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Siemens Expands Convergent Modeling in Parasolid to Increase Productivity with Mixed Geometric Data Formats

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The Aftermarket Opportunity

From training to pay-for-performance to features on-demand, the emerging machine builder business model focuses on services that reduce a manufacturer’s financial risk by shifting the responsibility of asset acquisition and management on to the OEM.

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The Pandemic is Shaping the Future Supply Chain

Some of the greatest innovations happen during times of disruption.

Siemens Introduces First Soft Starters with Integrated Safe Torque Off Functionality

The Sirius 3RW55 Failsafe soft starters from Siemens has an integrated fail-safe digital input that directly connects to an emergency stop pushbutton.

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Weighing Module

The Siwarex WP351 module is Siemens’ newest solution for intelligent weighing automation for a wide range of applications in pharmaceutical, food and beverage, chemical, and steel industries.

Response to the question: In your opinion, whose job is it to protect an organization's industrial networks? Source: Claroty

Cybersecurity Survey Reveals IT/OT Bridges and Disconnects

In a global survey of cybersecurity professionals, Claroty unearths insights into how operations and enterprise networks are increasingly being co-managed. Plus, Claroty and Siemens combine hardware and software for industrial cybersecurity applications.

Siemens introduces Sinamics G120X drives, suited for use in pump, fan, and compressor applications in industries such as water/wastewater, building technology, and in industrial environments.

Sinamics G120X Drive Series

With power range from 1–700 hp (0.75–630 kW), Sinamics G120X is optimized for pump, fan, and compressor applications.

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Web Server Module

Siemens launches the Sinamics V20 Smart Access web server module designed to mount directly onto the drive, transforming a mobile device or laptop into a virtual operator panel for drive control.

Additive Manufacturing Process Simulation

Additive Manufacturing (AM) Path Optimizer from Siemens combines physics-based simulation with machine learning to analyze a full job file before execution on the machine.