Real Results for Real Manufacturers

Challenge

The plant ran 10 progressive die stamping presses and 5 spot weld stations across three shifts with no real-time downtime capture. Shift leads logged stoppages on paper at the end of each shift — often incomplete and always too late to act on. OEE was calculated in Excel the following morning. Management had no visibility into which machines were the biggest contributors to lost production, and chronic delivery shortfalls to their OEM customer were becoming a contractual risk.

Challenge

A multinational customer required component-level traceability across the full PCB assembly process as a condition of a major program award. The plant was using paper travelers and manual test result logs. When a recall verification drill was run, reconstructing the production history of a single board took an average of three working days — and some historical records were simply missing.

Challenge

The bakery produces over 40 SKUs across three tunnel oven lines. Oven temperature profiles — zone set points, actual zone temperatures, and belt speeds — were recorded manually by operators every 30 minutes on paper log sheets. When a customer returned a batch of bread rolls citing inconsistent texture, the quality team could not confirm whether the correct bake profile had been followed, as the paper logs for that shift were partially illegible. Separately, raw material traceability was limited to daily flour delivery records with no link to individual production batches, making a targeted recall practically impossible.

Challenge

Batch manufacturing at the plant required paper batch records that QC staff compiled manually after each run — a process taking an average of 45 minutes per batch. During a regulatory audit, inspectors identified two batches where the paper records had gaps in parameter sign-offs. Retrieving historical batch documentation for a customer query required locating physical folders from the archive room, sometimes taking hours.

Challenge

Electricity was the third-largest line item on the plant's P&L, but management had no visibility into which machines or production lines were driving the cost. There was a strong suspicion that machines were drawing significant power during unplanned downtime and idle periods between jobs, but no data to confirm or quantify it. Monthly utility bills gave a single total — nothing more.

Challenge

The manufacturer operates an in-house finished goods and spare parts warehouse storing over 1,800 SKUs — extinguisher cylinders, valve assemblies, propellant cartridges, and service kits spanning multiple pressure ratings and certifications. Inventory was managed in Excel, updated manually after each despatch run. Stock counts regularly showed discrepancies of 3–5%, leading to either short shipments on urgent site orders or overstock write-offs on slow-moving variants. More critically, regulatory traceability requirements for fire suppression equipment meant that shipment records needed to show which certified batch of extinguisher bodies and propellant charges were sent to each installation site — a requirement that paper-based despatch notes could not reliably satisfy.

Challenge

The plant operates two rotary kilns, four cement mills, and a network of conveyors and fans consuming over 8 MW of installed electrical capacity. Electricity and fuel costs account for more than 35% of total production cost, but the operations team had no visibility into energy consumption at the equipment level — only a monthly utility bill. Critical equipment such as kiln drive motors, mill gearboxes, and separator fans had no vibration or temperature monitoring; breakdowns were only discovered when equipment tripped, causing unplanned kiln stops that took 6–12 hours to recover. Maintenance was carried out on a fixed time-based schedule regardless of actual equipment condition.

Challenge

The OEM builds semi-automatic and fully automatic liquid chemical filling lines for industrial and household chemical customers. Their machines were shipped with a conventional touchscreen HMI for operator control and a paper-based maintenance checklist. Customers had no visibility into machine performance between service visits, and the OEM had no data from the field to understand how machines were actually being used or where failures occurred most frequently. As customers grew more sophisticated, requests for OEE data, fill count logs, and detailed fault history were increasing — requirements the current HMI architecture could not satisfy without significant custom development on each project. When machines broke down, service engineers arrived on-site with no prior context — no data on what the machine was doing before the fault, making diagnosis slow and unpredictable.

Challenge

The manufacturer operates a continuous annealing furnace line comprising multiple process stages — destacker, entry accumulator, furnace heating and soaking zones, atmosphere purging, cooling section, and exit stacker. Furnace process parameters — zone temperatures, atmosphere gas flow rates, belt speed, and tube surface temperature — were monitored via a legacy SCADA system that had not been supported by the vendor for several years. Alarm history was limited to a rolling 7-day log with no long-term storage, making it impossible to correlate process conditions with quality outcomes across the full line. Tube traceability was paper-based: coil identity and furnace run details were recorded manually on traveller cards, which were sometimes lost or illegible. Production and quality reports had to be compiled manually by the QC engineer from multiple sources at the end of each shift, typically taking over an hour.