Managing Digital Transformation from Automated to Autonomous Operations

By Dick Hill

ARC Report Abstract


A session at the 2020 ARC Industry Forum in Orlando, Florida focused on the complexity of aligning existing operational technology with new application roll-out plans.  Several speakers acknowledged that, regardless of the challenges, the plans must still be carried out due to the potential business value they can deliver.  However, we also learned that successful digital transformation requires flawless execution.

Due in part to the COVID-19 pandemic, industry has entered a period that urgently requires new modes of operation.  Thanks to advances in digitalization, the ongoing convergence of OT and IT, and the overall digital transformation of industry; the process industries now have an opportunity to move from “automated” to “autonomous” operations where appropriate.  Not only do these advances present the opportunity to improve overall business value, they present an opportunity to further advance safe and flawless operations.

Modern Plant Operations and Human Interaction

For the last half century, industry has been moving toward higher levels of automation.  Nevertheless, with each innovation, it has been important to consider the human factor.  While, today, it may be possible to run certain processes autonomously or with minimal human interaction, transitioning from current operations will require the right technology as well as the right approach.   ARC’s Autonomous Operations Maturity Model summarizes the basic requirements.

It is important to keep in mind that the goal of moving from automation to autonomous operation is to improve the reliability and predictability of the operating plant.  Today, human operators decide what to do when something unpredictable happens.  Tomorrow, the autonomous systems may be making those decisions, with the humans serving as observers and overseers.

One concern often expressed today is the aging workforce and how to pass on the knowledge gained over the years of making decisions.  This is often based on intuition and experience.  While these human characteristics can be hard to replicate in systems, when trained with appropriate historical data and combined with adequate real-time data, artificial intelligence (AI)- based applications, can enhance the human’s understanding of what is normal and abnormal in the plant operations.      

Moving Towards Autonomous Manufacturing Operations

Apostolos Georgiou, Program Leader and Sr. Engineering Advisor at ExxonMobil, talked about trends he is seeing with regard to the movement from automated to autonomous operations.  Mr. Georgiou referenced the four stages of the Industrial Revolution beginning with stage 1 in the late 1700s to the current evolving stage 4.  He characterized stage 3 as “Computer and Automation” beginning in 1970, which led to the beginning of the Digital Transformation that began roughly in the 1980s.  Mr. Georgiou commented that stage 4 is largely about artificial intelligence.   Ultimately, Industry 4.0-based “Cyber Physical Systems” will be enabled by exponential growth of Industrial Internet of Things, cloud computing, Big Data, machine learning/artificial intelligence, and autonomous operations, according to Mr. Georgiou. 

Transformation from Automated to Autonomous

Mr. Georgiou described the transition of the home thermostat to further explain.  New, “smart” home thermostats can take into account information beyond simply the temperature in the room or the time of day.  They can use additional sensors such as cameras or other devices to detect if people are home, away on vacation, or unplanned events.  By applying self-learning and optimization techniques, significant savings in heating/cooling bills can be realized.

“The concept of autonomous operation is not new,” according to Mr. Georgiou.  Back in 1967, the first autonomous trains began to operate.  Their purpose was not to replace the operator, but to have flawless operation and consistency.  As an industrial example, he mentioned a plant air separation unit that, in 2005, was equipped to run without humans being present.  This was possible because the plant events were very well defined and predictable.


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Keywords: Artificial Intelligence (AI), Machine Learning (ML), Autonomous Operation, Human Factor, Internet of Things (IoT), Industry 4.0, Operational Technology (OT), Information Technology (IT), ARC Advisory Group.

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