Digital Twins are becoming increasingly important in the process industry
Published on : Tuesday 07-12-2021
Prasad Kulkarni, Assistant Manager, Marketing Department – e-F@ctory Solutions, Mitsubishi Electric India.
Is the process industry slower in adopting digital transformation compared to discrete manufacturing?
It has been observed that process industry is slower in adopting digital transformation compared to discrete manufacturing in recent years. However, the use of heavily automated production, as well as centralised control and data collection dates back to the 1960s. Process industry is the early adopter of ISA-95 standard, which is needed to ensure consistent terminology and operation models. With ISA-95, most process industry facilities achieve a nearly fully automated production process, where assets are connected to a central control system [e.g., distributed control systems (DCSs) and supervisory control and data acquisition (SCADA)] and historians/manufacturing execution systems (MESs) are often deployed.
Conforming to ISA-95 is certainly an advantage for the process industry. It is true that most of the initial use cases for Industry 4.0 and the hype around Internet of Things (IoT) was observed in discrete manufacturing such as automotive. However, one cannot overlook at the high connectivity and advanced real-time process optimisation that is already present in the process industry.
With Big Data and analytics in the IIoT era, is the traditional Data Historian becoming history? Is this a smooth transition?
Certainly, the emergence of Big Data and IIoT have blurred the role of the historian, but with the corresponding growth in the volume of process data, Data Historian is likely to continue to play a major role.
Recent advancement and technology adoption has evolved and improved the process historians in more sophisticated way. Methods such as data compression enabled ever larger amounts of information to be collected. Supported data types have expanded to include complex data types. Finally, the continuous advancement in computing performance has vastly increased both the volume and resolution of data collected. In larger facilities, it is common to collect tens of thousands of data elements, with scan frequencies as high as a thousand times per second. Today’s data historians can collect derived and calculated information, contextualise, and store data to provide workers with timely insights on easy-to-understand digital dashboards. With every advance in the quantity, quality and range of data that can be collected, new potential applications come to mind. These include applications that combine operational data with geo-data, weather data, financial data, and so on. While process data may have traditionally been only of interest to operations and maintenance personnel, these new applications have attracted the attention of users from across the enterprise.
Considering all of the above, it is not unreasonable to consider the collection and use of historical process data to be an example of Big Data that existed long before this term came into common use.
However, we feel that still there are areas where Data Historian can bring advancement in order to handle variety of data types – structured, unstructured and semi-structured. If data historian vendors want to avoid disruption, expand the user base, and deliver on the promise of IIoT use cases, solutions must bring together all three types of data into a single environment that can drive next-generation applications that span the value chain.
How effective is a digital twin in process automation vis-à-vis discrete manufacturing? Is the process industry making use of digital twin technology?
Industry 4.0 is rapidly changing numerous industry sectors and enabling new business models due to machine learning (ML) and artificial intelligence (AI), the Industrial Internet of Things (IIoT), data analysis techniques, and the latest developments in information and communication technologies. One of the technologies under the Industry 4.0 is digital twins (DTs).
The DT concept builds on traditional simulation techniques and continued to evolve and performs real-time simulations. The process industry is one of the early adopters of Digital Twin as it covers a wide range of complex manufacturing processes, from continuous facilities in the petrochemical industry to large-batch manufacturing in the glass and steel industries to small-batch manufacturing in the pharmaceutical and food industries.
Digital Twins are becoming increasingly important in the process industry and has realised significant benefits recently. Digital Twins in process industry enable process improvements through advanced data analytics and operational insight with collected data, informed decision making and ensure actual performance meets planned performance.
Is the number and complexity of standards presenting challenges for both end users and suppliers?
Certainly, the number and complexity of standards presenting challenges for both end users and suppliers. However, in the context of digital transformation, the timely and harmonised adoption of standards can play a pivotal role in shaping the digital transformation process, complementing regulations and contributing to digital transformation governance. It also ensures the successful scale-up of solutions to be implemented globally.
Standards can facilitate the ongoing digitalisation of industry by enhancing productivity and efficiency, promoting compatibility and interoperability between products and processes through common language, while minimising risk, improving safety, and supporting policy and legislation. Furthermore, standards can serve as accelerators of change as they promote innovation and the uptake of new digital technologies and spread knowledge through codification.
Good governance principles are necessary for guiding the development of standards in the digital technology landscape to ensure that the technologies remain human-centred and aligned to the goals of sustainability.
What is the present status of Open Process Automation and the move toward standards-based, open, secure, and interoperable process automation architectures?
Process Industry is adopting Open Process Automation very rapidly and Mitsubishi Electric is ready with standard-based, open, secure and interoperable process automation architecture. Mitsubishi Electric’s MELSEC iQ-R Series process CPU/redundant systems are ideal for various industrial process control applications requiring highly reliable process control solutions that can be easily integrated. Most components are based on the standard range of MELSEC iQ-R Series modules, enabling total cost of ownership to be reduced through utilisation of its extensive functions and features. Its extensive PID instructions that are embedded in the CPU can be used for maintaining stringent process parameters.
MELSEC iQ-R Series enables leading edge capabilities through its OPC UA Server and MES Interface module that connects to multiple OPC UA client and ODBC compliant databases such MS SQL, MS Access, MySQL, Postgres etc. respectively. These advanced features allow integration of field data to business systems. The specialised CPU inherits its high performance from the MELSEC iQ-R Series when used together with the centralised programming suite GX Works3 and iQ Works. The process control system incorporates a dedicated process instruction set (such as two-degree-of-freedom PID, sample PI, and auto-tuning), realising algorithmic PID and highly reliable features such as being able to interchange (hot-swap) I/O modules while the system is still online and large-scale process control with a maximum of 300 loops, closely bringing it in line with DCS capabilities without the financial burden.
There have been serious cyberattacks on process industries in recent months. How strong are the safeguards?
It is unfortunate that there have been cyberattacks on process industries in recent months. No industrial operation is free of risk, and different industrial enterprises may legitimately have different “appetites” for certain types of risks. Evaluating cyber risk in industrial control system (ICS) networks is difficult, considering their complex nature. Individual business needs to assess potential cyber threats to their own industrial sites across a wide range of circumstances, consequences and sophistication. A security program/posture can only be evaluated if we have a clear understanding of the kinds of attacks that might target the protected industrial site. Today, the technique for evaluating the risk of cyber-sabotage of industrial processes is highly developed.
Mitsubishi Electric has developed new cyber-attack detection technology that can classify computer virus behaviour into about 50 different patterns. Although hackers use vast amount of viruses for cyber-attacks, the number of the hackers activities monitored though network communication logs. By using correlation analysis to determine whether a particular sequence of activities follows the scenario or not, the technology is able to distinguish between legitimate activities that follow similar patterns and actual cyber-attacks. It is the solution for sophisticated cyber-attacks.
Prasad Kulkarni holds Bachelors in Electronics and Masters in Instrumentation from Pune University. His professional experience spans close to 10 years in Automation Industry. He started his career as Sales Engineer and developed good understanding of ISA-95 framework and layers that covers Field Instrumentation, Automation Systems (PLC/SCADA/Historian), IT-OT Integration, MES & IIoT. Prasad also established Industrial Automation implementation credentials for Smart Manufacturing with good understanding of IIoT communication protocols like OPC UA, MQTT, MTConnect and other Industrial Communication protocols of OT Systems.
In this role he is responsible for promotion, partner development and sales support for e-F@ctory Solutions (Industry 4.0 / Digital Manufacturing) in various industries like Automotive, Pharmaceuticals, Food & Beverages, etc., on Pan India Level. He also contributes in pre-sales activities that interprets and translates client requirements into a technology solution that can be configured from a standard set of offerings.