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Achieve autonomous operations, using data and AI

Create your roadmap to end-to-end autonomous — and sustainable — operations. Combine data, cloud, AI and transformative technologies to make the factory of the future a reality.

Why autonomous operations?

Manufacturers face increasing demands for complex, personalized, sustainably produced products amid cost pressures, market volatility, and labor shortages. To stay competitive and address these challenges, they must reinvent operations by leveraging data, AI, and pursuing end-to-end autonomous operations.

How AI is changing digital production and operations

From complex engineering data to human-centric insight

Gen AI can power digital twins that facilitate simulations, predictive maintenance and performance analysis. AI agents also analyze data, identify patterns and provide insights for informed decision-making.  They can predict equipment failures, allowing proactive maintenance and minimizing downtime.  Plus multi-agent systems enhance operational efficiency by managing various aspects of manufacturing operations.

What you can do

Consider what autonomous means for your manufacturing operations and how it can integrate into your operational goals. Develop a strategy that outlines actionable steps and practical examples, each with a clear return on investment, to achieve these objectives.


of manufacturing managers understand they need to reinvent operations to reach the full potential of data and AI in support of end-to-end process performance and sustainability

Achieving autonomous operations is similar to lean manufacturing: both require high-touch governance. The difference is the use of data and AI to uncover and apply new performance levers, accelerating process innovation at scale.


of manufacturers will deploy enterprise-wide AI-based tools to support decision-making processes and maximize the value of data by 2025

To shift from experience-driven to data-driven operations, you need an integrated operating model that cuts through functional silos. Use a digital twin to streamline processes and improve performance and sustainability with real-time data insights.


of industrial organizations will use real-time data capture and integration investments for sustainability initiatives to boost operational performance and visibility

Your architecture must evolve to fully utilize an operational digital twin. This approach doesn't require a complete overhaul; instead, the twin integrates with your existing IT/OT assets to enhance performance through digital applications.


of available PLM applications is expected to be built on top of composable technologies, enabling functional integration to other adjacent solutions to enable a digital thread

Awards & recognition

IDC MarketScape: Worldwide Smart Manufacturing Production Management

Arranging, controlling, and optimizing work and workloads in the production process to ensure effective utilization of machinery resources, materials, manpower, and technology

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IDC MarketScape: Worldwide Smart Manufacturing Asset Management

Managing the maintenance of physical assets of an organization throughout each asset's life cycle in the context of the production needs

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IDC MarketScape: Worldwide Smart Manufacturing Quality Management

Enabling manufacturers to electronically monitor, manage, and document their quality processes to help ensure products are manufactured within tolerance, comply with all applicable standards, and do not contain defects

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