August 2022


Viewpoint: The pathway towards autonomy: How process automation is building the future plant

Hydrocarbon Processing sat down with Jason Urso (JU), Chief Technology Officer, Honeywell Process Solutions, to discuss the current state of the process automation industry, how new technologies are enhancing efficiency and safety, and what the future holds for automation.

Urso, J., Honeywell Process Solutions

Hydrocarbon Processing sat down with Jason Urso (JU), Chief Technology Officer, Honeywell Process Solutions, to discuss the current state of the process automation industry, how new technologies are enhancing efficiency and safety, and what the future holds for automation.

What does the future plant look like and how can process industries get there?

JU: Major industrial producers today are focused on sustainability, productivity, safety and compliance. This involves environmental-focused initiatives like helping to reduce carbon footprints and improving safety of the plant, personnel and equipment. It also comprises new areas, such as ensuring the right level of talent are available due to the challenges associated with an aging workforce and reluctance from the next generation of workers to seek employment in oil and gas-related industries. Industrial autonomous operations provide a future where industrial facilities can continue to improve performance in these areas. By moving to a higher degree of autonomy, industrial operators can improve safety and environmental performance, increase efficiency over historical levels, improve reliability and attract highly skilled talent.

The future physical plant looks similar from a distance—the same pipes, columns, etc., are being used to process product. However, a significantly higher number of sensors are being employed with technology (e.g., drones and robots) to bring in data more frequently than can be accomplished by humans. New talent will be trained with technologies like augmented reality (AR) coupled with digital twins of processes and plants where they are able to learn how to physically respond to events that were previously taught on paper due to their hazardous nature or the infrequent occurrence of the operation. Systems in the plant must become increasingly self-diagnostic and eventually self-healing. As industry relies more on sensors, personnel need to consistently know their status in case a sensor malfunctions. The future of highly autonomous plants brings a higher degree of awareness in both its processes and systems.

How have current automation technology and software solutions impacted process industries today?

JU: Automation technologies like digital twins, advanced process control, historian and control systems are resilient and easy to engineer, maintain and upgrade—they form the basic backbone of industrial operations. Advancements in these technologies enable a cybersecure data exchange to the cloud and apply smart analytics, artificial intelligence (AI) and machine learning (ML) to the data to gain actionable insights. This is the path forward for the process industries to become more efficient, safer and more compliant. Some of the key drivers and enablers for autonomous technology in industries today are the relatively low cost and availability of sensors coupled with the advancement of data science and analytics to turn data into information. By adding sensors into the process, we can apply digital eyes (video), ears (sound), feel (e.g., vibration and heat) and smell (e.g., emissions). While these sensors are not purposed to replace human monitoring, they offer an advantage; they can be applied continuously or at least more frequently than what a person can do. Getting the data from these devices enables personnel to leverage data analytics to analyze what has been detected to a higher degree than ever before. When people sense something through routines like operator rounds, a report or log of the observation is created, but it is a qualitative account. Using sensors enables workers to log quantitative values and evaluate trends vs. simply comments or observations. By analyzing and correlating trends of quantitative data, plant personnel can detect and prevent undesirable events. For example, by detecting increasing levels of vibration, heat or sound, workers can detect mechanical issues long before equipment reaches a point of failure.

How will autonomous operations improve plant safety, reliability and efficiency?

JU: Autonomous operations can look at multiple aspects of plant operation and optimize it based on the entire value chain, from incoming raw material, energy used (green energy), emissions compliance and productivity to final finished product output.

As industry detects abnormalities in processes faster, personnel can take many more planned actions prior to a failure. If we run plant equipment to failure, we risk having challenges during startup, shutdown and, ultimately, we can jeopardize the stability of the operation. When abnormalities, or even variables trending away from normal operations, are detected early, planned actions can be taken. Personnel can switch to spare equipment, have required parts and expertise on-hand for anticipated maintenance, make repairs faster and have all equipment back to a normal state much faster when challenges are anticipated.

Beyond managing these abnormal situations, autonomous operations enable a higher degree of optimization. Leveraging improved data analytics, AI and ML can optimize industry operations. We can minimally duplicate what the best human operators do and make every operator the best operator at the facility. Our organization has been a member of the Abnormal Situation Management consortium for many years. Here, member industrial companies lead studies and work with other manufacturers to reduce human error and help to make operators more effective. Since our company is both a technology provider and a manufacturer of chemicals in our own plants, we have a unique capability and desire to improve operator effectiveness for our customers’ and our own plants.

How has the industrial evolution of control technology benefited plants and facilities today?

JU: Processing plants today operate significantly safer, more efficiently and more reliably than ever before. This has been possible largely through automation. The industry has progressed from old technologies when plants were controlled by pneumatic controllers. When digital controls became available, industrial producers saw significant improvements. Processes were controlled more precisely than ever before. Data was captured and stored electronically vs. by paper chart recorders. As processes were controlled better, industry was able to optimize—the next level of advancement came with advanced process control (APC) where control technology not only controlled input variables like temperature, pressure or flow, but also controlled output variables. With this advancement, the process industry was able to control quality parameters and optimize production across facilities. This fueled the development of soft sensors and inferential matters that were early applications of AI. In turn, this enabled prediction and control of outputs like quality parameters based on mathematical calculations and correlations without the need for many instruments and analyzers. This evolution has established a strong foundation that continues to develop into industrial autonomous solutions today.

Have you noticed an increase in autonomous solutions implemented by industrial leaders?

JU: We absolutely see an increase in autonomous solutions implemented by industrial leaders. Most industries are challenged to improve the safety, reliability and efficiency of their processes, and because autonomous solutions can provide benefits in this area, we see interest from most of our customers. As with any technology advancement, we also see leaders in adoption while others take a wait and see approach. As the leading industrial operators are experiencing significant benefits in their projects, the wait and see segment of customers will start to catch up. Autonomous solutions increase the ability to train new talent faster as well as attract higher skilled talent with an appetite for technology; those early adopting customers are staffing with the best and brightest.

As more autonomous technology is applied to processes, we are better able to connect remote expertise to support producing sites—this has enabled the use of remote hubs of talent for monitoring, support and surveillance of enterprises. This area developed rapidly in the last two years as part of our customers’ pandemic response. By connecting support remotely, industrial employers were able to minimize exposure of their site-based workforce, as well as mitigate long quarantine periods for those that would have historically travelled to sites. As this culture of remote support grew, the automation industry quickly expanded the use of remote technology. We are now able to migrate customer automation systems from older versions of software to current versions using remote connectivity. We can also provide support to commission new startups without having engineers travel to the construction site, and we can test and prove new installations with remote engineers that have live connections and video feeds to the industrial site.

Are there specific controls and remote solutions that have the flexibility to fit any plant or facility manager’s custom needs?

JU: There are a few areas of autonomous technology that not only fit any plant’s needs but that are becoming necessary to most of them. First, anything that is done must be done with the highest levels of cybersecurity—it is important that both the IT (information technology) and OT (operational technology) digital infrastructure are architected and protected with adequate cybersecurity protection. Once a cyber infrastructure is created, the facility can enable remote connections. By allowing remote views or even control of processes, most plants can improve their offsite support. From simply enabling on-call weekend or afterhours support, empowering leadership to see what is being seen inside the plant or connecting to corporate-level technical teams, remote connectivity provides significant benefits. Once remote connectivity is established and initial benefits experienced, some customers progress to remote operations. By creating control centers outside of hazardous process areas or in remote geographies, plants can establish higher levels of safety and improve access to talent.

What steps should a plant/facility take to achieve industrial autonomy? Is there a roadmap a plant manager/supervisor can follow?

JU: Our company has developed a 5-stage maturity level map to identify where a plant or facility are on their journey to autonomous operations. These include the following:

  • Level 1: Controlled and optimized
  • Level 2: Intelligent plant
  • Level 3: Remote and integrated operations
  • Level 4: Resilient operations
  • Level 5: Autonomous operations.

A facility must first identify where in this maturity level map they are and then they can work with a technology provider to develop the roadmap to autonomy. The journey to autonomous operation is not a one-size-fits-all approach. The roadmap should start with a strong plan for change management. We have seen examples where technology application without change management has created an end state of lower efficiency than the starting point. The desired results must be mapped with technology and change management processes that enable the result. Our organization has staffed a team of process change consultants, as well as partnered with other companies to facilitate our customers’ autonomous journey. We have created standard deployment guidelines for industry verticals that describe available technologies and typical benefits experienced by each industry. By applying a consultative approach with our customers, we can participate in a discovery process and share which applications have been proven high-value in their industry.

How does an autonomous operation help plants reach their sustainability goals and reduce their carbon footprint?

JU: Autonomous operation can enable sustainability in several ways; we have already touched on how it enables a sustainable workforce. Operating autonomously can also have significant impact on carbon footprint. For example, by implementing autonomous technologies that measure emissions from the process, industrial operators can quickly detect process emissions and incidents like smoking flares and methane emissions. Our organization’s new emissions control and reduction initiative allows customers in a wide range of areas to detect the precise location of methane leaks through a combination of detection and gas cloud imaging cameras, translating the information into comprehensive data analytics and trends. Customers will then be able to use this data to quickly identify leaks, increasing productivity and maintaining legislative compliance. This kind of technology can also help prevent the root cause of emissions by reducing process upsets and eliminating unplanned shutdown/startup activity. In addition to beneficial technologies such as these, our company has the capability to provide other solutions to reduce carbon footprint: technology to produce renewable fuels, game-changing battery technology for renewable energy storage and environmentally friendly refrigerants for processes, improving numerous areas that positively impact our customers’ carbon footprint. HP


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