The Long Road to Autonomous Operations
The Long Road to Autonomous Operations
Moving refineries and petrochemical facilities to autonomous operations will require a broad focus and cross-domain approach to build intelligent, resilient and remote operations. It would impact all areas of the operations, but, fortunately, bring benefits just as widely.
The drive to autonomous operations in refining and petrochemicals is not difficult to understand. In many respects, the motivations are similar to those that have already seen widespread adoption of automation in the industries: to boost safety, eliminate errors, and boost compliance and efficiency in the operation.
The process is also recognizable from the drive to digital technologies and automated processes that we have already seen. Manual readings and process workflows are replaced by sensors and automated responses by control and safety systems (SIS) and controllers.
But autonomous operations go well beyond this automation. In the current state of automation (ignoring even those areas relying on manual or semi-manual processes), the operator’s role is enhanced rather than diminished. The automation paradox is that, as basic monitoring and control functions are automated, those that remain for operators are more critical and complex. Automation still leans heavily on the experience, contextual information and awareness of the process environment of operators and those supporting them.
Truly autonomous operations require more than automated responses across various processes in the plant or refinery. They need the system to bring an awareness of the process environment to make intelligent decisions in response to changes in the process or plant; robust remote operations technology to facilitate people to be removed from the site of operations; and resilience to help ensure the long-term site safety and robust responses to abnormal situations.
Therefore, autonomous operations are not a single technology solution or project but the culmination of a maturing technology set. This solution set sees operations move from manual operations through basic automation, optimization and remote operations to resilient and autonomous operations.
All the time, as refineries and petrochemical complexes move up these levels, a wide range of priorities and imperatives must be kept in mind: the safety of people and the environment, quality specifications, logistical demands and regulatory requirements. Each has its own set of decisions and challenges.
Tackling the challenges: Control, optimization and autonomy
A crucial step in the journey to autonomy is the recognition of the importance of cross-domain linkages. In traditional manual operations, these linkages are identified by field workers: A noisy bearing on a crucial piece of rotating equipment that is recognized as a sign that it requires maintenance; a smell that suggests a leak or overheating.
In automated operations, these senses of sight, smell and hearing are replicated by cameras, gas detection and acoustic sensors. Links across the control system such as video view of an overflow weir of a clarifier, or the view of the clarifier itself, or even the sump level of a centrifuge, or once again a filter backwash output stream; as an interface level or water boot levels are all examples that provide additional inputs to drive operational decisions. The goal of those seeking to move up the operational technology levels is to recognize these links and render intelligent, resilient, and autonomous responses.
Moreover, achieving the efficiencies and operational performance desired requires that some linkages and responses will be cross-functional. Switching crude oil feeds to a crude distillation unit remains an ongoing challenge at many sites, for instance. Operators struggle to reduce disturbances to product qualities and minimize operator actions.
A more autonomous approach would identify key inputs such as accurate or predicted crude tank contents, including any mixing or layering effects, and link this information to unit controls. More broadly, a direct link from plant scheduling to the autonomous start and stop of a crude switch to meet scheduling goals, with little or no operator intervention, would improve many operations.
Advanced process control (APC) must be central to this discussion. In traditional automation, simple process control loops continuously correct deviations in single process values, while alarms help operators understand the nature and cause of incidents and mitigate unwanted effects.
As the sophistication of automation and control systems has grown and headcounts on site have shrunk, the scope of an operator’s purview has expanded in a significant way.
Combining multiple event occurrences by the control system into concluded conditions can help operators achieve more intelligent operations. Automated or semi-automated operational procedures also help guide operators along with context-sensitive documentation. APC, though, helps enable operations to move beyond safe and controlled operations to optimized operations.
The APC technology manages multiple interactions and can control complex processes to reduce energy consumption, maximize product yields and meet quality requirements – without human interventions. APC models can now update themselves, even in closed loops, with no interruption helping achieve the resilience of advanced controls.
The long and the short of it
Crucially, autonomous operations seek to take a broader definition of optimization: Not just within units but across them; not just process-driven but economically optimized; and not just short term but over the entire run length between shutdowns. And it can be applied across the business.
First, optimization across multiple units can identify interactions and express their relationship in terms of both macro-level economics and micro-level stream flow targets. A site-wide or refinery linear program (LP model) can be linked to individual controls through the clever transformation of the decision space from one level to another. The result is that governance of plant economics becomes increasingly autonomous.
Optimization can also be extended to offsite operations and the linkage between feed logistics, process units, product blending in refineries and finished product logistics. New approaches to tank farm valve management, the capture of measurements from the field and wireless communications over a tank farm or marine loading dock can help achieve more intelligent logistics operations.
Second, technology can enhance performance over the run-length cycle of a plant. Refineries and petrochemical complexes typically have run lengths of three or four years between major shutdowns. During that time, plant equipment such as reactors or distillation towers gradually foul or degrade over time, as does catalyst performance.
Currently, management of the long-term cycle is manual. Simulation using a digital twin, for example, can enhance this maintenance process and optimize performance over the run-length cycle of a plant. Linked to the overall economic optimization of a site, it can be used to enforce run-length driven objectives to deliver intelligent and resilient operations.
Safety, reliability and performance
Because the road to autonomous operations is a journey, changing roles in the process will be gradual. And in all autonomous operations, there will still be substantial roles for people for tasks or incidents.
Technological developments that support those that remain in the short, medium and long term remain vital. Two are particularly ripe for review.
The first concerns alarms and process safety. Alarm management, logs and analysis have come a long way in developing mode-based alarms with units. Yet cross-unit or transitional alarm settings are still not usually implemented.
Meanwhile, verification of functional safety and safety instrumented systems remains largely defined by standards such as IEC61511. Increased closed-loop verification and flagging the need for remediation of safety elements such as sensors, valves or logic is key to achieving more resilient operations. Whether it’s scheduling verification of valves and sensors or notification of the results, capturing such information and linking it with the process control domain will be crucial to achieving more autonomous operations.
The second area that could see remarkable improvements is process and equipment health and performance monitoring. Models of equipment and assets such as pumps, heat exchangers, compressors and filters have played an increasing role in recent years in improving facilities’ maintenance and process performance.
While individual equipment’s health and performance are better understood, the focus remains on single assets. The next step in engineering oversight must be cross-asset behavior flags: identifying where the temperature of incoming fluid from an upstream exchanger flags an event to the pump; a deficiency in the pump discharge head flags a downstream reactor. Ultimately, autonomous operations in terms of engineering surveillance will depend on these cross-asset conversations.
Remote and resilient
As operator actions in the field are reduced, control center locations can move away from the plant site. That brings enhancements to safety, productivity and efficiency, as personnel are relocated from potentially hazardous environments and freed to focus on performance improvement rather than data collection and manual analysis.
Even project activities can be increasingly managed remotely, including changes in control, safety and security infrastructure, with minimal plant impact up to the point of cut-over. This remote approach can be achieved by separating the design from physical equipment and using universal input/output (I/O) technology that allows control cabinets and channels to be configured for any I/O purpose.
Remote capabilities can also reinforce resilience. Remote support for control and safety systems infrastructure can improve monitoring, accelerate troubleshooting and eliminate delays waiting for site visits. This remote support can all be implemented with high levels of cybersecurity.
At the same time, autonomous operations will need to be supported by resilient infrastructure at the plant. That doesn’t mean failures won’t occur, but it does mean the system or process continues to operate normally and recovers automatically.
Traditionally, resilience on-site has relied on redundant controllers taking over in the event of a failure. A fault triggers the backup. However, a second fault will still cause an outage. True resilience requires that the operation continues even with multiple faults, running until the compute is exhausted.
This resilience can be achieved by using multiple process controllers as a distributed mesh – similar to a data center of controllers. Control strategies are no longer assigned to a specific physical controller. Instead, they are deposited in a community of controllers that automatically distribute control to wherever there is available capacity.
It is of, course, just part of the journey to autonomous operations that will develop at different places across different functions and domains. For many, if not most, the journey will be a long one. But it will be worthwhile, and businesses will enjoy benefits from each step they make along the way.