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Australian Energy Producers Journal Australian Energy Producers Journal Society
Journal of Australian Energy Producers
RESEARCH ARTICLE (Non peer reviewed)

Using machine learning to enhance operator performance

David Walker
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Yokogawa Australia, PO Box 744, Belmont, WA 6984, Australia. Email: david.walker@au.yokogawa.com

The APPEA Journal 60(2) 681-684 https://doi.org/10.1071/AJ19163
Accepted: 4 April 2020   Published: 15 May 2020

Abstract

Machine learning is a powerful tool to analyse very large datasets. Although machine learning has been used for many years in other areas, such a social media, its value to process industry has only recently been realised. Operators interact with control systems in the same way people interact with social media and, as such, many of the algorithms that have been developed for modelling human interaction are applicable to industrial process operations. Recently, control systems companies have been developing analytical tools to leverage the vast amount of data collected in control systems over many years. These tools enable operations to understand the efficiency of their processes and procedures, identify gaps in their standard operating procedures and measure operator capability. This analysis assists in the improvement of procedures, highlights areas where further training is required and identifies opportunities for procedure automation. This has led to considerable improvements in operation performance, resulting in improved production and reduced downtime. This paper describes what machine learning is, how it can be applied to operation performance, the benefits this provides and possible applications in other areas of the industry.

Keywords: automation, control, efficiency, operations, optimisations, procedures.

David Walker is a chemical engineer with over 30 years of experience in control systems across a wide range of technologies and industries, including oil and gas, mining, power, water and waste and chemicals. David has worked in many aspects of the business, including engineering management, systems engineering, project management, training and research and development (R&D), including a secondment to Yokogawa in Japan to work in the development team of their edge devices. David continues to advise R&D on a range of industry issues and solutions. Currently David is Chief Engineer for Yokogawa Australia, and provides technology support, project execution management, engineering improvements and standardisation. In the past, David worked in the UK on Join European Taurus (JET) to implement the automation of the cryogenic separation of the experimental fusion reactor and developed the controls for the Birmingham Water Treatment plant. Most recently, David was lead engineer for the Wheatstone Upstream project and was involved in the implementation of the topsides and subsea controls.