By Aayaan Bery, Global Marketing Director at KSP Inc.
Every manufacturer has a number they dread seeing at the start of a month. For some it is the metal rate, for others fuel, or the price of a component that only one supplier makes. The plant has no say in any of them. What it does control is how much of each goes into every unit that leaves the gate.
That distinction matters more right now. The HSBC Flash India PMI for September 2026, compiled by S&P Global, shows cost pressures picking up again among manufacturers, even as they eased across the wider private sector. Firms reporting higher costs pointed to electrical components, fuel and metals, and factory gate prices rose as companies tried to protect their margins. Exporters have less room to do that. Overseas buyers negotiate hard, and a price increase can send an order elsewhere.
So the practical question is not how to stop input costs from rising. It is how to make each good unit carry less of them. Automation, in its less glamorous forms, is one of the more dependable ways to do that.
Variation is where the money hides
Ask a plant manager where material goes and the answer is usually scrap. Look a little closer and the real culprit is variation. Fill weights are set slightly high to stay safely above the minimum. Cutting layouts leave more offcut than they need to. Ovens are held hotter than necessary, just as a cushion.
Consider a plant coating metal components for an overseas customer. The specification calls for a minimum film thickness. Without dependable measurement, operators aim well above it, because a thin part means a rejection. Every extra micron is paid for in paint, cure time and energy. With inline thickness measurement feeding back into the spray parameters, the line can settle just above the minimum and stay there.
That is closed-loop control in plain terms. Sensors measure the actual value, a controller compares it with the target, and actuators correct the difference many times a second. Once a process holds a tighter band, it can run closer to the specification limit without crossing it. Over a year of production, the giveaway that disappears adds up to a good deal of steel, resin or fabric that never had to be bought.
Energy is a cost you can manage
Commodity prices belong to the market, but energy use belongs to the plant. The first step is a modest one: submetering. Many factories know their monthly electricity bill without knowing what a single line, press or furnace consumes per unit produced. Once that number exists, patterns appear quickly, such as a compressor running through the lunch break or a pump throttled by a valve while its motor spins at full speed.
That second case is a classic. Variable frequency drives on pumps and fans let the motor slow down to match demand, and because power draw falls roughly with the cube of speed, a modest reduction in speed brings a disproportionately large drop in consumption. Add automatic compressor sequencing, leak detection, power factor correction and load scheduling around time-of-day tariffs, and the electricity bill begins to move.
There is an export angle as well. The EU's carbon border mechanism entered its definitive phase in January 2026, and EU importers in covered sectors increasingly need emissions data from their suppliers. Energy readings captured automatically at machine level make that request far easier to answer than a spreadsheet stitched together at month end.
Quality is a pricing issue
Export competitiveness is not only about the unit price. A rejected consignment can erase the margin on an entire order through freight, re-inspection and replacement, and it can cost something harder to win back, which is the buyer's confidence.
Automated inspection helps here. Machine vision cameras, in-line gauging and automated test stations check every part instead of a sample, and they do not tire at the end of a night shift. Paired with batch or serial traceability, a defect can be followed back to the machine, tool or material lot that caused it. The fix then happens at the source, not at final inspection, where the cost of the mistake has already piled up.
None of this runs itself, of course. Vision systems depend on stable lighting, proper fixturing and well-labelled examples of defects, and a system that rejects good parts too often burns money in a different way.
Fewer surprises on the floor
Unplanned downtime is expensive in ways the machine's own report never shows: idle operators, missed dispatch dates, and scrap generated during restarts. Condition-based maintenance uses vibration, temperature and motor current signals to spot a bearing or gearbox heading for trouble before it stops the line. The shift is from servicing on a calendar to servicing when the equipment says it needs attention.
The sensible way in is to choose a handful of critical assets, gather baseline readings for a few weeks, and set alert thresholds from real behaviour rather than default values. Otherwise the plant drowns in alarms and learns to ignore them.
Labour, handling and flow
Wages are climbing and skilled operators are hard to retain. Automation here is less about replacing people than about moving them towards work that needs judgement. Collaborative robots can take over repetitive loading, screwdriving or palletising. Autonomous mobile robots can carry material between stations so that a skilled machinist is not pushing a trolley. Less manual handling also means fewer dented parts and scratched surfaces, which quietly feed the rejection numbers.
You can't fix what you can't see
Much of the Indian factory floor is a mix of machines from different decades, and replacing all of them is not realistic. Retrofit gateways that read signals over common industrial protocols such as Modbus and OPC UA can bring data from older equipment into a manufacturing execution layer without a rebuild.
Once that data flows, overall equipment effectiveness can be split into availability, performance and quality, and the biggest loss becomes obvious. Orders can also be costed on actual machine time, scrap and energy used, which shows which jobs make money and which only look busy.
Where projects go wrong
A few mistakes repeat themselves. Automating a process that is already unstable only produces bad parts faster. Buying a large system before measuring a baseline leaves no way to prove it worked. Islands of automation that cannot share data create new manual work in between. And cybersecurity and operator training tend to be remembered after go-live, which is late.
A more forgiving path is to choose one bottleneck line, measure OEE and energy per unit for a few weeks, fix the largest loss, confirm the payback, and only then move to the next. It also helps to judge projects on cost per good unit rather than on the price of the machine. A modest controller that cuts scrap on a high-volume line can repay itself faster than an expensive robot cell on a low-volume one. For smaller manufacturers, modular equipment and phased retrofits keep the capital at risk small.
The practical takeaway
Some of the pressure on Indian manufacturers, from commodity swings to freight and geopolitics, sits outside anyone's control. What a plant can control is how much material, energy, time and rework goes into each unit that ships. Automation is a way to move that number, line by line, without fanfare. An overseas buyer will never see the sensors or the control loops. They will notice consistent quality and shipments that arrive when promised, and that is usually what keeps an order on the books.
Aayaan Bery is Sales and Global Marketing Director at KSP Inc., Business Development & Global Markets, RAI Manufacturing, Industrial Automation.
Aayaan Bery represents the next generation of leadership at KSP Inc., a family-led manufacturing business currently transitioning into its third generation. Since joining the company in 2023, he has been instrumental in strengthening KSP’s global commercial strategy, with a focus on expanding international market presence, building long-term customer relationships, and driving sustainable sales growth.
