Siemens Opens New Additive Manufacturing Hub to Accelerate Industrial Digitalization

Engage now with Siemens’ new Additive Manufacturing Hub, as it launches a universal platform designed to speed up industrial digitalization. The hub fully integrates software, data standards, and production, bringing member companies and customers into a single source of practical capabilities, with each provider contributing specialized expertise.

Сайт goal centers on turning pilots into scalable deployments, letting teams двигаться quickly from concept to manufacture-ready parts. The hub brings together AM machines and automation, plus a machine-agnostic software layer, with robots handling material transfer and post-processing while a shared source tracks part provenance, process parameters, and quality outcomes, which делает it easier for teams to connect across functions. Later, the platform opens access to additional modules such as supplier catalogs and service partnerships.

For member manufacturers, the hub offers clear steps to realize value: define a concrete goal, map your needs to the platform’s modules, and establish partnerships with Siemens as a trusted provider. Start with a need for a baseline data source and gradually expand to end-to-end digital twins. This approach reduces risk, shortens time-to-production more than before, and creates an organic path to full-scale deployment.

As industries adopt the hub, enterprises gain faster integration with supply chains, a universal data model, and a move toward fully digitalized sourcing. The платформа provides a consistent API surface and data schema, enabling external partnerships to extend capabilities later without disrupting current workflows. For teams seeking speed, the modular design helps accelerate collaboration across functions and suppliers.

To realize the most value, map your project timeline to three milestones: implement a baseline data source, test a printed part in the hub’s workflows, and scale to high-volume production in the next quarter. Engage early with Siemens’ account teams to align your machine capabilities with the hub’s offerings and to secure targeted training for your staff. The result is a move toward fully digital operations that is organic and scalable across facilities.

Scope and practical impact of Siemens AM hub

Launch the Siemens AM hub as the central platform to accelerate adoption across design, production, and metrology. Incorporated into existing workflows, the hub links design-for-AM, process control, data analytics, and services through a partner network to deliver faster, better outcomes. The april milestones will demonstrate value to many business units and set a clear pace for broader rollout.

Scope includes a full suite of services: digital twins for part qualification, build-process monitoring, metrology-driven quality assurance, and supplier coordination. The provider coordinates with internal teams and member companies to reduce hand-offs and improve life efficiency and life-cycle control. The hub addresses challenges such as data silos, process variability, and certification readiness. Analysis and ongoing testing show early improvements in rework rates and print cycle times. Leaders from manufacturing, procurement, and R&D will collaborate in a governance forum to pose questions about data ownership, assumptions, and risk, ensuring alignment with risk control.

Practical impact includes faster design-to-print cycles, higher first-pass yield, and better material usage control. Metrology-backed feedback closes the loop between design and production, reducing scrap and rework while expanding capacity. Shared standards and a unified data model let many member sites operate with a common provider network, unleash value at pace. This setup supports clear ROI signals and addresses cost, lead time, and quality gaps through ongoing analysis and targeted services.

Target industries and high-value use cases for the hub

Start with a site visit to map high-value use cases across anchor industries: aerospace, automotive, industrial machinery, healthcare devices, and energy utilities. This focused initiative translates into a staged portfolio engineers can test and scale, addressing entire stages from design to finished parts.

In aerospace, prioritize printed structural components and tooling that reduce weight while maintaining strength. Target brackets, housings, and cooling-channel routes validated by existing standards; pair them with optimized post-processing and dimensional control to meet certification criteria.

In automotive and mobility, develop printed fixtures and end-use parts for prototyping and limited production. Focus on jigs, clamps, sensor housings, and brackets that shorten cycle times and improve earnings potential. An intelligent workflow analyzes performance and enables engineers to optimize geometry for stiffness, vibration resistance, and safety.

In healthcare, address precision devices, surgical guides, and patient-specific trays where fit and biocompatibility matter. Use materials available for medical use and robust documentation trails to support customer needs and certification tests. The hub will coordinate co-design with clinicians to ensure the required dimensions and tolerances.

In energy and utilities, produce spare parts and specialized tools for remote operations. Printed parts enable on-site availability, serialized to support traceability, and stored in a centralized catalog to reduce downtime. This approach improves эффективность and lowers maintenance costs, driving earnings uplift over time.

Across all sectors, implement an optimization loop: design, print, inspect, certify, and ship. A clear certification pathway, with industry-specified tests, ensures reliability. Leaders from engineering, procurement, and operations collaborate to address customer requirements, with results shared in a regular newsletter и more opportunities available to partners. By tracking analysis и dimensions, the hub turns this initiative into a scalable capability that engineers can visit again, while organic material options and intelligent data analytics expand the range of use cases and available parts.

Capabilities showcased: additive tooling, automation, and digital twin integration

Begin with a fully integrated cell that links additive tooling, automated handling, and a digital twin to drive serialized tooling, faster assembly, and better analysis across the enterprise.

From a maritime perspective, the hub demonstrates how on-demand tooling accelerates component fabrication for hull blocks, propeller fixtures, and marine equipment while maintaining traceability and quality across days of production.

• Additive tooling: precision fixtures, jigs, and inserts produced with optimized geometries; serialized tooling data travels with each part, enabling end-to-end traceability; supports assembly on tight tolerances; reduces fixture lead times and enables on-site configuration in shipyards and offshore platforms.
• Automation integration: collaborative automation (cobots, vision-guided grippers, and automated handling) streamlines material flow and reduces manual intervention; together with AI-based scheduling, boosts throughput and reduces cycle time by 20–40% in typical lines; supports multi-site manufacturing, reinforcing internationality of supplier networks and customers.
• Digital twin integration: live data from printers, sensors, and inspection systems feeds a digital twin that simulates print sequences and assembly steps; analysis informs parameter optimization, print orientation, and material selection; enables predictive maintenance, reduces unplanned downtime by up to 30%, and shortens testing cycles.
• Quality and testing: integrated testing protocols validate serialized parts at every stage; automated inspection captures dimensional data and feeds the digital twin for continuous improvement; executives can see real-time quality dashboards and traceability records across days of production.
• Partner ecosystem and financing: a collaborative network with industrys leaders and partner suppliers offers financing options for mid-market and enterprise customers; aligns with well-planned executive roadmaps to optimize capital expenditure and time-to-value; expands tools repertoire and accelerates what customers can make, from standard parts to complex assemblies.

This opens new opportunities for enterprise-scale manufacturers to optimize performance, reduce waste, and deliver serialized parts to customers faster, and more, while maintaining internationality and collaborative culture.

Strategies for extending die casting tool life: process control and material selection

Adopt closed-loop process control with real-time sensing of temperature, pressure, and shot velocity, paired with a tightly defined material pedigree for low variability. This approach will reduce thermal hotspots, minimize wear, and extend tool life without sacrificing cycle time on typical high-precision parts. Use topology-informed cooling channels to move heat efficiently along critical surfaces and maintain an environment where repeatable results are possible across shifts and machines. Begin testing in a controlled pilot to verify wear reduction and establish a robust process window.

In-process control details drive reliability. Install inline sensors on the die and platen to capture temperature, surface wear, and lubrication flow, then feed data into SPC workflows for immediate alerts. Streamlines of data transfer to Teamcenter enable traceability from tool setup to production outcomes, supporting certifications and future adoption at scale. Regular testing validates that parameter drift stays within defined limits, and the team can move from pilot to production with confidence as tooling wear signals stabilize.

Material selection affects tool life as much as process control. Favor alloys with stable chemistries and low susceptibility to sticking or transfer to tool surfaces, supplemented by newly developed coatings and lubricants designed for high-precision cycles. Use lubricants and release agents compatible with the chosen alloy to minimize build-up and surface damage. For medical and other demanding applications, restrict material batches to those with certified chemistry and documented reliability, then verify performance during transfer to new production lines. Plan material adoption with a clear set of questions for suppliers and QA to avoid surprises in head geometry or gate design that could impair reliability.

Implementation path aligns teams and standards. Initiate a point-focused pilot on a limited line, capture tool life metrics, and compare against baseline traditional approaches. Link tool-life data to Teamcenter records to support repeatability, traceability, and international certification audits. Prepare the environment for broader adoption by aligning with training, procurement, and maintenance teams, and set governance to manage newly integrated data and tool-replacement cycles.

Data and analytics: capturing performance signals and predictive maintenance

Implement a centralized data fabric that ingests real-time signals from printers, sensors, and post-processing stages, and ties them to serialized parts in the assembly line. This move enables predictive maintenance and optimizes the additive initiative across sites.

To accelerate value, deploy a fully connected data network that links machines, tools, and QA outcomes with the customer and supply chain systems. Also bring a worldwide perspective by standardizing data models and dashboards that provide a single solution across locations where printed parts are produced and assembled.

1. Data model and tagging: design a data model that is designed to capture printer telemetry (temperature, nozzle health, vibration), in-situ metrology, and QA outcomes for each serialized part. Place serialized identifiers on every part so data moves with the part through assembly and post-processing, enabling end-to-end traceability over the entire lifecycle.
2. Data pipeline and network: establish edge-to-cloud pipelines and a robust network that collects signals from printed parts across the worldwide hub network. In place, deploy streaming (and batch) processes that feed a central data lake, with clear data lineage and access controls to protect intellectual property.
3. Analytics and predictors: apply advanced analytics to detect anomalies and forecast maintenance windows. Use time-series models to estimate nozzle wear, filament consumption, and build stage energy usage, enabling maintenance over planned downtime rather than reactive breaks. Integrate QA feedback from Instron testing rigs to refine failure likelihood and yield predictions for each build.
4. Governance and security: enforce data quality checks, lineage, and role-based access across all additive systems. Also document data provenance for each part and each build, ensuring trust across distributed teams and suppliers involved in the initiative.
5. Operational decision-making: build dashboards that show system health, yield, and predicted failure points for operators and managers. This customer-focused solution helps bring value everywhere, enabling teams to respond quickly while maintaining high safety and process controls.

Implementation metrics and targets: aim for a 15–25% reduction in unplanned downtime within the first 12 months, a 5–12% increase in first-pass yield, and a 10–20% cut in scrap across multiple sites. Track serialized part visibility across the network and report weekly on maintenance windows, mean time to repair, and parts availability to sustain a reliable additive manufacturing workflow.

With these steps, the initiative gains cutting-edge advances, establishing a global standard for data-driven maintenance. We believe this solution will move the industry forward, with that designed to be fully scalable and ready for future integrations across all systems, everywhere, while maintaining consistent performance for every printed part and assembly.

Actionable implementation roadmap with milestones and ROI indicators

Launch a 90-day pilot on only two medical components designed for printed production to quantify value, reduce cost per part by 22–28%, and prove a scalable workflow that can be delivered everywhere across centers.

Days 0–30: form three cross-functional groups–engineering, manufacturing, and quality–to lock the base design, complete the BOM, and finalize the print process. Define the certification path, including material approvals and process validation. Select a machine mix capable of delivering over 1,000 printed units per week with tight tolerances. Establish a control plan to track days to deliver, lead times, scrap rate, and inspection pass rate, and align it with the center’s governance.

Days 31–60: create and test prototypes, capture performance data, and fine-tune print parameters for greater precision. Confirm financing arrangements for initial capex–aim for a balanced mix between leasing and internal funds. Run interim qualification tests to satisfy certification criteria and document results for the center’s audit.

Days 61–120: move to limited production of qualifying parts, monitor throughput, machine uptime, and scrap trends; adjust processes to realize at least a 15% reduction in cost per part and a 30% faster delivery cycle. Document earnings impact from reduced labor and faster time-to-market to create a stronger perspective on value. Prepare for broader expansion by validating repeatability across batches.

Days 121–180: expands to additional sites and ensures the same certification framework across the network; moves from pilot to full-scale production with printed parts deployed everywhere; creates a standardized quarterly newsletter to share outcomes and best practices while securing long-term financing to accelerate growth.

ROI indicators to monitor monthly include payback period in days, cumulative earnings uplift, and ROI percentage; track cost per part, lead-time reductions, and part performance over the first 6–12 months. A greater earnings multiple and a clearer perspective on risk enable financing to move faster; if payback stays under 180 days and the net earnings lift surpasses 12%, scale to additional components and sites. Use the newsletter to report quarterly results and align with groups and center management.