Quantbit's weighbridge connector reads net weight data from your weighbridge indicator in real time over RS232, RS485, or TCP/IP. When a truck arrives at the gate, the connector captures the gross weight reading, creates a draft gate entry in ERPNext, and waits for the tare weight on exit. The net weight is calculated automatically and matched to the open purchase order. A goods receipt note is created in ERPNext without anyone typing a single number. The weighbridge register and ERPNext always agree — because they are the same data source.
Yes. Quantbit's PLC connector for ERPNext reads production counts, reject quantities, cycle times, and process parameters directly from Siemens S7, Allen Bradley, Mitsubishi, and other PLC brands via OPC-UA or Modbus TCP. Every shot counted by the PLC becomes a manufacturing log entry in ERPNext. Every alarm becomes a quality flag. Work order progress updates in real time as the machine runs — not at the end of the shift when an operator fills in a form from memory. This is the foundation of real Industry 4.0 for Indian manufacturing.
Connect weighbridges, PLCs, RFID readers, SCADA systems, and MQTT sensors to ERPNext. Production entries, quality records, and material movements happen automatically — the moment the machine does the work.
Indian shop floors are a mix of old and new — a 1990s weighbridge sitting next to a 2022 PLC, connected by nothing except a clipboard. Our connectors bridge that gap without replacing your existing equipment.
The most common integration request from foundries, steel yards, quarries, and agri-processing plants. Your weighbridge already captures the correct data — we just bring it into ERPNext automatically instead of letting someone write it on a slip of paper.
PLCs run your machines. Our connector reads the data they produce — counts, temperatures, pressures, cycle times — and pushes it to ERPNext manufacturing records in real time. No operator data entry, no end-of-shift estimates.
Modern IoT sensors publish data over MQTT — the lightweight protocol designed for machine-to-machine communication. Our connector subscribes to your MQTT broker and routes sensor readings directly into ERPNext records.
RFID readers at your warehouse gates, machine stations, or inspection points can trigger ERPNext transactions automatically. When a tagged item passes a reader, ERPNext knows — without anyone scanning a barcode or filling in a form.
SCADA systems already aggregate data from your entire plant. Instead of maintaining a parallel system in ERPNext, our connector pulls production totals, downtime events, and quality data from SCADA directly into ERPNext records.
Overall Equipment Effectiveness — availability, performance, and quality — calculated automatically from machine data in ERPNext and displayed on a live dashboard. No manual OEE calculations, no weekly spreadsheets.
A foundry's integration needs are different from a food processor's. Each vertical connector pack is pre-configured for the equipment, process parameters, and ERPNext documents that matter in that industry.
Induction furnace temperatures, charge mix, heat numbers, spectroscopy results, and mould counts — all flowing into ERPNext FoundryX automatically from furnace PLCs and weighbridges.
CNC machine cycle times, tool wear tracking, rejection reasons from quality gauges, and production counts mapped to work orders and operation-level routing in ERPNext.
Cane weighbridge entries, juice flow meters, boiling house process parameters, and sugar grading results tied to batch records in ERPNext for end-to-end traceability.
Stamping press counts, heat treatment furnace logs, CMM inspection results, and RFID-based WIP tracking through multi-stage assembly lines.
These are stories from plant floors we have worked on. Not every plant is high-tech. Some are old buildings with reliable machines and clipboards that have worked for decades. The integration is not about replacing what works — it is about eliminating the part where someone has to transcribe what the machine already knows.
A grey iron foundry in Kolhapur was receiving pig iron, scrap, and coke from 15 to 20 suppliers daily. The weighbridge at the gate would generate a printed slip with the truck number, gross weight, tare weight, and net weight. The gateman would hand one copy to the driver and keep one for the store. The store team would manually enter the weight into ERPNext as a goods receipt at the end of the day — usually all at once, from a pile of slips collected during the shift. Every few weeks, a supplier would raise a discrepancy — their delivery note said 12.4 tonnes, but the GRN in ERPNext showed 12.1. Without the original slip, it was impossible to tell whether the transcription was wrong or whether the weighbridge reading was disputed. After the weighbridge integration went live, every reading goes directly from the weighbridge indicator into ERPNext. The GRN is created the moment the truck exits the gate. When a supplier disputes a weight, the weighbridge timestamp, reading, and truck number are all in ERPNext — and the resolution takes minutes instead of weeks of back-and-forth. The foundry also discovered that their store team had been making an average of three data entry errors per day in weight recording — small errors individually, but they had caused Rs 4.5 lakh in reconciliation adjustments over the previous year.
A Tier-2 auto components manufacturer in Pune was producing crankshaft forgings across two shifts. At the end of every shift, the shift supervisor would count the finished parts, fill in a production report on a pre-printed form, and hand it to the planning team who would enter it into ERPNext the next morning. This meant production data was always twelve to twenty hours behind. When the planning manager tried to check whether production was on track for a customer delivery tomorrow, the data in ERPNext showed yesterday's shift. He was making delivery commitment calls based on numbers that were already history. After PLC integration connected the forging press output counters to ERPNext, production counts update every ten minutes. The planning manager can open ERPNext at 2 PM and see exactly how many pieces came off the press as of 1:50 PM. Delivery commitment calls became factual rather than guesswork. One export customer specifically commented that the delivery accuracy improvement had led them to increase their order volume with this supplier.
A precision engineering firm in Sangli was running twelve CNC machines on a three-shift operation. Their planned production numbers were based on the rated cycle time of each machine. But the actual cycle times — what the machines were producing in practice — were being measured only when there was a quality problem or a capacity crisis. Nobody was tracking OEE systematically. When the IoT connector was installed and OEE data from all twelve machines started flowing into ERPNext, the first month's report was uncomfortable reading. The average OEE across the plant was 58% — well below the 75 to 80% that these machines were capable of delivering. The breakdown was revealing: availability was 82% (reasonable), performance was 76% (acceptable), but quality was only 91% (a rejection rate of 9%). The quality issue was traced to a specific setting on three machines that operators were adjusting informally to compensate for tooling wear — a workaround that was causing dimensional variations. Fixing the tooling change schedule and eliminating the informal adjustments raised quality to 97.5%, and overall OEE to 74% within three months. That improvement translated to the equivalent of two additional CNC machines worth of capacity — without buying anything.
A grape processing and export company in Nashik was storing fresh grapes and processed grape products in cold rooms maintained at 0 to 2 degrees Celsius. They had temperature loggers in each cold room that stored readings internally — but nobody looked at the logger data until there was a visible problem. On two occasions in the previous three years, they had discovered temperature excursions after the fact — refrigeration had malfunctioned overnight, temperature had risen to 8 degrees, and a portion of the stored consignment had been damaged by the time anyone noticed in the morning. After MQTT temperature sensors were integrated with ERPNext, any temperature reading above 3.5 degrees triggers an immediate WhatsApp alert to the plant manager and the maintenance in-charge. When a compressor failure caused a gradual temperature rise at 1:30 AM one night, the alert reached the maintenance team within four minutes. They arrived, identified the failed compressor, switched to the backup, and the temperature never exceeded 5 degrees. The consignment was saved. The estimated cost of what would have been lost: approximately Rs 18 lakh.
A structural steel fabrication plant in Bhiwandi was producing beams, columns, and plates to order, tagging each piece with a painted job number and stacking them in a large open yard. Dispatch was supposed to happen from FIFO — oldest production first — but in practice, the yard was so large and the pieces so heavy that the fork-lift operator picked whatever was easiest to reach. When a customer order was due, someone would walk the yard, physically count the pieces, and update ERPNext. This manual count took half a day and was always slightly wrong because pieces got moved, mislabelled, or partially dispatched without a system update. After RFID tags were attached to each fabricated piece and readers were installed at the yard gate and dispatch area, every movement was tracked automatically. The stock count in ERPNext matched the physical yard within 2% instead of the previous 8 to 12% variance. Dispatch went from FIFO-in-theory to FIFO-in-practice because the system could now identify which pieces were produced first. Customer complaints about receiving older stock mixed with new production disappeared.
A pharmaceutical formulation plant in Aurangabad was manufacturing tablets on a batch basis. After each batch, the production team had to compile a batch manufacturing record — capturing granulation temperature and humidity, compression force settings, coating parameters, in-process test results, and final yield. This record was assembled from three different paper forms filled in by operators at different stages of the process. A quality executive would collect the forms, compile them into a master batch record, verify every entry, and enter it into ERPNext. The process took between 45 minutes and two hours per batch, and the risk of transcription error was real. Any batch record entry error required a formal deviation report under GMP rules. After MQTT sensors and PLC data from granulation, compression, and coating equipment were integrated with ERPNext, process parameters are captured automatically and timestamped during production. The operator still fills in manual observations and in-process test results — but the sensor data that previously required transcription is already there. Batch record compilation time dropped from 45 to 120 minutes to 12 to 20 minutes, and deviation reports due to transcription errors dropped to zero.
Your machines speak different languages. Our connector infrastructure speaks all of them and translates into ERPNext.
| Protocol | Common Equipment | Connection Type | Data Frequency |
|---|---|---|---|
| OPC-UA | Siemens S7, Beckhoff, modern CNC machines | TCP/IP | Real-time (100ms to 1s) |
| Modbus TCP | Drives, inverters, energy meters, older PLCs | TCP/IP | Configurable polling (1s to 60s) |
| Modbus RTU | Weighbridges, legacy PLCs, field instruments | RS485 | Configurable polling (1s to 60s) |
| MQTT | IoT sensors, gateways, ESP32/Arduino devices | TCP/IP | Event-driven (immediate) |
| RS232 / RS485 | Weighbridge indicators, barcode scanners, older gauges | Serial | Event-driven on reading |
| OPC-DA | Legacy SCADA historians (WinCC, Wonderware) | DCOM | Scheduled pull (1 min to 1 hr) |
| REST / HTTP | Modern CNC controllers, IoT gateways | TCP/IP | Webhook or polling |
| RFID UHF | Impinj, Zebra FX series, Alien readers | TCP/IP | Tag-read event (immediate) |
Understanding the technical approach helps your IT and automation team evaluate feasibility before we even visit the plant.
Tell us what machines you run, what protocols they use, and what data you wish ERPNext had automatically. We will assess your plant and tell you exactly what is possible.
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