Industrial Software Enables Performance Gains

Emerson's Innovations for Process Control - Winter 2022The 18th edition of Innovations in Process Automation from the Emerson European team is now available. It’s also available in German, Spanish, French and Italian. This edition highlights some prime examples of Emerson’s industrial software capabilities and explains how these capabilities are helping manufacturers and producers to achieve significant performance gains.

The articles in this edition include:

  • Emerson SCADA software simplifies management of photovoltaic power station
  • Emerson to help accelerate green hydrogen production
  • The next generation of plant data management (Author: John Nita)
  • Asset health monitoring and data analysis help maximise plant uptime and efficiency (Author: Alcino Beirão)
  • Optimised control and operator performance reduces energy costs and quality variation (Author: Guido Wink)
  • Instant access to critical tank data wherever you are located (Author: Catrine Haldorson)
  • Emerson solutions are helping life sciences companies get products to market faster (Author: Bob Lenich)
  • Cloud-based SCADA solution unlocks maximum value from operations data (Author: Selwyn Hammond)

I’ll recap some points from John’s plant data management article and invite you to register and download the English version or one of the language editions. John is the president of Europe for Emerson Automation Solutions.

He opens the article by explaining how the Plantweb Optics platform supports improved decision-making by collecting, aggregating and analyzing operations data from across an enterprise and delivering alerts and key performance indicators to the right people at the right time.

Better visibility into key operations data is essential for organisations looking to improve efficiency, increase plant and personnel safety, and support predictive maintenance strategies. Digital communications and smart sensing are now providing access to vast amounts of data on everything from process control to asset health, safety and emissions. However, such an abundance of data can prove overwhelming and it can be a challenge to prioritise the most critical information. In addition, data is often isolated in silos across an enterprise – with different departments looking at specific condition or process indicators to set their own priorities – which makes it difficult to identify issues impacting asset availability and operational performance.

The Plantweb Optics platform:

…is an operational performance platform with enterprise-level data management capabilities, which provides a single location to manage, protect and easily integrate operations data with IT tools and cloud applications. This software is transforming data management, helping companies digitally enable their workforce and allowing them to gain unprecedented insight into operational performance at the enterprise level so they can increase efficiency, reduce risk and drive profitability.

It securely unifies:

…structured and unstructured operations data from across a production site or from multiple sites, enabling users to fully leverage this data in their analytics, trending and reporting. By eliminating operational technology (OT) data silos and efficiently aggregating global operations data from manufacturing, process control and IT systems without disruption, users can establish a sound data foundation for their digital initiatives. Beyond the centralising of data, this software also contextualises the data so that it has meaning and is ready for use. What’s more, it can deliver persona-based key performance indicators (KPIs) to enable faster and better-informed decisions that can lead to operational improvements.

Register and download the English edition or one of the other language editions today for more in this article on the methods of plantwide integration, extensibility to AI, machine learning, and industry-based expertise, and the visualizations to enable the information to be actionable and drive performance improvements.

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