Future Trends in Process Industry
Published on : Monday 05-12-2022
How is the availability and maturity of new technologies shaping the Refinery of Future?
Process industry was an early adopter of automation in its operations but has been slow in the journey to digital transformation. Discrete manufacturing stole a march ahead by rapidly adopting industrial automation and digital transformation in one step. But recent developments both in technology, and also in the manufacturing eco-system, have nudged process industries to get serious about incorporating data technologies. So which process industry domains are ready for digital transformation? Ready in a sense of having a technology base and competence, and also ready in a sense of management acceptance?
“Companies across industries are looking to enhance their data-driven decision-making skills, agility, and speed in the ecosystem. Adopting a bionic approach involves the right blend of human capabilities and digital capabilities, and organisations that are undergoing digital transformation apply those capabilities to all aspects of their business, thereby keeping the momentum going,” explains Rajesh Nath, Managing Director, VDMA India Services Private Limited, German Engineering Federation (VDMA). According to him, along with artificial intelligence (AI), advanced analytics, and the cloud, process automation is a core component of digital transformation. Smart manufacturing solutions cover the areas of Operations Management, Production Optimisation, Supply Chain Management, Plant Asset Management, SDGs, and Energy Management & Optimisation. Further, it is not just the process industry as in Oil & Gas that is benefiting from digital transformation, but also several other segments like farming and agriculture, healthcare and telemedicine, banking and finance, training and education, and even the legal and judicial services are increasingly looking at digital solutions to address bottlenecks.
Dr Marcio Wagner da Silva, Process Engineer & Project Manager, Crude Oil Refining Industry is of the view that it is industry as a whole that is advancing in the digital world, since it is obviously not a question of choice any longer, but is strictly related to the survival of the companies in an increasingly competitive environment. “Despite this, it's possible to see some industries like food, paper and cellulose, and other manufacturing processes ahead in the digital transformation efforts than the refining industry, for example. This is strictly related with the process risks that are inherent of the crude oil refining sector and the whole oil & gas industry, this characteristic lead the management to be more conservative in the experimentation and implementation of digital transformation projects, but it's important to highlight great advances in this area like the use of drones to carry out some operational routines and the IoT devices to monitoring critical process equipment like pumps and compressors,” he elaborates.
“In the process industry manufacturing domain, many large companies from sectors like oil refining, exploration & production (E&P), metals and bulk chemicals are already at some level of digital maturity as they had the benefit of being early adopters of technology like MES and Advanced Process Control,” says Sushant Rabra, Partner Digital Strategy, KPMG in India. “Such companies are ready for the next leap of digital maturity in areas like compliance, worker safety, supply chain management, asset performance management and ESG. Also, the Pharma industry is expected to take this leap as well, due to the stringent needs of the sector and high impact benefit areas like R&D.”
Adding another perspective, Shyam Warialani, Managing Director, Baumer Technologies India Private Limited, is of the opinion that there are three groups across the sectors that have better digital maturity and hence better digital transformation – Technology, Telecommunication and Financial Services. “The group comprising the consumer and industrial sectors (process industry) are on an average less digitally mature. The consumer sector would have a better chance of success. This is due to the fact of consumers’ pressure for better digital expectations (online, purchase, Uber service or Air-BnB kind of experiences). The industrial goods sectors still have to take a long time for digital transformation. The process industry can adopt digital transformation but this has to be more towards improving internal processes, production activities, automations and improvising consumers with faster deliveries, best after sales services and products with better quality,” he says.
“My expertise is limited to the upstream oil and gas industry. My views therefore are restricted to automation and digitisation in this area of the process industry. One must understand that this is a niche field rarely open to the normal process environment. Hence the normal process control or digitisation in factory or pharma cannot be compared in this case,” says Khurshed R Printer, Proprietor, M D Fusion Technologies. According to him, oil exploration and processing is an extremely challenging engineering subject. What makes it very different from factory automation is that there is no margin for error. The work environment is always hazardous from exploration to production.
Digital transformation has been seen as a consumer driven impetus for discrete manufacturing of consumer products. How does it translate for process industries? Which drivers work for the process industry to embark on digital transformation?
Rajesh Nath believes increasing efficiency at all stages of the manufacturing value chain, optimising cost structures, as well as producing and delivering products and services at certain quality levels will remain important in order to stay globally competitive. “However, being able to respond appropriately and smoothly to fast-changing and increasingly complex customer requirements will be an ever-greater challenge in the very near future and, more than ever, should be fully integrated into every manufacturer’s strategy. A first step on the path towards a consumer-driven manufacturing approach is to digitally transform all relevant value chains in manufacturing in a way that enables increased agility and flexibility,” he emphasises.
“The traditional implementation pattern of digital transformation, ‘experimentation, failure, experimentation’, finds some barriers in the process industry due to the most severe safety risks which lead the management staff to be more conservative and reserved with the changes implementation, especially for those related to the substitution of human action in the process control,” observes Dr Marcio. According to him, this characteristic tends to enlarge the lifecycle of digital transformation projects in process industries. “In my point of view, digital transformation is advancing in the whole industry but the process industry requires a more detailed analysis, especially considering the growing pressure over these industries due to ESG policies, which demand even more concern from the industry players about their impact on the society,” he notes.
Pranav Thakkar, Associate Director, Industry X.0, KPMG in India, holds the view that while improved productivity, higher efficiency, increased cost savings, sustainability, and health and safety remain the key triggers for process industry to upgrade and invest in digital transformation journey, the drivers of digital disruption are expected to be end-to-end commercial optimisation, real-time plant adaptation to macro-economic hazards and deployment of AI/ML systems to optimise process control systems. “Additionally, the Covid-19 pandemic introduced a few more drivers as disruptions in supply chain and personnel availability forced the process industry to consider digital solutions like command control centers among others,” he adds.
“I feel the digital transformation for the process industry is far behind in terms of adoption and success as compared to discrete industrial manufacturing or consumer sector and financial banking sector. This is because the maximum benefit and exposure of digital technologies is seen by consumers as outlined in the previous reply,” says Shyam Warialani.
For Khurshed R Printer, the oil industry has never lagged in adapting to new technology in automation. It is the automation providers that take time to reach the oil industry standards of safety; and the standards of safety are way above any other process industry due to its hazardous environment. “The oil industry primarily looks for safety and reliability. An oil processing facility will have a mix of different automation systems like pneumatic, electric, and digital. The selection depends on the area of operation with safety being the prime criterion,” he says.
What is the role of availability and maturity of new technologies like cloud computing and AI/ML in making this topic attractive for continuous process industries? Which are the most attractive applications, the low-hanging fruit?
“Cloud Computing, Machine Learning and Artificial Intelligence are fast becoming important cogs in the wheels of enterprises. Using one's enterprise data effectively is only possible when you leverage these advanced technologies. It can help solve complex problems that allow businesses to scale operations quickly,” says Rajesh Nath. “Several digital transformation platforms use cloud computing and/or AI to offer a 360-degree view of members' needs based on their browsing history, EDM analysis, and click-through rates.”
To Dr Marcio, the availability and maturity of powerful technologies like AI and cloud computing is fundamental to the digital transformation, but it's alway important to remember that the real digital transformation is related to people, only a culture change is capable of promoting a real digital transformation in any industry. “The technologies will allow us to achieve the data, but the people will transform these data into information, knowledge, and finally in wisdom,” he opines.
“Technologies like Machine Learning are mature and thus easy to tap into with modern low-cost cloud infrastructure (pay-as-you-go). For example, computing the state of fouling equipment like heat exchangers (HeX) or forecasting Remaining Useful Life (RUL) for reactors or early detection of anomalies in equipment can be achieved using ML. Hence, we see asset performance management and operational efficiency as two major low-hanging fruits,” says Sushant Rabra.
According to Shyam Warialani, though the continuous process industry is more advanced in terms of automation, plant based web communications, etc., but in terms of digital maturity, e.g., use of new technologies like cloud computing, use of AI or ML in production process, it is very low. “The most attractive applications could be plant and machinery based AI. Transforming digitally and controlling productivity improvements through machine learning and data analytics; improving data communication between production and stockiest using non critical data by digital transformation, etc.,” he says.
“An offshore oil process platform is probably one of the best feats of human engineering,” says Khurshed R Printer, as the control room of these platforms could easily make a space launch centre look small in comparison. “The level of automation can only be imagined, as a single complex is connected to over 20 thousand plus sensors, valves, instrumented open and closed loop systems and often controlled by a single operator. In such a complex field AI and cloud computing would surely find its way once fool proof security is established,” he explains.
What would a ‘lights-out’ refinery or a pharma plant look like? Is it possible to meet all safety and other regulatory compliances in such a highly automated and autonomously operating factory?
“A ‘lights-out’ refinery or a pharma plant is designed to operate in an automated way. In a lab, for example, all the filling robots and all the quality control robots operate at the same time – the robotic arm, in the meanwhile, shuttles dozens of trays up and down the production floor, making sure that each capsule is filled with the right drugs in a certain time period. This process, with a non-fluctuating speed as opposed to human labour, does not mitigate the production process and yields a maximised output,” explains Rajesh Nath.
Taking a cautious approach, Dr Marcio, is of the view that we are not able to do this currently. “As quoted earlier, the operational risks of a crude oil refinery for example are very high to allow a totally autonomous operation, but I strongly believe that we can use the current technologies to help the operators and minimise the risk of human failures. The use of simulators has been increasingly applied to the operators training, especially in the critical scenarios of the process plants. I believe that the technology development will reach the autonomous operation of process plants in the future, but some questions need to be answered previously, mainly related to the cybersecurity issues,” he elaborates.
“With advent of process automation, safety levels have increased and the requirement of personnel as guardians and operators around machines has gone down. A 'lights-sparse' – rather than the futuristic 'lights-out' – refinery or pharma unit would be possible with numerous IIoT devices, automated machines, and AI driven robots or Intelligent Automation, along with advanced Manufacturing Operations Management (MOM) software. Stakeholders can remotely supervise operations and perform complementary actions, in case of alerts,” says Pranav Thakkar.
What benefits would an end-user consumer experience when large process plants adopt data technologies?
Speaking of the benefits of data technologies from end user perspective, Dr Marcio, says, “The end-user consumer can enjoy a more stable, reliable and safe production process which is translated into a more uniform supply chain with lower probability to deliver a failed product.”
“When large process plants adopt data technologies they can deliver, using enablers like customer analytics, a great customer experience; be it purchase or complaints, and low-cost, high-quality products delivered through an agile and efficient digital supply chain. Intangible benefits would include a low carbon-footprint product produced with high ESG standards achieved via digitalisation,” says Sushant Rabra.
“In case of large process plants the consumer doesn't buy products directly from the producer. There are several middle agencies probably taking care for products to reach the consumer's hand. However, using data analytics, the producer can gather a lot of data regarding consumption, usage, habits and geographical preferences of product, packing, cost, etc., and then adopt this in plant and production so that consumers will benefit,” says Shyam Warialani.
With his long experience in ONGC, Khurshed R Printer certainly knows the importance of data in the process industry. “Oil production is extremely capital intensive; hence data and key communication channels need to be fully protected. In most cases fully owned and dedicated channels are used by the field operator. Seismic data is the key to upstream oil production. This involves collection and storage of huge amounts of data. Deciphering the data is the key to establishing oil reserves. AI is in its infancy presently. There are signs of AI entering the automation field. It will take time to sort out the security and safety issues before large scale implementation in this area of oil production,” he cautions.
“Digital technology shall transform consumer habits. Mobile devices, apps, machine learning, automation and much more will allow customers to get what they want almost exactly at the moment they need it. What’s more, these new digital technologies will have caused a shift in customer expectations, resulting in a new kind of modern buyer,” explains Rajesh Nath. “Today's consumers are constantly connected, app-native, and aware of what they can do with technology. Because of the opportunities that rise from using modern technology, customers often rate organisations on their digital customer experience first,” he concludes.