PLM becomes the connective layer for software-defined vehicles

Sophie Lindqvist

Three core systems—product lifecycle management (PLM), enterprise resource planning (ERP) and manufacturing execution systems (MES)—sit at the center of a new approach to connected vehicle programs, according to Andreas Eek, account executive at Siemens Digital Industries Software.

Eek said manufacturers are moving away from fragmented IT estates toward a smaller core, but centralization alone will not solve their data problems. Engineering, manufacturing and service personnel need shared context, allowing factory teams to see engineering decisions earlier and changes to proceed without repeated feedback loops and costly rework.

Why is PLM broader than engineering data?

PLM has long managed engineering information and design workflows. Over the last 10 years, rising software content, electrification, modular platforms and service-oriented business models expanded its remit from mechanical data to software modules, electronics and their compatibility with mechanical-electronic systems, known as mechatronics.

For a customer-configured vehicle to remain producible, PLM must combine a modular product structure with integrated configuration rules. Eek said manufacturers must manage mechanical parts, mechatronic parts and software modules as one assembled vehicle, ensuring both correct initial build and compatible over-the-air (OTA) updates: “Once an update goes out, it has to work.”

What makes commercial vehicles harder to configure?

Commercial vehicle original equipment manufacturers (OEMs) operate platform families through continuous change for a decade or more. Unlike high-volume passenger-car programs, they must support numerous customer applications without compromising manufacturability or functional compatibility.

Some OEMs maximize configuration freedom, while others restrict options to optimize production and build larger volumes of specified vehicles. Broad commercial applications therefore require sophisticated configuration rules and modular bills of material (BOMs), according to Eek.

Commercial-vehicle programs also place greater emphasis than passenger-car programs on ensuring that modules remain usable across a vast number of configurations. That requirement makes PLM particularly important for truck and van manufacturers with long-lived, modular platforms.

How can a digital twin stay accurate?

Vehicles accumulate changes throughout their service lives, including repairs, dealer retrofits and third-party modifications. Work performed outside the OEM ecosystem can leave the manufacturer’s digital record out of step with the vehicle’s physical configuration.

Eek warned: “If you do some maintenance on a vehicle, by yourself or by a non-authorized dealership, you will never update that DNA, and then the OEM will not be able to understand what's fitted to that vehicle.”

The vehicle DNA forms part of a comprehensive digital twin, a live digital representation of what was engineered, manufactured, configured and maintained for each vehicle. Eek expects that record to become more important as trucks and vans adopt software-defined functions.

PLM must also prepare manufacturers for transportation-service and uptime-guarantee contracts. Eek said serviceability, maintenance workflows and lifecycle-cost visibility need to be embedded from the start, because OEMs selling uptime assume responsibility for quality throughout the vehicle’s operating life.

Can AI improve PLM without losing control?

Eek sees AI as a practical search and maintenance layer for the interconnected records held within PLM. The data volume can force engineers to spend considerable time locating accurate requirements, test cases and linked components.

AI could surface those items while reducing administrative work, provided its results draw on trusted engineering, manufacturing and service context. Eek also expects it to slow the deterioration of model-based engineering artifacts, which often become unusable as people maintain them manually.

Simulation information must also move closer to the product record. Structural, computational fluid dynamics (CFD), manufacturing and service simulation outputs should remain available within product context, according to Eek.

He said linking those results to the actual product would help manufacturing, service and operational teams understand how a design performs across its life. The mechanism is straightforward: simulation remains reference material until engineers can connect it to a specific vehicle and its subsequent changes.

What must OEMs and software vendors connect?

PLM vendors and OEMs must preserve specialist engineering tools while establishing connected, trusted master data for the digital twin. Eek said PLM should hold authoritative product and lifecycle context while supporting multiple endpoint systems, rather than attempting to consolidate every tool.

That balance supports faster change management, improved manufacturability and serviceability, and clearer business cases for system changes. Eek also expects integrated PLM, ERP and MES workflows to streamline operations, shorten change cycles and reduce rework, supporting service-oriented models built around uptime and total cost of ownership.

These benefits remain development expectations rather than demonstrated production results. Eek cited no plant deployments, production volumes or quantified time savings, so manufacturers will need to validate those claims against operating data.

Watch for evidence that digital records remain current after independent service work and that engineers spend less time searching for validated information. Those milestones will determine whether PLM can move from managing engineering data to governing the connected vehicle lifecycle.