Discussion with Siemens on LCA, Sustainability, and AI

In this episode of the PLM Green Global Alliance interview series, Jos Voskuil and Klaus Brettschneider speak with Eduardo Salva, Global Portfolio Developer for Teamcenter at Siemens Digital Industries Software. The discussion explores Siemens’ approach to sustainability, Life Cycle Assessment (LCA), Digital Product Passports (DPPs), and the role of AI in Product Lifecycle Management (PLM).

Sustainability as a Business Transformation

Eduardo explains that Siemens began addressing carbon footprint calculations around 2017, anticipating growing reporting requirements. What started as an extension of cost engineering evolved into a dual focus on cost and carbon performance during product development. Internally, Siemens drives sustainability through its DEGREE framework, which includes environmental, social, and governance metrics covering emissions, circularity, inclusion, ethics, and employee development. Sustainability KPIs are embedded across the business and software portfolio.

Carbon Footprint Management is Becoming Standard Practice

A key topic is Siemens’ Product Cost Management (PCM) solution, which enables simultaneous calculation of product cost and carbon footprint. According to Eduardo, more than half of PCM customers use this functionality, particularly in the automotive sector, where OEMs increasingly require suppliers to provide carbon data alongside quotations. Carbon footprint reporting is rapidly becoming standard business practice rather than merely a compliance activity.

From Carbon Footprints to Full LCA

As customers began demanding cradle-to-grave assessments, circularity insights, and Digital Product Passport capabilities, Siemens expanded its sustainability portfolio through a partnership with Makersite. The integrated solution enables engineers to conduct AI-supported environmental assessments directly in Teamcenter, covering carbon emissions, water consumption, waste generation, and other impact categories.

A major advantage is the ability to generate sustainability insights from incomplete Bills of Materials (BOMs), allowing organizations to shift sustainability analysis earlier into the design process. This enables engineers to compare alternatives and improve products before key design decisions are locked in.

AI as an Enabler, not a Replacement

Eduardo stresses that the solution relies primarily on machine learning rather than large language models, using historical ERP, supplier, and PLM data to generate reliable results. Human expertise remains essential for validating outcomes and interpreting trade-offs.

The objective is not to replace sustainability specialists but to make environmental performance information accessible to engineers and designers, allowing sustainability considerations to become part of everyday product development decisions.

Digital Thread as the Foundation

The discussion highlights the importance of the digital thread. Teamcenter connects design, simulation, manufacturing, and ERP systems, as well as sustainability data, within a single environment, making sustainability analysis part of existing engineering workflows.

Both speakers emphasize that AI, sustainability, and Digital Product Passports depend on structured, connected product data. Organizations that continue to rely on document-centric processes will find it increasingly difficult to benefit from emerging digital capabilities.

Digital Product Passports: Regulation as the Main Driver

Interest in Digital Product Passports is strongest in the battery industry, where regulations are creating immediate requirements. Siemens has developed a dedicated battery passport solution that combines LCA, carbon footprint reporting, supply chain traceability, risk assessment, and due diligence capabilities.

While many companies are waiting for regulations to fully mature, Eduardo argues that organizations should begin preparing now, as DPP implementation requires significant work around data quality, governance, and supply chain integration.

Digital Twins and Agentic AI

Looking ahead, Siemens sees digital twins and AI as complementary technologies. Digital twins remain critical for reducing prototypes, optimizing manufacturing operations, and accelerating innovation, while AI will increasingly automate workflows and support decision-making.

Eduardo envisions future AI agents capable of evaluating BOMs, balancing cost, sustainability, and risk metrics, and proposing optimized alternatives. However, he emphasizes that organizations must first establish a strong data foundation to fully benefit from agentic AI capabilities.

Key Takeaways

• Sustainability is becoming directly embedded in engineering and product development processes.
• Carbon footprint reporting is evolving into a standard business requirement, particularly in the automotive industry.
• Siemens is leveraging AI and its partnership with Makersite to bring LCA capabilities closer to engineers.
• Digital threads and structured product data are essential foundations for sustainability and AI initiatives.
• Digital Product Passports are gaining momentum, especially in battery-related industries.
• Digital twins, AI, and PLM are converging to enable more informed decisions that balance cost, sustainability, and risk.
• Companies that invest early in data quality and digital infrastructure will be best positioned for the next generation of AI-enabled PLM solutions.

The discussion reinforces a core message of the PLM Green Global Alliance: sustainability becomes scalable when environmental intelligence is embedded directly into the digital thread and available to the engineers making product decisions.

Conclusion

The discussion highlights how sustainability is becoming increasingly embedded within mainstream PLM and engineering processes. By integrating carbon footprint management, LCA, Digital Product Passports, and AI-driven analysis directly into Teamcenter and the digital thread, Siemens demonstrates how sustainability can evolve from a reporting exercise into an operational engineering capability.