• Friday , 23 June 2017

Intelligent Systems in Process Safety On the taming of the shrew?


While safety in the process industries has received widespread attention for several decades, recent advances in the field of Artificial Intelligence (AI) promise to bear choice tools for plant personnel. Artificial Intelligence has been described as “the part of computer science concerned with designing systems that exhibit characteristics we associate with intelligence in human behaviour”.
From its early beginnings in the Thinking Machines of the 1960s to the Mars Rover Sojourner of the 1990s, the field and its applications have come a long way. These advancements in natural language processing, computer vision, robotics, machine learning and expert systems have lead to practical applications in diverse fields of human endeavour.
In process systems engineering, a wide variety of areas including process design, modelling and simulation, process planning and operations, process control, and product design have gained from these developments in AI. Process design and operations are inherently expertise-based fields. This has lead to the development of expert systems that assist humans tackle different aspects of safety such as hazards analysis, process monitoring, preventive control and emergency training.
Process Hazards Analysis (PHA) is the proactive identification, evaluation, mitigation and prevention of process hazards. A team of experts performs PHA and the analysis is repeated periodically during the entire life of the plant from design until decommissioning. room
Given the enormous amounts of time, effort and resources involved in performing such reviews, there exists considerable incentive to develop intelligent systems for automating the process hazards analysis of chemical process plants. Recently, expert systems that automate Hazard and Operability analysis and other hazard identification and evaluation techniques for both continuous and batch processes have been reported. These systems exploit the fact that the analysis is systematic and logical and a large part of any PHA study involves routine aspects that are common across different plants. Therefore, by suitable knowledge capture and using process knowledge, these systems can automatically identify hazards, their causes and adverse consequences. The appeal of such automated systems is that they can reduce the time, effort and expense involved in a PHA review, make the review more thorough and detailed, minimize human errors, and free the team to concentrate on the more complex aspects of the analysis.”
The other side of the safety coin is ensuring the safety of a process during its operations. The onus for this normally rests on plant operations personnel. Any failing can result in repercussions ranging from poor product quality and schedule delays to equipment damage, human injury or worse. A recent study reported that such mishaps have an economic impact of at least $20-billion annually in the US petrochemical industry and highlighted the need to bolster support to the plant operations personnel especially during abnormal situations. While humans are better at recognising patterns, solving original problems, learning from past experience and improvising and adapting, machines are better at storing and recalling large quantities of information quickly, performing routine repetitive and precise operations over long periods of time. Based on this, recently there is a significant effort from industry and academia to develop and deploy intelligent systems that can act as an intelligent associate to operations personnel. This extra member of the operations team has skills that compliment the human operators’ and is based on AI-based collaborative decision support technologies and is expected to significantly improve safety during process operations.
There are several such examples of process design and operations responsibilities being leveraged through the use of intelligent systems. Many of these developments are now well beyond proof of concept and ready for industrial applications. In the future, such intelligent systems are certain to become plant personnel’s treasured partner in taming the safety shrew.
Rajagopalan Srinivasan
Dept of Chemical & Environmental Engineering
National University of Singapore

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