Clarifying Operational Analytics

by , | Oct 19, 2020 | Digital Transformation

Jim Cahill

Jim Cahill

Chief Blogger, Social Marketing Leader

Analytics help turn reams of data into useful information. In the manufacturing and production industries, operational analytics work on the steams of continuous, batch, event, operator actions and other data sources to help create useful insights.

Plantweb Operational Analytics

In a Forbes article, Navigating The Growing World Of Analytics, Emerson’s Peter Zornio clarifies the types of analytics useful for manufacturers and producers.

Peter opens highlighting the vast amount of data created in these industries.

Manufacturing generates more data than any other sector, and according to McKinsey, analytics has the potential to deliver more than $4 trillion of growth in industrial manufacturing alone.

He notes the confusion created by the wide array of analytics solutions.

While there are many analytics solutions that can help functions like customer management, human resources or finance, the highest-value opportunity for industrial manufacturers is the analytics surrounding the manufacturing production itself.

These analytics, operational analytics have the:

…potential to impact and improve the performance of simple equipment, complex assets and process units and entire plants. When effectively applied, operational analytics can improve key performance areas such as reliability, safety, production optimization and energy management.

Peter describes one class of operational analytics.

Principles-driven analytics are based on known rules, physical laws or principles — and most manufacturing plants and equipment were originally designed using this knowledge.

For example, we:

…know the flow equations, heat transfer rules and other physical laws and principles around heat exchangers, so we can easily model heat exchanger online performance based on these laws.

For common assets in refineries:

…we can predict 80% of failures with FMEA [failure mode and effects analysis ] models and the right sensors, according to our company research.

Another class of operational analytics is advanced data-driven analytics.

Data analytics can be as simple as regression models, but they more frequently rely on machine learning, neural networks and other statistical data modeling techniques to identify solutions to problems where the laws or principles are unknown or are too intertwined.

Read the article for more on these data-driven analytics, and guidance to begin with clear goals, objectives and vision for a digital transformation initiative.

Visit the IIoT Analytics: Plantweb digital ecosystem on for more on scalable analytical tools transforms plant data into actionable information. You can also connect and interact with other operational analytics experts in the IIoT & Digital Transformation group in the Emerson Exchange 365 community.

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The opinions expressed here are the personal opinions of the authors. Content published here is not read or approved by Emerson before it is posted and does not necessarily represent the views and opinions of Emerson.

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