Choosing the right partner who will walk you through the journey of Automation & digital Transformation is important, says Rajalakshmi Hegde.

A word used very often in today's digital transformation world is ‘AI’ or industrial AI. Adopting AI in industrial applications is changing the landscape of manufacturing. For example, AI algorithms analyse data from sensors to predict equipment failures, minimise downtime, optimise maintenance schedules, extend the lifespan of equipment, and much more – driving agility and data-driven decisions. Industrial AI is, therefore, transforming how real-world scenarios are simulated, enabling predictive maintenance, optimising scheduling, and enhancing productivity and throughput across many use cases.

IT-OT integrations and the application of AI/ML models bring greater visibility and analytics through self-service analytics, a business intelligence technology that helps key stakeholders view, evaluate, and analyse data.

·         Real-time data control and monitoring over 5G networks ensure high-speed connectivity to shop floors.

·         The Industrial Edge, which connects the physical and digital worlds, provides computing power at the shop-floor level while pushing only essential and required data to the cloud for further analytics. Real-time monitoring and control are key, and industrial edge devices are perfect enablers for manufacturing and other industries.

·         Industrial Cybersecurity at the OT Layer is a fast-growing domain in manufacturing shop floors. As the IT/OT world converges, industrial infrastructure becomes more vulnerable to cyberthreats.

·         Digital Twins: This technology allows for simulations, optimisation, and real-time monitoring. Imagine testing different production scenarios in a virtual environment before building a physical machine or executing a process.

Other key areas include Industrial Robotics, Additive Manufacturing, Machine Health and Safety, and Smart Industrial Sensors.

In my opinion, the above technology trends are game changers in the world of automation plus the digital transformation journey. Connected is the key here – whether it’s machines, workforce, assets, humans, or robots.

Intelligent sensors, wearables, IoT devices, gateways, networks (4G, 5G, mesh), and industrial edge devices enable connectivity from sensor to cloud. Streaming data from shop floors and factory environments allows for real-time monitoring, analysis, and optimisation of factory operations. Legacy systems are becoming smarter by adding intelligent devices. The systems that once worked in silos now communicate seamlessly, fostering enhanced collaboration. Increased collaboration leads to agility in problem-solving and improved efficiency.

Enabling intelligent and focused dashboards via remote monitoring devices, mobiles, tablets, or control panels accelerates decision-making and allows critical operations to be overseen from anywhere in the world. Vision systems help inspect quality on high-speed lines with greater accuracy, reducing wastage and ensuring quality.

·         Collaborative robots (cobots) work alongside humans, assisting with tasks and improving worker safety.

·         Optimising processes using machine learning algorithms helps identify bottlenecks, improve workflows, and enhance efficiency.

·         Automated guided vehicles facilitate material movement based on work order execution, enabling just-in-time material availability for production.

·         Operator training and SOPs have evolved to include the industrial metaverse, providing immersive training experiences for workers and helping them learn new skills while enhancing safety standards.

These trends are gradually shifting operations to be smarter, more connected, and more agile. Embracing technology can unlock new levels of productivity, efficiency, innovation, and competitiveness in the manufacturing landscape.

When connecting to sensors and machines, a factor is to reduce latency and respond faster, this would be a game changer in real time decision making. By processing data locally on the edge devices, analysing information and making decisions can be done in real time without relying on slow connections to the cloud. This forms a crucial area in improving quality, correcting defects or adjusting the parameters to get your golden batch/product.

Edge computing is the shifting of the thought process of manufacturers, thereby collecting the right amount of data, processing it locally, forming key metrics to enable quick actions on production needs, hence creating smoother workflows.

Processing data locally on edge devices minimises the amount of sensitive information that needs to be transmitted to the cloud reducing the risk of data breaches and improving privacy.

Computing on the edge in real time to predict failures and optimise maintenance schedules, minimum downtime and maximum productivity.

Real time analytics helps with process optimisation, automated quality control with vision systems enabled edge devices. Further improving flexibility and scalability of factory deployments where new devices can be easily adopted in the future.

Few examples as seen in factories today are smart sensors, edge gateways, AI - powered cameras, autonomous mobile robots, etc., leading to smarter, more connected factories.

Legacy systems need additional sensorisation, automation and OT infrastructure to enable data to edge devices. Moreover, common data transfer protocols like MQTT help. Prioritising critical legal systems from a business standpoint and modernising them is an important step. Encapsulating the legacy system to expose functionality via application programming interfaces without interfering with its original code. Re-platforming without altering its code, rehosting into modern infrastructure or replacement in few cases could help easily enable data from legacy systems.

Sustainability is the core driver of innovation and a competitive advantage in the manufacturing industry. It is significantly influencing automation goals in factories.

Few areas I could envisage are:

·         Minimising waste: Manufacturing execution systems and automation together allows for precise control over material and processes, hence reducing waste and scrap. Combined with robots and AI helps to optimise material usage, leading to less waste and lower cost.

·         Identifying energy intensive processes and eliminating/optimising machine operation for peak efficiency helps to optimise energy consumption. This in turn leads to lower emissions and smaller carbon footprints.

·         Enabling circular economy by using robots and automation to disassemble the products and recover valuable material to reuse and recycle.

·         Remanufacturing and repair could be introduced to promote a circular economy.

·         Traceability and transparency to track materials and products throughout the supply chain, ensuring responsible sourcing, identifying quality issues and enabling quick after sales support and service.

Automation can enable production of more complex and sustainable product designs. Technologies such as additive manufacturing technology is a game changer helping manufacturers leverage on demand production with minimal waste and customised design.

Summing up

Industrial automation and manufacturing are experiencing a very dynamic environment. This makes it very critical to look at budgeting with an overall view of being innovative, at the same time being adaptable to changing situations and factor in investments to take care of the dynamic situations be it supply chain disruptions, tighter regulations or prioritising the road map for digital transformation and automation.

Second critical area is to not compromise on technology, but to focus on adopting advanced technology and stay competitive while improving growth. Factor in tools, technology like metaverse to upskill and enable the workforce to adapt to change and apply their new knowledge to improve operational benefits.

Identifying a roadmap with key milestones along with technology enabled partners are very important to bring success to the program. Choosing the right partner who will walk you through the journey of Automation & digital Transformation is important. Keep in view additional investment for legacy systems, sensorisation, automation of legacy systems, making them smarter may need additional investment in terms of hardware and skilled resources.

Total cost of ownership, initial investment, ongoing cost of unexpected expenses during implementation needs to be factored in. Drive by return on investments, delivering quantifiable benefits in short term and long term. Align your overall business goals to strategic investments, timeline, change management and risks (external and internal).

Author’s note: If any of the above topics interest you, I would be happy to get on a virtual call with you to discuss further, kindly connect on email: rajalakshmi.hegde@outlook.com

The views expressed in this article are personal, not necessarily of the organisation she works for.

Rajalakshmi Hegde is Senior Director – Tech and MALS, at Capgemini Engineering. Prior to that, she was Senior Director – Product Engineering: Manufacturing, LTIMindtree. With over 25 years of experience in Industrial Automation, Product Engineering, Sales, Business Development, Key Account Management, and Application Development, Ms Hegde has motivated many women to join the Industrial Automation and Manufacturing workforce. Prior to joining LTIMindtree, Ms Hegde worked in Global Strategic Account Management at B&R Industrial Automation Pvt Ltd. 

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