Leveraging Graph-Based Layering for a Revolutionary Leap in Automotive Manufacturing

eBOM and mBOM outline two engineering worlds, R&D-Design and manufacturing

In the automotive manufacturing sector, the Engineering Bill of Materials (eBOM) and Manufacturing Bill of Materials (mBOM) dictate the development and production life cycles. The eBOM, generated during the design and research phase, outlines the foundational blueprint of the vehicle, detailing every aspect of its architecture. The mBOM translates these abstract concepts into tangible components and assemblies crucial in the manufacturing stage.

The industry still largely depends on outdated systems that create siloed data and disjointed processes. These issues hinder the smooth transition from eBOM to mBOM, leading to delays and inefficiencies in the product realization process.

But the disconnection of eBOM and mBOM create issues in cascade

Presently, data is dispersed across PLM, CAD, and ERP systems obstruct a smooth flow from eBOM to mBOM, thereby stalling the product development process. This scattered landscape cripples cross-functional visibility, hiding potential bottlenecks and areas ripe for optimization.

Furthermore, the lack of a centralized system magnifies the adverse effects of revisions and changes, fostering a disconnect among engineering teams and impeding the leverage of existing engineering knowledge. The prevailing setup stifles innovation and leads to missed opportunities for performance improvement.

Verbatim in the industry are as such:

“We can not grow our industrial activities with the current BOM. We do artisanal work, not industrial.” World Top 5 Auto supplier

“We (manufacturing) receive a PDF, a plan, and they say to us. It’s like saying “here, understand the change”. Everyone has their own area of knowledge, and it’s not easy to understand the impact of your change on the other person.” World Top 3 car manufacturer

Graph is the way to reconcile BOMs

The integration of graph databases presents a viable solution to overcome the limitations of legacy systems and the organization that comes with it. By fostering connectivity and synchronizing technical information from diverse organizational facets, graph databases effectively dismantle the barriers erected by siloed data sources.

Through the deliberate capture of relationships between various entities – such as parts, assemblies, or processes – graph databases facilitate advanced analysis and insights. This shift creates an ecosystem where data evolves from a static entity to a dynamic collaborative tool, offering unprecedented value delivery. img[]

The operational benefits for the auto industry are huge

Transitioning to a graph-based BOM database promises transformative impacts on business operations. It fosters streamlined processes that significantly reduce time-to-market durations. By enabling real-time insights, it already helps the top 1% companies:

• Eliminating siloed and sequential technical developments
• Better dealing with complex products (number of components, multi-level, structure, SuperBOM) ;
• Removing asynchronous changes
• Cutting the number of iterations / meeting by a factor of 5
• Reducing errors by 90%
• Identifying the constraints of the downstream operations

Moreover, this approach improves output quality by leveraging existing engineering knowledge to unveil avenues for performance enhancement. The enriched context brought about by graph databases empowers teams across various functions, ensuring optimized results in line with the company’s broader objectives.

By the way, that’s how Tesla ramped up its Model 3

Tesla custom developed an end-to-end Product structure platform to enable the ramp-up for the Model 3. Developed for Engineering, Design and Manufacturing with BOM processes and CAD informations, it unlocked BOM variance management, single change management between all the functions and for the business faster iterations, knowledge consolidation for better vertical integration and design first principles.

And Tesla built this platform on top of existing systems, avoiding the big bang induced by replacing such a heavy IT architecture.

Cognyx: supercharge your business in 6 weeks

As organizations gear up to undertake this transformative journey, platforms like Cognyx are coming to the fore as enablers of a smooth transition to a graph-based BOM database. Cognyx leverages the relationships between different entities to foster a common understanding of the product, unveiling insights previously obscured by older data systems.

Cognyx integrates seamlessly with existing setups, negating the need for extensive IT overhauls. It enhances existing data with rich semantics, fostering a landscape characterized by enhanced data flows, faster market readiness, and heightened engineering contributions.

Remarkably, Cognyx promises a transformative shift within a span of 6 weeks to prove a first use-case. The goal is to allow companies, in less than 6 months, to realize a full graph architecture of their product data in order to unlock AI applications such as generative design, process optimization, standardization etc.