reference. This allows the organization to build agility into its supply chain and ensure that vehicle design is always aligned with business priorities.
NETVIBES Material Cost Intelligence has enabled the company to extend its virtual twin experience beyond design and engineering, empowering a new set of people to contribute to its technological and digital transformation. The solution’s powerful data science capabilities allow teams to work together across the enterprise, ensuring that design, engineering and quality KPIs are met while maximizing cost efficiency.
A New Economic Context
In a rapidly evolving automotive industry, vehicle manufacturers are under pressure to get innovative, sustainable vehicles quickly to market. To do that, they must develop compelling vehicle designs, master the complex software and systems involved, and make sure everything complies with multiple regulations. At the same time, these organizations are grappling with a new economic context as health crises, climate change, geopolitical tensions and other factors make the availability and cost of raw materials increasingly volatile. Bringing agility and stability to the supply chain is now essential for manufacturers to align market-leading vehicle design and development with business needs.
A leading vehicle supplier focused on sustainability is meeting these challenges head-on through its business transformation plan, which sees the company shifting its strategy from volume to value creation. Launched in 2020, the strategy is supported by the virtual twin, a digital backbone for the entire enterprise that is based on the 3DEXPERIENCE platform.
“We expect a lot of value from our transformation,” said the head of PLM. “More simulation and less physical testing will reduce costs. Being able to solve problems in the virtual phase of vehicle development will improve accuracy and enable more right-first-time designs, bringing a big reduction in project lead times and faster time to market. To facilitate that, we built our technology backbone around robust, agile and multi-process design; mastering systems and software; and desiloing upstream and downstream data.”
The company has partnered with Dassault Systèmes for more than 20 years, adopting the 3DEXPERIENCE platform on the cloud in 2021. The platform combines advanced solutions including artificial intelligence, machine learning, and collaborative business processes with data-enriched 3D modeling. Industry expertise is an integral part of that, as Dassault Systèmes continues to develop unique data science offerings that are closely linked to the virtual twin of the product.
With its designers and engineers already using the platform to collaborate around virtual twins of its vehicles and enterprise, the company’s next step was to extend the experience further into the value chain. It took less than six months to deploy NETVIBES Material Cost Intelligence, bringing strategic business functions like costing and procurement onboard.
A Common Language for Collaboration
The company’s extended virtual twin capabilities break down silos across legacy systems and provide a single place where users can track and make informed decisions. Product engineering teams can collaborate better with process engineering, design or purchasing, for instance, making it much easier for everyone to align with the key performance indicators of multiple stakeholders.
Using 3D as a common language helps everybody to understand each other.
“Working with 3D makes exchanging information and collaborating much more efficient and easier, including in an international context where Romanian teams collaborate with Indian, French or Japanese teams, for example,” said the vice president of Engineering. “Discussions around a 3D object eliminate the risks of misunderstanding compared to using static spreadsheets. Purchasing can use the 3D object to show and discuss issues with a supplier and get quotes much more efficiently.”
We want to build an enterprise platform not only for product lifecycle management, but for all departments and the extended enterprise.Vice President of Engineering
the company’s virtual twin is built on the 3DEXPERIENCE platform, it goes beyond traditional assumptions about what digital twins can do. It connects data from internal and external sources and uses AI, machine learning and analytics to visualize it in the light of business and industry knowledge. With the data mapped onto the 3D virtual model, users gain contextualized insights to drive better decisions.
“This is about combining real-world data from multiple sources and putting it in the context of the company’s business to help it make the right decisions,” said Morgan Zimmermann, CEO of NETVIBES. “Having a data lake is not enough. To understand the data, you need to put it in the context of the business and industry you’re operating in.”By extending these capabilities to costing and purchasing functions, the company is ensuring that users have the knowledge to weave business priorities into the design and engineering cycle.
“Our extended virtual twin is based on NETVIBES technology,” said the head of PLM. “It creates a dashboard that combines legacy data with platform data, including 3D. This provides a single place where the costing team can instantly see any gaps between the target price for a part and the actual price negotiated by purchasing, for example. If they want to find a more cost-efficient alternative, they can collaborate with the engineering team to identify a similar part from the 3D parts catalog and analyze it for suitability. Then it can be sent to the engineering team who will mesh, simulate and validate the part replacement in the virtual twin.”
This is about combining real-world data from multiple sources and putting it in the context of the company’s business to help it make the right decisions.Morgan Zimmermann, CEO of Dassault Systèmes NETVIBES
Improving Quality and Cost
The virtual twin on the 3DEXPERIENCE platform provides actionable, data-driven insights into a vehicle, so users can find innovative ways to balance vehicle design with business priorities.
By using NETVIBES Material Cost Intelligence to extend this capability to its costing and quality teams, the company has made it easier for them to work together on improvements to vehicle design. Quality assessors can retrieve reports on vehicles including after-sales data, identify quality improvements in the virtual twin, and work seamlessly with costing and purchasing teams to make sure their changes align with business objectives. Equally, as raw material prices change, the costing team can receive alerts about cost increases on specific vehicle parts. They can then work with engineering and quality teams to find an alternative that meets cost, quality and design KPIs.
“The idea is to enrich the 3D digital model with all the data from our legacy systems around purchasing and costing, and quality data from our customers and factories,” said the vice president of Engineering. “By making all of this data accessible in the platform and applying business intelligence, we can identify savings opportunities on vehicles with immediate results, and our customers will benefit from quality improvements on vehicles already in the field.”
Predicting Price Evolution
Volatile markets bring unexpected fluctuations in cost and availability, but the advanced analytics built into NETVIBES Material Cost Intelligence helps the company to prepare for any surprises.
For instance, users can aggregate equipment designs, configurations, historical data and forecasts, and test different design scenarios using various materials in a virtual twin to understand, anticipate and optimize vehicle price and cost.
Users can also generate and analyze a commercial mockup of the vehicle to understand how raw materials and procured parts contribute to the total cost. Based on this, they can then measure – and precisely forecast – the impact of evolving raw material prices on the cost of each car. Pricing teams can use these insights to find the best trade-offs that will minimize the need to increase vehicle prices while protecting return on investment.
Predictive analytics also support the running of what-if scenarios that anticipate the fluctuation of raw material costs, so users can create effective strategies to mitigate the risks. In addition, historical engineering and procurement data can be analyzed to drive effective negotiation with suppliers.
By making all of this data accessible in the platform and applying business intelligence, we can identify savings opportunities on vehicles with immediate benefits for the company, and our customers will benefit from quality improvements on vehicles already in the field.Vice President of Engineering
A Platform for the Future
Through its business transformation strategy, the company aims to establish itself as a major provider of energy and mobility services by 2025. Leveraging NETVIBES solutions on the 3DEXPERIENCE platform marks a big step towards that goal. By extending collaborative data science capabilities across its value chain and subcontractors, the company is empowering new sets of users to contribute to its technological and digital transformation.
“We’re targeting 20,000 platform users worldwide,” said the vice president of Engineering. “Our ambition is to deliver value as quickly as possible and to build an enterprise platform not only for product lifecycle management, but for all departments and the extended enterprise. Ultimately, we want to evolve from a world where we exchanged information using emails, to a world where the platform is at the center of collaboration – a place where people and data cohabit in real time.”