Organisations can utilise simulation environments and pilot projects for employees to interact with autonomous systems in a controlled environment, says Dr Ravi Kumar G V V.

Industrial autonomy can play an important role in achieving an organisation's long-term goal for operational efficiency, cost reduction, and sustainability. According to Acatech’s Industrie 4.0 maturity index¹, the entire Industry 4.0 journey has been envisioned in 4 levels of maturity, viz., Visibility, Transparency, Predictability and Adaptability. The last stage of this maturity level, Adoptability, is a fully autonomous state with no human intervention. No organisation reached the state of adaptability and human needs to be there in the loop to take final call. However, industrial autonomy can be envisioned in stages from minimal to full autonomy. The real-time data obtained from systems and processes empowers organisations to make informed decisions that align with long-term strategic goals. Industrial autonomy can help organisations adapt quickly, scale and be competitive. Autonomy can help in reducing the risks by detecting issues before they escalate, protecting the organisation's reputation.

Some of the details on how industrial autonomy can help in organisations long term goals are given below:

Operational efficiency

·         Systems equipped with advanced sensors can monitor operations continuously and adjust processes in real time, ensuring optimal throughput and minimal downtime. It can improve the overall quality of the end products by adjusting and fine tuning the process parameters real time.

·         Data collected from various components and subsystems of machines can be used to monitor the health of the critical equipment and machines on the shop floor continuously. It can forecast equipment failures and schedule maintenance proactively, reducing unplanned outages and increasing asset utilisation. It can help in reducing the maintenance cost of the equipment and can assess the remaining useful life of the equipment.

·         Industrial autonomy can automate repetitive tasks and integrated control systems minimising human errors, speeds up production processes, and frees up humans for more value added and strategic work.

Cost reduction

·         Industrial autonomy minimises the need for manual intervention, thereby cutting labour costs and lowering the risk of human-induced errors.

·         Smart energy management systems can automatically adjust production processes to reduce energy consumption, leading to significant utility savings.

·         Through better data analytics, autonomous systems help optimise the use of raw materials, reduce waste, and enhance supply chain management, all contributing to lower operational costs.

·         Autonomous systems can monitor the safety aspects of people in the shop floor continuously reducing their exposure to hazardous and dangerous environments. This helps in reducing the incidents and accidents in the shop floor there by improving the quality of life of workers. This will help in reducing the costs related to non-compliance and non-adherence.

Sustainability

·         Autonomous systems can optimise energy usage and reduce waste, directly contributing to lower greenhouse gas emissions and a smaller carbon footprint.

·         Industrial autonomy facilitates the integration of renewable energy sources, enabling facilities to adjust operations based on renewable energy availability and reduce reliance on fossil fuels.

·         Automated systems can precisely control processes to minimise overuse of resources, promote recycling, and implement circular economy principles, thereby supporting long-term environmental sustainability.

Governance frameworks and safeguards

Organisations must establish cross functional governance mechanisms like steering committees and regular review policies. The steering committees should encompass experts in AI, cybersecurity, operations, ethics, and legal to oversee the autonomous systems lifecycle. This steering committee should regularly review and help in updating policies and procedures to keep pace with technological advances and evolving regulatory landscapes.

Robust governance and safeguards should be implemented for ensuring that autonomous systems operate reliably, securely, and ethically. Some of the standards that need to be adhered to and implemented are IEC 61508 (functional safety)and ISO/IEC 27001 (information security management), IEC 62443 to protect against cyber threats.

Organisations should conduct comprehensive risk assessments for hazards, Failure Modes and Effects Analysis (FMEA) to identify and mitigate potential risks. Further, organisations should define and implement SILs to ensure that systems meet required safety standards under various operational scenarios. Organisations should establish and regularly update incident response and recovery plans for both safety and cybersecurity events.

Organisations must institutionalise ethical oversight and transparency practices. These should cover fairness, accountability, transparency, and non-discrimination. All autonomous decisions should be explained through audit trails and logs, enabling post-incident analysis and accountability.

Data governance and integrity is critical. Organisations should establish protocols for data collection, storage, and analysis that ensure data integrity, quality, and compliance with privacy regulations. Also, should implement strict access controls and encryption to protect sensitive operational data.

Organisations must ensure appropriate human oversight in critical decision points, ensuring that autonomous systems have well-defined escalation procedures. All the control mechanisms should be put in place to include fail-safe modes, emergency shutdown protocols, and manual override capabilities to mitigate unforeseen system behaviors.

Human-autonomy collaboration

Organisations must institutionalise change management processes and empower workforce to adapt to industrial autonomy. This involves many things that includes training, culture change, and organisational support.  Some of these are elaborated in the following paragraphs.

Organisations should embark on comprehensive training and upskilling. This includes focused training on both technical skills and soft skills. Encourage and enable the workforce to take up certification courses, workshops, and online learning on emerging technologies and autonomous systems. Organisations can utilise simulation environments and pilot projects for employees to interact with autonomous systems in a controlled environment. Enable employees to work across different functions like operations, quality, maintenance to understand various facets of industrial autonomy, fostering a broader capability. Organisations must identify and train internal champions who can mentor colleagues, ensuring a smooth knowledge transfer and building a community of practice around industrial autonomy. Promote team-based projects that involve both technical experts and frontline workers, fostering a collaborative environment where diverse perspectives drive innovation.

Organisations must develop processes for efficiency and effective collaboration between humans and machines. This includes implementation of systems and processes where human oversight remains integral to decision-making, thereby reinforcing the importance of human judgment alongside automation. Also create avenues for employees to provide feedback on system performance and usability, ensuring continuous improvement and engagement.

Organisations must develop strong Change Management and Cultural Shift practices. Regularly update employees on how autonomous systems impact operations, emphasizing that technology is there to amplify their strengths rather than replace them.

Organisations must establish platforms or innovation labs where employees can experiment with autonomous technologies, propose improvements, and drive process innovation. Recognise and reward employees who take initiative in adapting to new systems and contribute to process enhancements.

References

1. Günther S., Reiner A., Jürgen G., Michael T. H., Wolfgang W., Industrie 4.0 Maturity Index - Managing the Digital Transformation of Companies, acatech Study, 2017

Dr Ravi Kumar G V V is Vice President and Head Advanced Engineering Group and Unit Technology Officer of Engineering Services, Infosys. He has over 28 years of experience in leading innovation and applied research projects and working with industry in scaled implementation. His areas of expertise include Aircraft structures and systems, knowledge-based engineering, composites, artificial intelligence, robotics, autonomous systems, AR, VR, and Industry 4.0.

Dr Ravi has led the development of commercial products such as AUTOLAY, Nia Knowledge, and KRTI 4.0. He played a key role in the development of Industry 4.0 maturity index under the umbrella of Acatech, Germany and has since contributed to Industry 4.0 implementations across industries, such as manufacturing, mining, and utilities. He is engaged in the design and development of advanced robotics and autonomous systems, including the development of India’s first autonomous buggy. Dr Ravi is also leading many AI and GenAI initiatives across industry verticals like Aerospace, Automotive, Heavy Engineering and Utilities. Involved in many sustainability initiatives which include design and development of solar monitoring application, solar inverter predictive maintenance application and solar panel cleaning robot.

Dr Ravi is a member of the HM-1 and past chair of G-31 technical committee of SAE International contributed to many aerospace standards development. He has published more than sixty technical papers, 5 granted patents and a book.  

Dr Ravi has a Ph.D and Master of Technology(MTech) in Applied Mechanics from IIT Delhi, and a BE(Honors) from BITS Pilani, India. He has been recognised for his contribution in engineering research and advanced technology development with many awards including James M Crawford Executive Standards Committee outstanding achievement award from SAE International, Roll of Honor award from SAEINDIA and Corporate Excellence Award from American Society of Engineers of Indian Origin.