Autonomation can reduce human interference, prevent errors, and improve the quality of products, says PV Sivaram.

How can industrial autonomy align with an organisation's  long-term goals for operational efficiency, cost reduction, and sustainability?

The purpose of a manufacturing organisation is to provide maximum benefit to its stakeholders. Stakeholders are the equity partners, the employees, the customers, the vendors, public at large, the government and the environment. Operational efficiency is the key to cost reduction and sustainability.

As a part of strategic vision, a scheme must be in place to set targets and to monitor progress towards set targets. To monitor progress the relevant parameters should be measured continuously.

To continuously acquire data is one part; the second part is to derive corrective action. These two parts are very much in common practice. It is possible to move the industrial control process to the next stage of evolution – to move from prescription to implementation.

Data Analytics comes in various capabilities. First basic level is Descriptive Analytics. This level provides answers to the questions of what, and where. The second level goes deeper, and provides answers to the question why. Here come the techniques like root-cause analysis and so on. The third and higher level is predictive analysis, whereby we get answers to the question of what comes next. It is clear that armed with the assistance of the three levels of data analytics, human operators can take decisions early and effectively.

Now comes the level of Industrial Autonomy. At this level, the system uses the predictions and derives prescriptions to improve performance. Prescriptive analytics is the fourth level. At the apex is the action itself. Autonomous systems can take decisions and implement the same. This provides the highest speed of response.

Risk management

What governance frameworks and safeguards should be implemented to ensure autonomous systems operate reliably, securely, and ethically in critical industrial processes?

From the previous discussion, we can see that autonomous systems perform actions whose main goal is to bring the process trajectory on to the optimal path in the quickest manner. But there are other issues in play. In particular, these are issues of safety and security and points of ethics. We have a dilemma – to provide high speed of decision making and high accuracy we want to reduce human intervention. On the other hand, to deal with ‘soft’ issues, we would like to have humans in the loop. So we need some guard rails to the decisions. The system programming should be prevented from taking actions which are potentially dangerous and violative of individual safety and freedom. The three laws of Asimov for robotics are applicable here in a suitably modified manner.

Human-autonomy collaboration

How can we empower our workforce to adapt to industrial autonomy, ensuring they have the necessary skills to supervise, intervene, and innovate alongside these systems?

Even at the best, autonomous systems are a co-pilot. Never is the automaton fully in-charge of the process, it is always subordinate to the human pilot. Hence we have two needs here – training for the operator, and a hierarchical set of permissions to take decisions. The hierarchy gets set by competence and wisdom at increasing levels.

· Automation: A system that follows predetermined instructions, requiring human oversight for any deviations. Automation can produce parts faster, but it can also cause defects. 

· Autonomation: A self-reliant work system that can detect and correct errors without direct human control. Autonomation can reduce human interference, prevent errors, and improve the quality of products. 

PV Sivaram, Evangelist for Digital Transformation and Industrial Automation, is mentor and member of steering committee at C4i4. He retired as the Non-Executive Chairman of B&R Industrial Automation and earlier the Managing Director. A member of the Board of Governors for Automation Expo 2024, he is a past President of the Automation Industries Association (AIA). After his graduation in Electronics Engineering from IIT-Madras in 1976, Sivaram began his career at BARC. He shifted to Siemens Ltd and has considerable experience in Distributed Systems, SCADA, DCS, and microcontroller applications.

Sivaram believes strongly that digitalisation and adoption of the technology and practices of Industry 4.0 is essential for MSME of India. He works to bring these concepts clearer to the people for whom it is important. He believes SAMARTH UDYOG is nearer to the needs of India, and we must strike our own path to Digital Transformation. Foremost task ahead is to prepare people for living in a digital world. He is convinced that the new technologies need to be explored and driven into shop floor applications by young people. We need a set of people to work as Digital Champions in every organisation.