The Measured Revolution Slow and Steady Advances in Process Automation
Published on : Tuesday 17-09-2024
The strategic transformation of process automation, driven by advanced technologies like AI, IIoT, and digital twins, is gradually reshaping industries, say Vijay Mathew and Sumit Goyal.
The landscape of process automation is evolving, albeit at a measured pace. Unlike discrete industries – such as automotive and electronics, where digital transformation has advanced rapidly – process industries have traditionally been slower to adopt new technologies. This cautious approach is often due to the complex, continuous nature of their operations, which involves high stakes and stringent regulatory requirements. In industries like oil & gas, food & beverage, and pulp & paper, any disruption or failure can have far-reaching consequences, both in terms of safety and cost. As a result, these industries have historically prioritised stability and reliability over rapid technological change.
However, this trend is gradually shifting. As the pressures to enhance efficiency, reduce waste, and meet sustainability goals intensify, process industries are beginning to make inroads into digital transformation. Key areas of adoption include predictive maintenance, real-time monitoring, and process optimisation, where the benefits of advanced technologies are becoming increasingly clear. Although the transformation is not as swift or widespread, the gradual integration of technologies such as AI, Industrial IoT (IIoT), and edge computing is beginning to reshape how process industries operate.
This article delves into the evolution of process automation, focusing on the technological advancements that are driving this gradual transformation.
Historical Perspective: The Evolution of Process Automation
Process automation has a rich history that dates back to the early industrial era, where simple mechanical systems were employed to control production processes. A significant leap occurred in the mid-20th century with the introduction of feedback control systems, which allowed for more precise and reliable automation. Over the decades, these systems evolved with the advent of digital technologies, leading to the development of Distributed Control Systems (DCS) in the 1970s. DCS enabled real-time monitoring and control of complex industrial processes, laying the groundwork for the highly automated and interconnected systems that define modern process industries.
Current Technological Advancements: Gradual Integration in Process Industries
Industrial IoT (IIoT): Enhancing Connectivity and Control
The adoption of IIoT in process industries represents a significant, though cautious, step towards enhanced connectivity and control. By linking sensors, devices, and systems, IIoT enables real-time data collection, analysis, and communication, which are critical for optimising processes. However, challenges such as cybersecurity concerns and the complexity of retrofitting legacy systems have slowed widespread adoption. Despite these hurdles, where IIoT has been implemented, it has proven invaluable in improving operational efficiency, enabling predictive maintenance, and reducing downtime.
Artificial Intelligence (AI): Slow Adoption with High Potential
AI is gradually making its way into process automation, especially in areas like predictive maintenance and real-time optimisation. Machine learning algorithms have the potential to analyse large datasets, predict equipment failures, optimise processes, and even automate complex decision-making. However, the adoption of AI has been slow, largely due to the significant upfront investment required and the need for specialised expertise.
Digital Twins: Powerful Tools with Selective Deployment
Digital twin technology offers a powerful means for monitoring, simulation, and optimisation by creating virtual replicas of physical systems. These digital models allow operators to simulate different scenarios, test process changes, and predict potential issues before they arise. The complexity and cost of implementing digital twins have limited their widespread use.
Industrial 5G: Poised for Revolution, but with Gradual Rollout
The advent of Industrial 5G holds the potential to revolutionise communication within process automation through high-speed, low-latency connectivity. This connectivity is critical for real-time data transmission between devices, systems, and control centers, enhancing the capabilities of IIoT and AI systems. However, the rollout of Industrial 5G has been slow, facing challenges related to infrastructure development and cost. As these hurdles are gradually overcome, Industrial 5G is expected to significantly enhance automation processes, particularly in remote or harsh environments.
Smart Industrial Sensors: Advancing Precision and Efficiency
Smart industrial sensors are becoming increasingly important in process automation, offering more accurate and comprehensive data than traditional sensors. These advanced sensors, with capabilities like self-calibration and real-time monitoring, enable precise control and improved quality, safety, and efficiency. The integration of smart sensors has been gradual, often slowed by the challenges of compatibility with existing systems and the need for significant investment.
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Industry Applications: Tailored Automation Solutions for Process Industries
Oil & Gas
The oil and gas industry has long been at the forefront of process automation, driven by the need to manage complex operations and ensure safety in hazardous environments. Advanced automation systems in this sector are crucial for monitoring and controlling everything from drilling to refining, optimising performance, and minimising risks.
Food & Beverage
In the food and beverage industry, automation is key to maintaining consistent quality and safety standards. Advanced control systems manage processes from ingredient mixing to packaging, reducing human error and ensuring compliance with stringent regulatory requirements, thereby safeguarding product integrity.
Pulp & Paper
Automation in the pulp and paper industry is essential for managing the intricate processes of pulping, bleaching, and paper-making. These systems optimise energy consumption, reduce waste, and enhance product quality, all while ensuring adherence to environmental regulations.
Chemicals
The chemical industry involves some of the most complex and hazardous processes, making automation critical for maintaining safety and efficiency. Advanced automation systems manage reaction conditions, hazardous materials, and ensure product consistency, supported by real-time data analytics to improve yields and reduce waste.
Pharmaceuticals
Process automation in the pharmaceutical industry ensures the precision and consistency necessary for drug production. Automated systems control everything from raw material handling to final packaging, ensuring compliance with stringent regulatory standards and optimising production processes through AI and machine learning.
Future Technologies and Trends: Paving the Way for Next-Generation Automation
AI-Driven Automation
Artificial Intelligence is revolutionising process automation, providing the tools necessary for advanced analytics, predictive maintenance, and real-time optimisation. Siemens, with its innovative AI solutions like the Industrial Copilot, exemplifies how AI can integrate with real-time data processing to deliver exceptional operational efficiencies, positioning companies at the forefront of industrial innovation.
Industrial Edge
Industrial Edge computing is reshaping process automation by bringing data processing closer to the source. Emerson’s DeltaV Edge platform is a leading example, enabling real-time monitoring and control directly at the data generation site. This decentralisation reduces latency, enhances decision-making, and supports the integration of AI and machine learning, leading to more agile and responsive operations
Machine Health
Machine health, driven by the integration of AI, IIoT, and advanced analytics, is transforming how industries monitor and maintain their equipment. Ensuring the reliability and longevity of equipment is critical in process industries, where unexpected downtime can be extremely costly. Machine health technologies enable the continuous monitoring of equipment, allowing companies to predict and prevent failures before they occur.Augury is at the forefront of this trend, offering AI-powered solutions that utilise advanced vibration analysis and other predictive maintenance techniques to monitor the health of industrial machinery. Augury’s platform provides real-time insights into machine performance, allowing operators to address potential issues proactively, thus minimising downtime and extending the lifespan of critical assets. By integrating these insights with broader operational data, companies can optimise maintenance schedules, reduce unnecessary repairs, and ensure that machinery operates at peak efficiency.
Software-Defined Automation
Software-Defined Automation represents a paradigm shift in industrial automation by decoupling automation logic from hardware. SDA, a pioneering company in this field, offers a suite of products that leverage AI and machine learning to redefine how automation systems are designed and deployed. Their virtual PLCs allow for rapid adaptation to changing operational needs, reducing deployment time and costs, and enhancing scalability – key benefits in industries requiring constant optimisation.
Conclusion: Embracing the Future of Process Automation
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The strategic transformation of process automation, driven by advanced technologies like AI, IIoT, and digital twins, is gradually reshaping industries. While the adoption has been slower compared to discrete industries, the potential for enhanced efficiency, reliability, and sustainability is becoming increasingly clear. As process industries continue to integrate these technologies, they will unlock new levels of productivity and competitiveness.
The journey toward fully digitalised and autonomous process automation is filled with opportunities for those ready to embrace change. The future of process automation is bright, and the companies that invest in these technologies today will lead the industries of tomorrow.
Vijay Mathew is Director, Industrial Technologies, at Frost & Sullivan. With over 18 years of experience, Vijay is a seasoned advisor known for providing strategic, unbiased, and objective advisory services across a variety of industries. His areas of expertise include automation, process control, industrial sensors and instrumentation, and electronic test and measurement.
Sumit Goyal is Consulting Analyst, Industrial Technologies, at Frost & Sullivan. Sumit is a Mechanical Engineering graduate from Ahmedabad and has completed PGPM from ICFAI Business School with a major in Marketing and minor in Operations. He has a keen interest in Statistics and Data Science, and was earlier a Strategy Consultant at NEC Corporation.
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