Industrial Process Operation 4.0

Digitalization is impacting industrial processes as the technical infrastructure that allows data-driven decision making—Internet of Things, big data, artificial intelligence, virtual reality—becomes available
Process Auto Main Img

By Martin Hollender, PhD

Digitalization, Internet of Things (IoT), big data, artificial intelligence, and virtual reality are some examples of rapidly developing areas of technology that will have a big impact on how industrial processes will operate in the future. Normal operations that are already highly automated will be even more automated in the future. Tasks like fault detection, diagnosis, and process optimization are becoming more complex.

Many of those tasks are best handled by interdisciplinary teams with broad expertise and knowledge about process, plant, operations, maintenance, networks, sensors, and actuators. Collaborative process operations make it possible to efficiently bring disciplines together to focus on the problem at hand. Big data and artificial intelligence tools support teams and make them as efficient as possible. Previously isolated control rooms become networked control centers for the Industry 4.0 high-performance work force. Work environments must support collaboration at all levels and support high-performance work around the clock.

Like the situation in the transport sector with the advent of self-driving cars, the way industrial processes operate is dramatically changing. Today's sophisticated digital automation programs can handle most situations. Cheap sensors connected to powerful artificial intelligence algorithms, like image recognition or vibration monitoring, can increasingly replace human sensing. A single operator can take responsibility for larger and larger plant sections.

Integrated industrial information systems gather operational data to enable collaboration across locations, disciplines, and organizations. They make real-time data easily available to the appropriate individuals.

However, the reality is often far from ideal. In a case example about offshore platforms, McKinsey has shown that although huge amounts of data are already being collected, only a small portion is actually being used as a basis of operational decisions (figure 1). This is currently changing, as the technical infrastructure that allows data-driven decision making becomes available.

Other important trends include flexible modular plants for producing small quantities of frequently changing products. Such processes are more difficult to operate because of the frequent product changeovers, and it is more difficult to gather experience.

New big data and artificial intelligence methods can predict upcoming problems long before they affect production. They also enable prescriptive maintenance strategies. Remote operation is becoming more widely used. Often it makes sense to bring in highly specialized remote expertise. Sometimes even the whole plant is operated remotely, as is the case for many offshore platforms.

Modern control rooms have turned into networked information and communication centers where collaboration workflows come together. The remaining operators need a supportive work environment that helps them stay vigilant and carry out their jobs as effectively as possible.



Process Auto May/Jun fig 1
Figure 1. Case example about data-driven decisions.


Process Auto May/Jun fig 2
Figure 2. Although industrial applications have been lagging behind consumer and enterprise
solutions, industry is now catching up to provide the same level of digital support to
the industrial worker and the office worker.



Breaking down information silos

Modern process plants are complex and highly coupled systems. As a result, a problem in one part of the process will tend to propagate across different subsystem and plant components. The advanced automation systems in use also add complex dynamic interactions between the different plant components, making it difficult to obtain a clear assessment of a potential problem. Collaborative efforts from a multidisciplinary team are needed to effectively troubleshoot, diagnose, or optimize process dynamics. In addition, the highly advanced systems used to support plant operations may also require the involvement of specialized expertise, often represented by an external supplier.

Unfortunately, collaboration between personnel from different disciplines, locations, and organizational boundaries is often hindered by the fact that the information needed to solve the problem at hand is hidden within numerous information silos. Knowledge workers in process operation still spend too much time searching for data in information silos or proprietary tools. Many companies also lack the organization and work processes to support multidisciplinary collaboration, and therefore tend to execute work based on a relay race approach instead of as a collaborative effort.

However, industrial companies are realizing that they need to improve the way they work to stay competitive in an increasingly volatile market. The digitalization trend is sweeping across the industries. Companies are taking actions to improve workforce effectiveness through the introduction of digital technologies. Many companies are introducing "bring-your-own-device" policies and deploying solutions so their employees can work effectively wherever they are: at the office, on trips, or from home.

Although industrial applications have been lagging behind consumer and enterprise solutions, industry is now catching up to provide the same level of digital support to the industrial worker and the office worker, whether they are in the control room, in the plant, or in a remote location (figure 2).

Information previously hidden within the control systems or proprietary tools is now increasingly made available through improved connectivity and integration across different systems and network layers. Web-based applications are available to support the consolidation of data from different systems and tools, making these easily accessible from one place. Easy data access and a common work environment is the first step for effective collaboration to support process operation. Improvements in analytics and visualization techniques also help workers make sense of the increasing amount of data available.

Other technology trends are also supporting a new collaborative approach to working. After many years of teething troubles, video conferencing technology has matured and is moving from a nice-to-have technology to a necessity. Several companies now have remote operation centers that support the local control rooms with continuously open video links between locations. High-quality video conferencing technology is also available from mobile devices or personal workstations, so operators can get instant access to remote expertise via video conferencing whenever they need it. In combination, the introduction of digital technology for easy access to information, independent of location, and the proliferation of video conferencing to support remote collaboration, are blurring the boundaries between local and remote operation.

Modern automation systems cover most aspects of normal operation but also handle many abnormal situations. Advanced control techniques, such as model-predictive control (MPC) and state-based control, allow the automation of very complex tasks, such as the startup of a plant. Automatic control performs better than typical human operators. The operator is less and less involved in the inner control loops with direct contact to the process. The tasks shift more and more to supervisory control, where the operator manages and supervises a large number of control modules.

Bridging the knowledge gap

But being less involved in direct process control also means fewer opportunities to develop a feeling for the process by training on the job. (This problem was dramatically illustrated with the accident of flight AF447. The autopilot discovered inconsistent speed measurements from all three redundant speed measurements and switched into manual mode. The pilot did not have enough experience flying at great heights and was overburdened with this sudden and unexpected transfer of responsibility. He went into climb mode, which reduced the speed of the plane and finally led to the crash.)

To be able to take over when automation fails, operators need higher qualifications and a profound understanding of the technical process, the automation system, and the control modules. Simulator training is necessary to develop a feeling for the process. Modern operators should also be deeply involved in the optimization of process operations, because such an activity keeps them involved and helps to build up the required knowledge that allows them to take over in case of automation failure.

Another area where Industry 4.0 will have a huge impact is industrial quality control. Big data techniques make it possible to distill historical process data into algorithms that can predict the quality of the currently production. Upcoming problems can be detected early, and countermeasures can be taken before the effect of the problem becomes significant. Previously, it took an operator many years to accumulate comparable experience.

Remote expertise should be brought in for all complex and difficult decisions (figure 3). For example, in the case of the Deepwater Horizon oil spill, the investigation report clearly states that one major factor contributing to the accident was the incorrect interpretation of available measurements. Quite likely, with advice from highly qualified remote experts, the company would have avoided this accident.

The high complexity of modern plants requires expertise from many different domains (e.g., MPC, chemistry, electrical drives, distributed control systems). It is impossible for most plants to hire personnel with sufficient knowledge in all these areas. Modern collaborative environments make it possible to bring in remote expertise as needed.

Managing key performance indicators for process operations in areas such as control loop performance, alarm management, energy efficiency, and overall equipment efficiency is not a classic operator task but is becoming more and more important to ensure good production performance. Disciplines such as operations, maintenance, and analytics need to go hand in hand to achieve best results. Many of the tasks either can be performed by centralized internal service centers or can be outsourced to specialized external service providers.

Typical goals are increased throughput, efficiency, and uptime for the production plant. These goals are accomplished by a structured approach to revealing the sources of process variations and upsets and how they are currently handled. By reducing process variations, organizations will increase the operational flexibility, plant regularity, safety, and integrity, while reducing off-spec production, energy costs, environmental impacts, operator stress, and equipment wear.

For example, Dow Chemical introduced a global analytics layer that turns vast amounts of data into information and metrics anyone could see. Experts from a centralized Analytical Technology Center can now support plants globally to determine manufacturing obstacles, improve efficiencies, and develop best practices. World-class expertise, methods, and tools are now available.



Process Auto May/Jun fig 3
Figure 3. Modern operators should be deeply involved in the optimization of process operations, because such an activity helps to build up the required knowledge that allows them to take over in case of automation failure. Remote expertise should be brought in for all complex and difficult decisions.



Improving the working environment

As shown in previous sections, most simple parts of traditional operator work have been taken over by automation. Modern operators now have a very different profile. They supervise large numbers of control modules and must be able to quickly diagnose complex situations, collaborate with various support units, and coordinate field operators and maintenance personnel. They decide when it is time to bring in external expertise and manage the temporal integration of remote experts. To make use of their full potential, they need a work environment that really supports their work.

A challenge will be how to design the more collaborative environments that will replace traditional control rooms. Often those centers will no longer be physically close to the process, but they need to be much better integrated with remote service communities in their own company and with service providers and suppliers. New collaboration centers can also be implemented to work through different steps in modernization before the entire technology and organization is ready for all benefits.

The involvement of experienced control room designers from an early stage is even more important in the design of next-generation, collaborative operations centers. They require a totally new approach and "future integration" thinking. As the traditional way of building control rooms becomes obsolete, new best practices will have to be defined.

The new control centers will have fewer operators, and the operator role will evolve from reactive to predictive problem solving and analytic operating. It will become more important to have motivated, stimulated, and more alert operators with better education to deal with increasingly bigger parts of the production process.

The space around the operator will be more connected to many other functions, such as IT/OT support, multifunctional support, technical and remote support, asset risk management, alarms, safety, cybersecurity, and maintenance management, that previously were often separated from the control room operations. More frequent interactive communication with different remote service people to jointly solve troubleshooting and optimization tasks will require a work environment that supports this kind of work as well as if they were in the same room.

These new workflows, still rare today, but which will be the norm tomorrow, have completely new requirements concerning room layout, working zones, screens, cameras, analytical tools, and remote collaboration workspaces. An example of the new design is five traditional control rooms with 12 operators will be replaced by a collaborative center hosting two operators, who will call in remote expertise on demand. The space around the operators will be more connected to many different functions that were previously separated.

There is ongoing research to understand how we can establish an individual health improvement microenvironment that can be adapted to each operator. A typical integrated platform will be much more than an advanced motorized operator desk. This platform is a complete health improvement microenvironment that can be adapted and even automated to change for each individual operator depending on individual needs. For example, the distance between eyes and screens can automatically be adjusted with imperceptible slow speed to release muscle tension in the eyes, and the lighting can shift from warmer to colder light during the day. These are just two examples of how technology can support the health and well-being of the operator.

New technology and big data analytics make it possible to create a data-driven "day by day" improvement program for operators. The new collaborative operations center will turn big analyzed data into actions and, thanks to Industry 4.0, yield benefits by becoming faster, safer, more competitive, and of course more profitable.



Process Auto May/Jun fig 4
Figure 4. The only way to encourage the next generation of operators to work in control rooms is with a holistic approach to the control room working environment. Introducing gamification can be a motivation for learning, education, and passing knowledge from baby boomers to the gaming and multitasking generation.



New generation of operators

Generational shift will affect business markets and the industry sectors as the older generation (i.e., baby boomers) retires. One challenge will be to attract the next generation of operators, often referred to as Generation Y, the gaming generation, or the multitasking generation, into the control room working environment. An average, a gamer executes up to 300 actions per minute, while a nongamer can perform a maximum 100 actions per minute (figure 4).

Personal ergonomics is becoming more and more important to improve the health and well-being in the control room working environment. Human factor involvement in the early stage of design layout is even more important in future control rooms or control centers with the entry of the next generation into the industrial field. We must seriously consider the needs, requirements, behaviors, and values of the next generation of operators that we need to attract to the industrial world.

The only way to encourage the next generation of operators to work in control rooms is a holistic approach to the control room working environment. Acoustic disturbances will play a key role if operators must share a common working space, communication devices, navigation keyboards, etc.

Improved illumination is another area of concern, because we know that interrupting individual circadian rhythms can have devastating consequences for shift operators. Air quality, heating, air conditioning, and ventilation also matter when enhancing human performance in the control room working environment. Dedicated operator fatigue management minimizes the influence of fatigue.

The knowledge gap is another problem that we will face as baby boomers retire. One way of transferring knowledge from baby boomers to the gaming and multitasking generation is by introducing gamification as a motivation for learning, education, and passing on knowledge. Human-centered design that creates intelligent and individual working places is the way forward to meet these demands for the next generation of operators.

Integrated control centers

With the shift away from traditional control rooms toward integrated collaborative control centers, tomorrow's operators will require a very different skill set, with much more emphasis on cooperation, coordination, analytics, and management. To be able to attract the best operators and offer them an environment where they can consistently bring high performance in 24/7 work settings, the integrated control centers should be designed by experts from the beginning.

New digitalized infrastructures tear down information silos and make world-class remote expertise available. Optimizations previously not possible are coming into reach.

Note: This article was adapted from Hollender, M.; Graven, T.-G.; Partini, J.; Schäring, P. Process Operation 4.0. atp edition, 2017, 59, pp. 52–58.

 
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Fast Forward

  • Digitalization, IoT, big data, artificial intelligence, and virtual reality will improve industrial process operation.
  • Work environments must support collaboration at all levels and support high-performance work around the clock.
  • Knowledge workers in process operation still spend too much time searching for data in information silos or proprietary tools.
 

About the Author

Martin Hollender, PhD, is a principal scientist and project leader at ABB’s Corporate Research Center in Germany.

 

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