Trends in Process Automation
Published on : Sunday 06-12-2020
Ravi Ramarao dwells on how the rapid pace of technology disruptions is having a telling impact on the decision makers.
When you think of process automation, one can quickly associate PLCs/SCADAs and then DCS. Interestingly and for the larger good, the past decade has seen a sustainable change from the conventional frontiers of proprietary hardware and software that used to define the process automation and steadily given way to open systems and standards. Who moved the needle of change?
The change is made possible primarily due to the convergence of internet, mobility, availability of sensors at an affordable price combined with the ease of network connectivity.
In fact, the way forward is going to be even more exciting and into an era loaded with enormous possibilities using the magical power of Sensors, Software and Solutions on platform, and I believe it is going to continue for a longer time, for sure. The journey has just started, it is just the tip of the iceberg.
Well, furthering on quantification of the myriad of technologies and systems, if to be prioritised, the following shall be the pick of the stack:
1. Cyber Physical Systems (CPS), Digital Twins, Augmented Reality and Virtual Reality (AR/VR)
2. Machine Learning (ML), Collaborative Robots and Artificial Intelligence
3. Environment, Health & Safety (EHS) – Bio Chips and bio health monitoring, and
4. Cybersecurity – The vital backbone.
None of them are buzzwords any longer. These are not new and prevalent in the market for quite some time. In a real life scenario, some of them already are hot current trends and quite a few as definite possibilities of the future in the industries. However, in an industrial context, the adoption level varies through a wider spectrum.
In my assessment, all of these shall gain momentum and become the basic hygiene in the near future across the industrial segments.
1. CPS, Digital Twins, AR & VR
Cyber Physical Systems or CPS are smart networked systems with embedded sensors, processors and actuators that are designed to sense and interact with the physical world (including the human users), and support real-time, guaranteed performance in safety-critical applications. CPS are characterised by the transfer of physical components into virtual space.
In CPS systems, the joint behaviour of the ‘cyber’ and ‘physical’ elements of the system is critical-computing, control, sensing and networking can be deeply integrated into every component, and the actions of components and systems must be safe and interoperable
A classic example for a CPS is a ‘digital twin’ that represents a virtual image of a process or a machine.
The extent to which the digitisation of the real components is realised is application-related. The twin does not necessarily have to be linked to real data. This means that the definition of the twin is the same throughout the entire value chain, which is illustrated in the phase model diagram:
By combining the different sections you get different products of digital twins like AR/VR, Real-time simulation, etc. Typically, digital twins have great potential in maintenance and service of equipment. This offers new control options to minimise risks and to enhance efficiency.
AR means that computer-generated information is integrated into the user's perception of the environment. Today, AR is mainly realised by augmentation of the real world with virtual elements, such as visual information using AR glasses, smartphones or tablets. In the future, AR will have a transformational impact on human kind. The augmentation of human mind and human perception with digital tools will lead to:
Intelligence Amplifiers: Providing users with all kinds of data (real-time, fitting to situation), translation of languages, etc.
Super-Senses: Information from sensors will augment the existing natural senses of people.
Natural language understanding (NLU) is a branch of artificial intelligence that uses computer software to understand input/content made in text or speech format – a sub-discipline of Natural Language Processing (NLP).
Target: Building of a machine that understands language (handling of mispronunciations, swapped words, contractions, colloquialisms, understanding of context and sentiments). For this purpose, methods such as Machine Learning are employed. NLU/NLP could be used for the analysis of language based information, e.g., search for specific information, or automatic language translation. (Further Link – 1Google Duplex demo from Google I/O 2018: www.youtube.com/watch?v=D5VN56jQMWM)
Virtual Reality (VR) is already established in several fields and offers many opportunities. With the expected technological progress VR will further mature, e.g., realistic virtual worlds which are indistinguishable from reality are likely.
2. ML, Collaborative Robots & AI
Machine Learning grew out of the quest for Artificial Intelligence. It’s the subfield of computer science that gives computers the ability to learn without being explicitly programmed, using algorithms that can learn from and make predictions on data. ML is employed in a range of computing tasks where designing and programming explicit algorithms is unfeasible, e.g., open context systems, physical models are not available. ML is an enabler for intelligent products and services in all business sectors. Computing systems based on ML already outperformed humans in specific tasks, e.g., object recognition, natural language understanding, and speech translation.
Collaborative Robots: Beside connected computers in the form of personal intelligent assistants also robots are on their way to appear everywhere. According to Boston Consulting (06.2017) the global spending on robots projected to hit USD87bn in 2025. They had to revise their original projection from 2014 which was USD67bn for military, industrial, commercial, and consumer applications. Important technological breakthroughs as drivers for the rise of the robots are, e.g., Robotics, Artificial Intelligence and Machine Learning, Computer Vision, Collaborative Autonomy and Rechargeable Batteries. We are on a tipping point in the history of technology where machines can fulfil tasks autonomously even in complex human environments (open context systems). Also they can react and interact with people naturally and intuitive through gestures, emotions, and natural language.
Artificial Intelligence and Robotics Computers are performing new cognitive tasks in which humans have been superior because of evolutionary brain improvements over a long period of time, e.g., algorithms learning from data instead programming of rules, natural language understanding or object recognition. This progress will push robotics in all domains. We will further automate all kinds of tasks and continuously enter the era of ubiquitous robotics: Progress in analogy to the development of computers from mainframe systems to today's computers.
Human-like Machines and Virtual Worlds in the future, the objects around us are connected, intelligent, and autonomous. They communicate with people, react to their emotions, and also know their preferences. Machines are more human-like. Increasingly, we will stay in virtual worlds not distinguishable from the real world, experiencing, e.g., new situations, places, and people. This will broaden our horizons. Both will likely influence our human identities.
3. Biochips & Biosensors for Environment, Health & Safety (EHS) Monitoring
A biosensor is an analytical device used for the detection of an analyte that combines a biological component with a physicochemical detector. In the future disposable biochips and biosensors could be used routinely for various purposes. Important driving forces for the technology development are printed electronics, lap-on-a-chip systems, organic-thin-film transistors and carbon based nanomaterials. Such inexpensive printed biosensors could also be used to analyse the personal health in hazardous industrial environments. (Further Link Wikipedia: https://en.wikipedia.org/wiki/Biosensor).
Our society today is massively dependent on the functioning of its technological infrastructure. Traffic, energy, communication and data infrastructures are inextricably linked. Modern societies are increasingly vulnerable at this point. An attack on the Internet as a central control system would have catastrophic impact. We can monitor massive shifts in cyber-attacks and espionage over the last 20 years from simple viruses written by hobbyist hackers to very complex attacks launched by criminals and nation-states. However, even hacks on a much lower scale could create massive damage. The remote car hack of the Jeep infotainment system forced Chrysler to recall 1.4m cars to bug fix in 2015.
Therefore, cybersecurity must be realised on all levels by diverse measures and technologies, e.g., access points, connected devices, data centres, and communication networks.
In summary, one is left to wonder, with so many proven solutions around, then, why there is no visible ‘sweeping wave of change’ happening across the industries. When you deeply look into this and in interaction with owners/operators, end users and so on, a striking thing that emerges is the fact that there is a genuine challenge for the practitioners ‘to define the problem statement’.
So what problem am I trying to address?
Secondly, there are so many old/legacy systems, how to address them?
Thirdly, the rapid pace of technology disruptions is having a telling impact on the decision makers and age old defence mechanisms advise 'caution' and 'go slow' approach.
Well, all that starts also needs to get converted into a decisive progress journey, so we are in the cusp of this process and I am optimistic, the forthcoming years shall accelerate the adoption process and we can see that in action. Great engineering years ahead. Ciao!
Ravi Ramarao is International Business Leader with 29+ years of overall experience in Connected Manufacturing – Digital/IoT/Enterprise wide E2E Supply Chain Consultancy to Fortune 10/50/100 industrial manufacturing clients and large global program management. Among accolades, more recently, a special assignment as India National Expert for MSME – I4.0 Solutions, and has worked for Asian Productivity Organisation, Japan under the auspices of NPC, India.
Ravi is presently Chief Architect – Industrie 4.0/IIoT/Smart Mfg Platform Solutions at Robert Bosch Engineering and Business Solutions Pvt Ltd, handling technology, solutions and business models for Smart/IIoT embedded digital manufacturing; and co-creation and building strong partner ecosystem using multiple technology and unified platform: 1. E2E Digital Supply Chain; and 2. Domain Driven – Technology enabled inter operable systems.
Prior to this, Ravi was a Business Leader – Manufacturing IT & Plant Solutions @ Tata Consultancy Services during 2005-2015; and in Manufacturing – Design, Engineering, Build and Operate in Petrochemicals, Oil & Gas industries during 1991-2005. Ravi believes Sensors, Software Solutions and Platform…is the way forward. Smart Manufacturing, Data Science, Algorithms and Predictive Analytics are the areas to invest – the life lines to remain in the market.