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AI can help factory teams spot production bottlenecks and warning signs before they become stoppages—but it depends on connecting data that often sits in separate systems. In an interview with The Economic Times, Praveen Arora, Tata Communications’ vice president of the IoT business unit, describes how the company’s Factory 360 approach combines sensor, application, and factory-control data to give operators a more joined-up view of production. The interview explains a provider’s approach, not an independent assessment of the product or evidence of industry-wide results.
What does AI actually do inside a factory?
In the approach Arora describes, AI analyzes information from machines and production systems to help operators understand what is happening across a plant. Sensors, equipment, applications, and control systems may already collect useful data, but when they operate separately, teams can struggle to see how one part of production affects another.
Tata Communications’ Factory 360 offering is described as bringing together data from sensors, applications, and factory control systems. A combined view can help teams compare installed capacity with actual output and identify where production is falling short. As Arora put it, “You get a complete visibility of where is the bottleneck. You know what is your installed capacity versus the gap.”
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How can connected data help prevent a stoppage?
Conventional alarms generally alert teams when a problem is already apparent. Arora contrasts that response with AI analysis intended to identify earlier signals of an anomaly. If those signals reach operations staff in time, they may be able to investigate and act before a fault becomes equipment failure or a production-line stoppage.
The practical value is therefore not simply collecting more data. It is connecting information, detecting a meaningful change, and getting it to people who can respond. The interview does not provide a technical architecture, latency figures, or an independently tested demonstration of how reliably Factory 360 detects anomalies.
What kind of improvement does Tata Communications report?
Arora told The Economic Times that throughput improvements of 30% to 200% had been achieved “in some situations” using the same resources. That is a substantial range, but the published account does not identify the underlying cases, explain how throughput was measured, or provide independent validation. It should be read as an interviewee-reported result—not a typical outcome, guarantee, or measured result for Indian manufacturing as a whole.
Can older factory machines be connected?
Arora says that even machines 20 or 30 years old can be included by converting their analogue signals into digital information. That offers a possible route to using existing equipment rather than replacing it simply to collect operational data. Whether a particular machine can be integrated, and what that would cost, depends on its signals and the implementation; the interview does not provide compatibility specifications or a cost estimate.
For manufacturers considering a first project, Arora describes starting with a business outcome such as efficiency or cost reduction, checking for security gaps, analyzing data already available from existing systems, and then running a pilot. He says a proof of concept can be demonstrated in less than a week. The account does not name a customer or describe the pilot protocol, so that timing is his claim rather than an independently documented implementation benchmark.
Should processing happen at the factory or in the cloud?
Arora describes deployments that can combine networks, devices, sensors, and applications. He says whether data is processed near the equipment or in the cloud depends on the use case and the system’s overall operating cost. The interview does not specify a universal configuration or provide figures for latency, security, or comparative operating costs. Those factors need to be assessed for the particular production process rather than assumed from the general description.
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How do workers fit into AI-enabled manufacturing?
Arora links worker safety to production continuity: fewer incidents can mean fewer interruptions, while sharing relevant operational information may help teams identify and resolve problems sooner. He describes the goal as supporting employees with information: “It’s about equipping the worker or the employee with more information to make decisions.”
The accompanying video summary says the discussion also touched on wearables, video analysis, worker privacy, manual overrides, and training employees to use AI. It does not establish what privacy controls, override designs, or worker-consultation practices are used in a particular deployment. These are implementation questions manufacturers should resolve rather than assume are covered by the technology.
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What the evidence does—and does not—show
The October 9, 2026 Economic Times interview and the October 10 video describe Tata Communications’ approach and Arora’s reported results. They do not independently evaluate Factory 360 or establish that the reported benefits apply across Indian factories. The interview also does not provide product specifications, current availability, security certification, or a head-to-head comparison with other offerings.
A 2022 Tata Communications blog by Arora said IoT investment in India was close to USD 5 billion in 2019 and forecast growth at a 17.1% compound annual rate. Those are an older company-published historical figure and forecast, not a current measurement of the Indian IoT market.
Quick Recap
Sources
- The Economic Times: “AI can help factories find bottlenecks before production stops: Tata Communications’ Praveen Arora”, October 9, 2026.
- ET Now / The Economic Times: “How AI can cut factory costs and boost output | Tata Communications’ Praveen Arora”, October 10, 2026.
- Tata Communications: “IoT Driven Digital Transformation for Enterprise Innovation”, by Praveen Arora, March 24, 2022.
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