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Our new digital initiatives focus on AI-based quality control, predictive maintenance, and cybersecurity enhancement: Satej Revankar, CIO, FIAT India Automobile

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In an interaction with Express Computer, Satej Revankar, CIO, FIAT Automobile highlights the recent digital initiatives implemented in his organisation. He speaks about safety enhancement, quality digitisation, cost reduction strategies, supply chain optimisation, and AI integration. 

Adding further, he also talks about the challenges in AI implementation and cybersecurity measures, while outlining future initiatives focusing on quality control, predictive maintenance, and cybersecurity enhancement, aligned with business goals.

Here are the edited excerpts: 

1. Can you take us through some of the recent digital initiatives that you have implemented, and its impact?

At FIAT, we stand out as a joint venture between Tata Motors and Stellantis (formerly Fiat), focusing on manufacturing rather than branding. We produce various vehicles, including the Jeep Compass, Jeep Wrangler, Jeep Cherokee, and Tata Motors’ Nexon and Altroz in petrol, CNG, and electric versions.

Digital initiatives are central to our strategic roadmap, which includes seven strategic imperatives for the next three years, with Industry 4.0 and digitisation being pivotal. These initiatives are closely linked to our core manufacturing objectives: safety, quality, delivery, cost, sustainability, and product innovation.

We have significantly improved safety through digitisation. A mobile app for safety audits and IoT sensor-based systems helps prevent unsafe conditions, enhancing our safety indices over the past few years. Quality digitisation is paramount, especially since we cater to domestic and export markets. We have implemented several initiatives, including automated quality inspections utilising Industry 4.0 tools. By connecting our manufacturing execution systems to workstations, we enable real-time quality inspection and defect detection, minimising human error. Additionally, capturing data from PLC-based systems helps identify and control cost overruns and quality defects. We are also planning to introduce virtual reality-based training for our paint shop to enhance quality further.

Cost reduction is another critical focus. The GEAR framework, an internally developed system (Generate, Evaluate, Approve, and Realise), captures ideas from operators, links them to processes, and evaluates them financially. It predicts potential cost reductions, becoming a cultural practice at FIAT.

Ensuring timely delivery is crucial for us. We use GPS-based tracking for vehicle traceability and supply chain optimisation. We have integrated around 600 suppliers within 5 km to 35 km of our plant. These suppliers are connected through a digital platform that ensures real-time data analytics and supply chain synchronisation. This integration has optimised our inbound logistics and improved efficiency significantly.

In short, our recent digital initiatives have significantly impacted various aspects of our manufacturing process, from enhancing safety and quality to reducing costs and ensuring timely deliveries.

2. How do you plan to integrate AI strategically into the organisation’s IT roadmap?

Integrating AI strategically into FIAT’s IT roadmap presents both exciting opportunities and notable challenges. The automotive industry, and specifically the manufacturing sector within it, offers significant scope for AI applications. We have been exploring generative AI since last year and have identified several promising use cases in areas like quality, prototyping, production startup stages, and streamlining manufacturing processes.

One of our key initiatives is enhancing quality digitisation using generative AI. Traditionally, the exterior inspection of cars involves quality inspectors, which can introduce errors and subjectivity, leading to throughput losses. We are now implementing a 360-degree vision inspection technology. This system models and audits the car’s exterior using data from the last six to seven years, applying AI to detect and control defects. Over time, as the AI learns, it should prevent these defects, significantly improving quality control. We are moving from evaluation to execution in this process, following the lead of our partner, Tata Motors.

Another area we are exploring is shop floor work instruction content creation. By analysing data from our manufacturing execution system, which records defects and misalignments, we can create specific work instructions for each car model and workstation. This content will be converted into voice instructions played at the relevant stations, further enhancing precision and efficiency.

We are also focusing on predictive maintenance using generative AI capabilities. Currently, sensor-based technology in our paint and body shops detects the conditions of heavy equipment. We aim to predict data trends and apply AI to provide process-level predictions, not just equipment-level, thereby optimising maintenance and reducing downtime.

3. What challenges do you foresee in AI implementation?

Implementing AI comes with multiple large and small scale challenges. Data privacy and security are significant concerns, as large volumes of data need to be processed by AI platforms. Ensuring these platforms handle our data securely is crucial. Additionally, AI integration requires workforce realignment and skills adaptation. For instance, vision inspection technology may reduce the need for physical inspectors, necessitating changes in process management and control.

Cost is another challenge, as the return on investment for generative AI is not immediately apparent. Senior leadership and business sponsors must be adaptive and able to foresee the potential impact of these technologies early on to avoid delays in adoption. Despite these challenges, the benefits of AI integration in terms of improved quality, efficiency, and predictive capabilities make it a worthwhile pursuit. Our early learnings indicate that while there are hurdles to overcome, the strategic integration of AI holds great promise for the future of our manufacturing processes.

4. With the increasing importance of cybersecurity, what measures are you taking to ensure the security and integrity of IT systems and sensitive data?

Ensuring the security and integrity of our IT systems and sensitive data is paramount at FIAT India Automobiles, especially given the increasing importance of cybersecurity. Our focus on generative AI and Industry 4.0 involves primarily manufacturing data, necessitating a clear segregation between IT (Information Technology) and OT (Operational Technology) systems.

Initially, we implemented logical segregation, but this financial year, we are moving towards mandatory physical segregation to enhance data protection significantly. This physical isolation of networks is crucial for robust cybersecurity.

One major challenge we face is integrating adaptive or emerging technologies with our existing legacy systems and third-party manufacturer dependencies. To address this, we are standardising our entire system, including the OS, patching, and application layer security across both third-party OEM systems and our own. This standardisation ensures compatibility and robust security.

We are deploying three top-of-the-line security solutions. First, we have implemented Security Incident and Event Management (SIEM) for comprehensive event logging and monitoring, providing real-time analysis of security alerts. Second, we are advancing beyond traditional Endpoint Detection and Response (EDR) to include OT-level security solutions, deploying a specific OT security module to protect our operational technology infrastructure. Third, we are integrating threat intelligence and analytics into our security strategy, using advanced systems to analyse and respond to potential security threats in real-time.

Our approach starts with physical network segregation, moves towards standardising third-party and legacy OEM systems, implements SIEM for logging and analytics, and finally, deploys the OT security component. This comprehensive strategy ensures the integrity and security of our sensitive manufacturing data.

5. In the next six months to one year, what are some of the new digital or technology initiatives planned?

We have multiple digital and technology initiatives in the next six months to a year. These include implementing AI-based 360-degree vision inspection for quality control and a cloud-based predictive maintenance system. VR-based training and cost optimisation models will enhance our paint shop operations. We’re also strengthening cybersecurity with SIEM, threat intelligence, and OT security measures. A real-time GPS-based vehicle traceability module will improve logistics, while digitised warehouse management with shelf-life tracking will enhance inventory management. Aligning these initiatives closely with business KPIs ensures positive ROI and builds internal trust, fostering sustained progress and innovation.

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