AI-Driven Autonomous Operation

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Do you have visibility of critical information when you are about to make a hard decision at your organization?

Are you currently using any technology to ensure visibility and alignment of decisions across your organization?

Have you ever wanted to use artificial intelligence or machine learning, but you do not know how to start?

What are the success factors of an AI project?

You may not have clear answers to these questions.

With time, technology has evolved. In the era of self-driving cars, typing correction on smartphones, robotic system handling questions from customers, direction and speed decision-making capabilities of drones, the world is moving towards autonomous operation from automation. Yokogawa believes that “the transition from IA2IA  (Industrial Automation to Industrial Autonomy) is already underway”.

Advanced analytics of process data cannot be done without domain knowledge; Yokogawa can provide the best practices of the industry with over a century of domain knowledge, and consequently Yokogawa has become able to provide something beyond Data Analytics: AI-Driven Autonomous Optimization. It offers not only highly efficient, realistic, and actionable, but it is also more insightful in providing quality stabilization solutions that can help companies stabilize and continuously improve the quality of their products. Any powerful AI algorithm alone is not enough to realize the true potential of customer data. Advanced analytics methods with domain and business knowledge are key for unleashing the latent potential in plant data. 

Yokogawa holds workshops and webinars to provide solutions to customers’ questions.

Improving Business Performance by Aligning Decision-Making Layers

At the base level of the Process Industry, as we go down the organizational structure, decisions are more interconnected, and their impact on top layers’ KPIs becomes less and less clear.

Yokogawa utilizes state-of-the-art and latest AI algorithms, which provide support to decision makers at each level.

Figure-1

Figure-1

Advisory Dashboards Powered with AI/ML and Simulation Technologies

Importance of a Dashboard for Decision Makers:

1.       Visualize the performance using real-time KPIs

2.       Understand the trade-offs among all decision-making layers

3.       Quickly align all layers with the management objectives

4.       Improve efficiency of each business layer to maximize overall business performance

Figure-2

Figure-2

The most powerful simulators and AI and machine learning platforms enable business intelligence with intuitive visuals.

The advisory dashboards envision key performance metrics into the following areas:

1.       Business Operations Performance / Insights

2.       Product Quality

3.       Process Anomaly

4.       Equipment Failure

If you desire more information about AI-Driven Autonomous Optimization or workshops for it with Yokogawa, please contact us.