Virtualization, Cloud Analytics

Use cloud-based predictive analytics to optimize enterprise

Examples, recommendations and webcast help unlocking the power of existing data, key to enterprise-wide optimization by using cloud-based predictive analytics.

By Naren Gopalkrishna December 15, 2021
Courtesy: GE Digital, Control Engineering

As manufacturers say they need visibility beyond four walls, enterprise dashboards, modern data architecture, artificial intelligence (AI) and machine learning (ML) help analyze, compare and optimize performance of assets, lines and plants. Other needs include reduced information technology cost, more cybersecurity and data governance, better performance on multiple backend data services connecting applications and reporting to operations along with standards-based interoperability.

Providing enterprise-wide visibility requires millions of pieces of information with data aggregation from operational-technology (OT) and information-technology (IT) systems.

4 ways to enable enterprise-wide visibility, analytics

To enable enterprise-wide visibility, GE Digital recommends following a four-step analytics process.

  1. Plan: Digital team works with operators, line supervisors and plant managers to understand challenges.
  2. Do: Analysts and process engineers create analytics for visualization that is digitally accessible by all stakeholders.
  3. Check: Operators and line supervisors are notified of anomalies on personal mobile devices that they verify and act upon.
  4. Analytics: Tweak analytics based on feedback.

These steps enable the plant manager, operators, line supervisor, process engineer and analyst to optimize and continuously improve the enterprise through analytics.

Manufacturing competitiveness relies on modern data architecture, artificial intelligence (AI) and machine learning (ML) to help companies curate and visualize data across the manufacturing value chan and rapidly and continuously drive and improve operational efficiencies, according to Naren Gopalkrishnais senior principal technical product manager, GE Digital. Gopalkrishnais explains more in a Dec. 16, 2021, webcast expected to be archived for a year at www.controleng.com. Courtesy: GE Digital, Control Engineering

Manufacturing competitiveness relies on modern data architecture, artificial intelligence (AI) and machine learning (ML) to help companies curate and visualize data across the manufacturing value chan and rapidly and continuously drive and improve operational efficiencies, according to Naren Gopalkrishnais senior principal technical product manager, GE Digital. Gopalkrishnais explains more in a Dec. 16, 2021, webcast expected to be archived for a year at www.controleng.com. Courtesy: GE Digital, Control Engineering

Examples, quick-start analytics, how to begin

Examples from a chemical company and pet food manufacturer explain challenges, actions taken and results in the webcast.

More details also are provided on how manufacturers can create a quick-start analytics journey. Seven recommendations include finding trusted software partners, start where you are to aim for rapid, incremental value, plan the journey, define the scope, make it scalable, evaluate off-the-shelf capabilities and extensibility and avoid science experiments and pilot purgatory.

The webcast and question-and-answer session, archived for a year, provide more information about the webcast topic to unlock the power of existing data and optimize at enterprise scale with cloud-based predictive analytics: “Advanced Analytics from Plant Floor to Cloud – It’s Not a One Size Fits All.”

Naren Gopalkrishnais senior principal technical product manager, GE Digital. Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media, mhoske@cfemedia.com.

KEYWORDS: Cloud-based, predictive analytics, manufacturing visibility

Understand how manufacturers can unlock the power of existing data, key to enterprise-wide optimization by using cloud-based predictive analytics.

Examine four ways to enable enterprise-wide visibility, analytics

Review examples, quick-start analytics, how to begin cloud-based predictive analytics.

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Naren Gopalkrishna
Author Bio: Naren Gopalkrishnais senior principal technical product manager, GE Digital.