November 2018

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Viewpoint—Industry 4.0: Demystifying the next big thing in oil and gas

Until a few years ago, the term Industrial Revolution referred to the significant technological changes that began in the late 1700s with the advent of the steam engine, leading to the mechanization of work and the unprecedented economic growth and prosperity that followed.

Habibi, E., PAS Global

Until a few years ago, the term Industrial Revolution referred to the significant technological changes that began in the late 1700s with the advent of the steam engine, leading to the mechanization of work and the unprecedented economic growth and prosperity that followed. The age of the steam engine is now considered the first Industrial Revolution. The second Industrial Revolution began in the late 1800s with the proliferation of electricity, enabling 24/7 factories, Henry Ford’s assembly lines and mass production. The third Industrial Revolution—often referred to as the Information Age—started just after World War 2 with the advent of computers and their adoption in industry.

Industry 4.0 was popularized at Germany’s Hannover Fair in 2011 and has become synonymous with the fourth Industrial Revolution. Characterized by smart manufacturing and industrial digital transformation, Industry 4.0 takes us from the era of automation and information to the age of the ‘wisdom of the machine.’ Here, automation converges with manufacturing knowledge, leveraging massive amounts of existing and new sensor data, emerging data analytics methods and intelligent computing in a continuous learning mode. The ultimate success of Industry 4.0 will be measured by its effectiveness in bringing about step change gains in production, safety and reliability. Existing and disruptive technologies promise to take industry from automated to autonomous manufacturing.

Enabling technologies.

The Industrial Internet of Things (IIoT) comprises the core technologies that enable Industry 4.0. The first step in the journey toward Industry 4.0 begins with digitalization of the enterprise—the unification of the cyber-physical and the reengineering of work processes to create new value-add opportunities. As expected, oil and gas executives require tangible and significant business drivers with clear return on investment to justify their companies’ investment in IIoT.

IIoT extends automation and business intelligence platforms to the next level by converging the internet, big data and advanced analytics. Many of the core technologies that make up IIoT have been around for decades but are increasingly more efficient and reliable. Core IIoT technologies can be classified into three categories:

  1. Smaller, cheaper and smarter sensors and actuators
  2. Ubiquitous connectivity through the internet, WiFi, Bluetooth and other communication media
  3. Powerful and affordable computer hardware with fast-evolving artificial intelligence (AI) enabled by data science, machine learning and deep learning.

Industry 4.0 and what it means for the processing industries.

The convergence of these technologies is enabling breakthrough innovations that continue to improve our quality of life. Smart devices remotely monitor and control our residential home security and climate. Hearing aids connect with our smart phones to stream alerts and music. We can track the driving behavior and whereabouts of our teens in real time (much to their chagrin). Computer-based process automation systems have been around for over four decades. For example, the hydrocarbon processing industries have leveraged advanced process control and optimization (APC&O) to improve throughput, yield and quality since the early 1980s. APC&O is inherently a good example of smart manufacturing. However, the greatest challenge with APC&O has been scalability and maintainability. The limitation of automation systems is that they are deterministic—highly engineered and designed to deliver a specific, narrow objective. They do not take advantage of modern AI that has provided value to other disciplines, such as detecting fraud for the credit card industry. IIoT promises to help accelerate the deployment and improve the maintainability of known critical value-adding technologies like APC&O.

IIoT also offers new business optimization possibilities. Chief digitalization officers at some major oil and gas companies are inviting data analytics and advanced technology suppliers to provide new offerings to mine emerging data lakes and deliver new value-adding, actionable intelligence.

The digital twin.

The digital twin refers to an accurate replica of a physical entity, like a process plant, its equipment assets, processes and systems in a highly integrated computer model with all its core elements. Typically residing in the cloud or on the facility premise, core elements of a digital twin include the automation and safety protection systems, the process design and chemistry models and the related manufacturing execution system (MES) technologies, such as production planning, advanced controls and computer-based maintenance management systems (CMMS). Once captured, the digital twin provides an integrated and dynamic representation of the plant’s physical counterpart. The digital twin is the ultimate plant reference model.

New business improvement opportunities created by the digital twin include (1) real-time intelligent advisory systems to help improve operators’ situation awareness with early fault notifications of process events; (2) next-generation equipment health monitoring; (3) process optimization advisory notifications for complex processes like polymers; (4) initial design, implementation and maintenance of dynamic operator training simulators (OTS); (5) real-time discovery, inventory and configuration change management in service of enhanced operational technology (OT) cybersecurity; (6) dynamic process safety lifecycle management, including boundary and independent protection layers (IPL) management; and (7) remote asset performance monitoring, benchmarking and diagnostics.

Challenges.

Like other disruptive technologies, IIoT presents hurdles that must be overcome before crossing the proverbial chasm of mainstream market adoption. Challenges include the contextualization and management of data, as well as the cybersecurity of data, processes and assets in the plant.

The fuel that feeds IIoT is data. Structured and unstructured data from sensors, systems like industrial control systems (ICS), the process historian, MES applications and business systems like SAP are prolific. Reliable gathering and processing of data from such disparate sources has been a challenge that has haunted the processing industries for decades. Until all manufacturing systems from field instrumentation to enterprise resource planning (ERP) become interoperable, if ever, we must find ways to aggregate, normalize and deliver massive amounts of data reliably.

Captured data without context is of little value. For example, real time process measurement data for use in condition-based monitoring and maintenance must be correlated to the physical assets, related automation configuration and associated process models. For example, assessing the functionality of a process control loop requires more than process measurements gathered from the historian. It requires proper context related to process dynamics and control objectives. Intelligence in analytics comes from insight. The insight comes from experts such as process, reliability and automation engineers. A successful IIoT technology strategy must provide for automated capture and integration of human knowledge into the data analysis and visualization.

As challenging as data management is, the greatest risk to a corporate IIoT strategy comes from the fast-growing threats to cybersecurity. As more field devices are added, connectivity is expanded and advanced applications are applied, the attack surface for a cybersecurity breach increases. The state of OT cybersecurity for most of the industry is mixed. Many OT assets are not even known to owner/operators, much less secured. As industry executives define their IIoT strategies, they must also consider plans to protect the existing infrastructure. A robust strategy for securing OT assets must begin with the establishment of an accurate and complete inventory of ICSs and their peripherals. All endpoints must be documented, from field instruments at level zero, to programmable logic controllers (PLCs) and controllers at level 1, and the human machine interface (HMI) at level 2. They must implement an automated vulnerability management system and prioritize remediation of discovered vulnerabilities. Once a configuration baseline of the OT system and the digital twin has been captured, a strict management of change process is needed to maintain the integrity of the systems.

Data Integrity.

Production, safety and maintenance data gathered from field instrumentation travels from level 0 through level 5 systems and networks of an enterprise and ends up in dashboards that help drive decisions at all levels. Therefore, confidence in the quality and the accuracy of sensor data is paramount to the success of an enterprise’s decision-making strategy. The challenge in ensuring the quality of the data is that it must traverse a complex maze of systems that, in many organizations, are under the custody of different organizations—I&E may be responsible for field sensors, automation may own the control systems and the historian and the dashboard may be the responsibility of the IT organization. Any unmanaged change to the data stream can distort the quality of data utilized in the information ecosystem.

Final thoughts.

IIoT and digital transformation are the foundation of the new industrial revolution—Industry 4.0. While it is impossible to fully imagine all the benefits of the new era of productivity, it is easy to see what will be done next—think digitalization. Also consider that the existing OT infrastructure is not fully secure, and that the expanded IIoT environment will create and expose more cyber vulnerabilities. Whether the threats emerge from ransomware hackers, war-gaming nation-states or mistaken operators and engineers, increased risk will accompany digitalization. Leveraging technology to secure cyber assets will be just as important to continued plant safety and security as it will be to realize the benefits of the fourth Industrial Revolution. HP

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