The Many Avatars of Automation
Published by : Industrial Automation
Sreeja Gadhiraju presents an overview of the different types of automation in the modern world.
Your alarm has been set to 6 AM, have a good night!
Lights off, door lock, navigation to work!
Though it feels like a sci-fi movie, this is almost happening right now. How? The answer is automation.
What is Automation?
Reduce the human effort to minimum and there we go; we have automated the process. This could be with the help of technology, programs, robotics or processes.
Over the past centuries, starting from the Industrial Revolution in Europe, automation has been the primary area of research for most of the researchers across the world. After all, automation reduces human intervention and increases efficiency. Temperature regulators, pressure regulators and speed controls are amongst first inventions in automation.
The 20th century has been a breakthrough for automation. The first and second World Wars witnessed major advancements in the field of mass communications and signal processing. Starting in 1958, various systems based on solid-state digital logic modules for hard-wired programmed logic controllers (the predecessors of programmable logic controllers or PLCs) emerged to replace electro-mechanical relay logic in industrial control systems for process control and automation, including early Telefunken/AEG Logistat, Siemens Simatic, etc.
Process automation is the use of technology to execute recurring tasks or processes in a business where manual effort can be replaced. It is done to minimise costs, increase efficiency, and streamline processes. This typically includes the usage of PLCs, sensors, robots and motors and many other things. Like any other automations it helps us with less errors.
How does Automation work?
Each industrial automation system works almost in the same way. It has to be started by some sort of input, which could be a sensor, pushbutton, switch, etc. Typically, a person will start the process by using the mentioned device or it could be a direct input to the sensors. Those inputs will go to a PLC and then to make the decisions based on how it is programmed. The PLC will then activate whatever output the program says to run. The output can be anything from a light to a motor. In an automated process output will typically be the input for the PLC and combined with other input devices or programming, to keep the process running. This entire process generally works like a chain reaction with one output device starting before the next is allowed to run. This is also called sequential starting.
Automation has to have many aspects working together in order to function properly. An automated process will continue the process until it stops receiving signal. The signal might be a physical input or something which was programmed. Generally, process automation is mostly controlled by computers and sensors with a very little human intervention. Industrial robots are a great example of process automation.
The Automation Pyramid is a pictorial representation of the different levels of automation in a factory. It’s a great way to make sense of the entire complexity in a factory.
Robotic process automation
Robotic Process Automation is the technology that allows anyone today to configure computer software, or a ‘robot’ to emulate and integrate the actions of a human interacting within digital systems to execute a business process. RPA robots (also called bots) utilise the user interface to capture data and manipulate applications just like humans do. They interpret, trigger responses and communicate with other systems in order to perform on a vast variety of repetitive tasks. Only substantially better – an RPA software robot never sleeps and makes zero mistakes.
Intelligence Process Automation
In 2018, Cognilytica released a report on the Intelligent Process Automation (IPA) market. Cognlytica’s report identifies four categories of Cognitive Automation, with increasing levels of cognitive ability:
Level 0: Enhanced RPA (not AI)
Level 1: Language & Context Aware
Level 2: Intelligent Process Awareness
Level 3: Autonomous Process Optimisation.
Why is Robotic Process Automation Not Enough?
Into this space of aggregating, managing, and manipulating data from a wide variety of sources is emerging a new class of automated ‘machine’: Robotic Process Automation (RPA) tools. These robots act on behalf of, or in place of, their human counterparts to interact with existing, legacy systems in the enterprise or anywhere online. They mimic the behaviour of humans so that the human can focus on more important tasks for the company, rather than say, copying information from a website into a spreadsheet.
Yet, while RPA is making significant improvements into company’s operations by replacing rote human activity with automated tasks, Artificial Intelligence (AI) is poised to give this new engine of productivity a gigantic boost. RPA tools get stuck when judgement is needed on what, how, and when to use certain information in certain contexts. What if systems can learn from its human supervisors about how to utilise that information? Systems that leverage machine learning (ML) to dynamically adapt to new information and data will shift these systems from mere robots that automate processes to Intelligent Process Automation (IPA) tools that can significantly impact the face of the knowledge worker economy. Or as McKinsey Consulting puts it, “In essence, IPA takes the robot out of the human.”
Intelligent Process Automation: The next step
Intelligent systems can work to build and maintain a more complete profile of a customer, patient, employee, partner, consumer, or other individual and company and use this knowledge to help fill gaps in information received by different sources. In this way, intelligent process automation systems can help eliminate many of the exceptions that require human handling of RPA systems.
How Intelligent Process Automation differs from Robotic Process Automation?
Although many people think that RPA and IPA are both the same thing, it is not so in the real-life. It is no doubt that RPA and IPA are both the robust tools of the automation industry, they both actually differ in the way they work and in the way they benefit the global industries.
IPA is something beyond RPA that further enhances the business processes in an efficient way. It uses smart automation techniques and core AI capabilities to learn about human perceptions and on how to utilise the correct information in times. So, by looking at definitions, one could clearly differentiate between RPA and IPA seamlessly. Furthermore, as we pointed out in the point mentioned above that IPA uses some advanced AI capabilities to learn from its users, let us learn what all AI techniques it uses.
The Industrial Automation trends making waves in manufacturing
The shift towards digital transformation in industry has already taken place. Manufacturers have increasingly been encouraged to invest in new technologies, with automation as a key technological driver. 2019 saw the trial of the first 5G smart factory in the UK, but what will 2021 have in store? As we look ahead to a new decade, Stefan Reuther, our Chief Sales Officer, gives three predictions for industrial automation in 2021 and explains why 2021 will be the better 2020 in automation.
The automation of manufacturing processes is at a turning point. Since the advent of the programmable logic controller (PLC), a number of automation islands have evolved that automate isolated steps in the manufacturing process. For example, a six-axis robot can stack and palletise products in a factory, but a manufacturer would need to invest in several different types of automation to fully automate its production line. This process-specific approach can result in some increases to operational efficiency. However, this does not provide a comprehensive, integrated view of manufacturing and thus doesn’t harness all the benefits of a complete automation system. While its years since the emergence of the term Industry 4.0, we’re not quite ready to leave the buzzword in its founding decade.
It would not quite seem impossible to have a completely automated world in a couple of decades. The combination of artificial intelligence, digitalisation and additive manufacturing could make this possible.
Who would have believed a world of palm sized devices, replaceable body parts and man-made intelligent machines if they had heard about it few decades earlier?
Sreeja Gadhiraju is a young engineer pursuing Masters in Mechatronics in Germany. A former team lead in Amazon, for Sreeja the craving to know and study latest technologies is an addiction. Presently studying Robotics, Modelling and Simulation, Cyber Physical Systems, etc., she has fallen in love with additive manufacturing. “There is so much to know, there are so many things which can do using this amazing technology. I want to finish my masters and proceed further towards PhD in Additive Manufacturing,” says Sreeja.