Smart Manufacturing

November 11, 2025

Industry Signals - November 11, 2025: Autonomous Robots, Flexible Warehousing, and Industry Standards

# AI

# Automation

# Automation & Digitalization

# CFDModeling

# Digital Manufacturing

# Digital Transformation

# Digital Twin

# Digital Twin & Simulation

# Industrial AI

# Innovation

# Predictive Maintenance

# Robotics

# Smart Manufacturing

What recent moves in robotics and intralogistics reveal about the future of industrial automation.

Industry Signals

Driven by labor shortages, increasing complexity in product customization, and the rising pressure to improve operational agility, the automation landscape is shifting, and it is shifting quickly.

This shift is both technological and structural. Manufacturers and logistics providers are rethinking how automation fits into the broader architecture of their operations. Rather than bolting on point solutions, leading firms are aligning around cohesive strategies that integrate digital twins, AI, robotics, and standardization frameworks into a unified automation vision. These efforts aim to future-proof operations by enabling more adaptive, interoperable, and intelligent systems.

In this edition of Industry Signals, we examine key movements that are reshaping how robots and autonomous systems are designed, deployed, and managed, using recent publications in the industry as our guidelines:

Siemens’ long-range forecast anticipates a future of fully autonomous industrial robots trained in virtual environments,

Automated Warehouse’s survey breakdown discusses the practical challenges of deploying flexible automation, and

VDMA’s newly published architecture model for AMRs provides a shared framework that could unlock interoperability and lower the integration barriers many firms face.

Collectively, these publications suggest that automation is just as much about systems thinking, lifecycle integration, and platform orchestration as it is about hardware.

Siemen’s 10-Year Forecast: Fully Autonomous Industrial Robots

Industrial manufacturers are moving toward a future where production lines operate with minimal human programming. They are leveraging digital twins, AI-driven decision making and the industrial metaverse with a vision of creating robots to build products autonomously. As shared in a recent Digital Transformation podcast episode (episode 6) Siemens predicts that, in the next 10-15 years:

Digital twin + AI will be the foundation: Using a real‑time virtual representation of the factory (the digital twin), manufacturers can simulate new processes and deploy AI for enhanced sensing and decision‑making.

No‑programming robotics will be in play: It is predicted that robots will derive assembly instructions from 3D designs, operate within closed‑loop ecosystems and require no explicit programming.

Industrial metaverse will be an enabler: The industrial metaverse (photorealistic virtual environments enriched with synthetic sensor data) will accelerate robot training and deployment, reduce reliance on physical prototypes and enable agile manufacturing.

The Path to Creating Adaptable Robots

Siemens also recently released a Digital Transformation podcast episode on the topic of creating adaptable robots (episode 3), which explored how manufacturing automation must evolve beyond rigid, pre‑programmed robotic systems to truly adaptable robots capable of operating safely and effectively alongside humans in dynamic environments. In it, they discussed:

Structured vs. unstructured environments: The distinguishing traits of traditional “structured” factory spaces, where robots operate in predictable, fixed conditions from “unstructured” ones, where human operators, changing production layouts and unpredictable tasks require robotic systems to respond dynamically.

Dynamic path‑planning and safety: Advanced path‑planning libraries and collision‑detection software that enable robots to avoid humans and other obstacles in real time and integrate across multiple robot brands.

Digital twin as enabler: The role of digital‑twin technologies in simulating robot movement, cable behaviour, and workspace interactions, which help engineers validate robotic performance and ensure full safety before deployment in the real factory.

Navigating the New Automated Warehouse

Source: WTWH Media and Automated Warehouse | Published: April 21, 2025

Automated Warehouse recently surveyed their readers - a mix of manufacturing engineers, design engineers, system integrators, operations and general management - on what automation technologies they are using and their areas of focus for the future. They discovered that, driven by labor shortages, changing fulfillment demands and rising cost pressures, warehouses are evolving from traditional, fixed-line configurations to flexible, modular automation ecosystems. From the survey results, they concluded that:

There is a shift from rigid to flexible infrastructure: Many existing warehouses built around fixed automation are now inadequate for today’s volatile demand. Instead, modular systems and autonomous mobile robots (AMRs) are gaining adoption because they can scale and adapt more easily.

The new automation landscape brings decision-making complexity: With an increasing array of automation options and vendors, organisations face “analysis paralysis”. There is a need for frameworks that compare technologies in real‑world operational contexts rather than waiting for a perfect solution.

Organisations must choose between existing facility upgrades and new builds: Many firms now prefer retrofitting (“brownfield”) warehouses over building from scratch (“greenfield”), but this introduces integration challenges. Modular, plug‑and‑play solutions are becoming more important to handle existing constraints.

Reference Architecture Model for Autonomous Mobile Robots in Intralogistics

Source: VDMA | Published: November 2025

VDMA’s “OPC UA for Robotics – Part 1 : Vertical Integration” is a vendor-neutral, industry-defined reference architecture specification for autonomous mobile robot (AMR) systems in intralogistics – a comprehensive model. It provides a standardized framework to support system interoperability, reduce integration complexity, and ensure safety, reliability, and scalability in warehouse and factory deployments. The document is 126 pages long, but here are some key points to get you started:

Structured Reference Architecture: The document introduces a multi‑layered reference model (RAM‑AMR) that organizes AMR system architecture into functional, software, hardware, communication, and integration layers. This layered model improves clarity in system design and facilitates cross‑vendor compatibility.

Standardized Interfaces and Functional Domains: The specification emphasizes the importance of clearly defined interfaces between AMRs and their environment, such as fleet management systems, safety infrastructure, human operators, and ERP/MES systems. These interfaces are critical to ensuring safe, efficient, and modular deployment of mobile robots in dynamic industrial settings .

Lifecycle Integration and Stakeholder Collaboration: VDMA 40010‑1 frames the architecture as a lifecycle tool supporting all stakeholders, from planners and integrators to software vendors and operators. It promotes collaboration across development, commissioning, operation, and maintenance phases .

Alignment with RAMI 4.0 and Industry Standards: The reference architecture aligns with broader frameworks such as RAMI 4.0 (Reference Architectural Model for Industry 4.0), ensuring compatibility with Industry 4.0 principles and international standardization efforts. It bridges digital twin thinking with real‑world AMR deployment challenges.

Looking Ahead

What was once a linear process, automating to reduce labor, has become a multidimensional effort to create systems that are not only efficient, but adaptable, interoperable, and intelligent. Across sectors, the emphasis is moving away from isolated deployments and toward platforms that can evolve alongside the needs of the business and its environment.

As the language of automation expands to include digital twins, modular frameworks, and software-defined infrastructure, so too does its strategic relevance. These developments signal technical progress and a growing maturity in how the industry understands and implements automation as an integrated part of industrial innovation.

That’s a wrap for this edition of Industry Signals. Have a report, use case, or event you'd like to see featured in an upcoming issue? Send a note via PM. We’re always looking to spotlight what’s shaping the future of industry and find recommendations from the Xcelerator Community especially valuable. Your insights and experiences continually shape Industry Signals.

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