Manufacturing
Manufacturing software that shows output, stock and quality during the shift
We build production reporting, inventory and traceability systems, AI visual inspection and maintenance tools that connect to the machines, spreadsheets and ERP you already have. Start with the data you can capture today, then add sensors, cameras and models where they earn their place.
Overview
Technology for manufacturers
Manufacturing software records what happens on the factory floor and turns it into decisions: production and downtime capture, inventory and batch traceability, quality checks, machine data collection and maintenance planning, connected to the ERP that holds orders and costs. AI adds camera-based inspection and early warnings of machine trouble where the data supports them.
Much of a factory's operational data never leaves the floor. Output is written on clipboards, stoppage reasons are remembered rather than recorded, stock is counted properly only at stocktake, and quality problems surface when a customer returns a batch. By the time the figures reach a spreadsheet, the shift that produced them has gone home.
We build the software layer between the line and the management meeting: line-side screens where operators log output, scrap and stoppages against the job; inventory and batch tracking from goods-in to dispatch; integrations with PLCs, machine controllers and your ERP where they exist; camera-based inspection for visible defects; and maintenance tools that use machine history to plan work before something breaks.
Projects begin with one line, one product family or one report management already relies on. We review what data exists, what can be captured cheaply and what genuinely needs new hardware, and we say plainly where AI helps and where a well-designed form and dashboard will do the job. Operators try working software on their own line every one to two weeks, and one named lead owns the written scope for each phase. The approach suits plants in the UK, Pakistan, Saudi Arabia and international markets, from textiles and packaging to food and engineered components.
Challenges
What manufacturers are up against
Production figures written up after the shift
Output, scrap and downtime are recorded on paper or end-of-shift spreadsheets, so supervisors manage today's line on yesterday's numbers and problems repeat before anyone sees the pattern.
Stoppages that are noticed but never coded
Lines stop for changeovers, material shortages or one unreliable machine, but without consistent reason codes the recurring causes never show clearly in the data.
Stock that only adds up at stocktake
Raw materials, work in progress and finished goods sit in separate spreadsheets, so one line stops for a missing component while other items build up in surplus.
Defects caught after the batch is packed
Visual checks rely on sampling and individual judgement, so a fault introduced early in a run can reach packing, or the customer, before it is spotted.
Maintenance triggered by breakdowns
Machines are serviced on a fixed calendar or after they fail, while the history that could warn of trouble sits in a logbook, a controller or one technician's memory.
An ERP that cannot see the shop floor
The ERP holds orders and costs but not what is happening on the line, older machines have no network connection, and planning still runs on a spreadsheet or an ageing in-house database that one person understands.
What we build
Technology solutions for this sector
Shop-floor data capture app
Tablet and mobile screens at each line where operators record output, scrap, stoppage reasons and changeovers against the work order, using barcode scans and short pick lists instead of free text.
Production reporting and OEE dashboards
Live views of output against plan, downtime by reason, scrap by product and shift handover summaries, with OEE calculated from definitions of availability, performance and quality agreed with your team.
Inventory, batch and traceability system
Goods-in, stock locations, work in progress, finished goods and dispatch tracked by barcode or QR label, with lot links that trace a finished item back to its materials, machine and shift.
AI visual inspection station
A fixed camera with controlled lighting at a defined point on the line, a model trained on your own images of good and defective parts, and a pass, fail or uncertain result sent to a screen, reject mechanism or log.
Machine data and ERP integration
Gateways that read counters and run states from PLCs, machine controllers or retrofit sensors, and services that sync orders, material consumption and completions with your ERP so reports stop depending on manual exports.
Condition monitoring and predictive maintenance
Vibration, temperature, current or cycle data combined with maintenance records to flag machines drifting from normal behaviour, starting with trend alerts and adding predictive models once enough history exists.
Quality checks and non-conformance tracking
In-process check sheets on tablets that record measurements against tolerances, raise a non-conformance report when a reading falls outside limits, and track the investigation and corrective action through to sign-off by your quality team.
AI visual inspection and maintenance alerts support your quality and safety procedures; they do not replace them. Results are reviewed by qualified staff, any connection to machine controls is designed with your engineers and follows your site safety rules, and we can work within the quality systems and customer requirements you already operate under.
Typical projects
Where we usually start
- 01A packaging plant replaces paper production sheets with line-side tablets, so supervisors see output, scrap and stoppage reasons during the shift instead of the following morning.
- 02A components manufacturer adds a camera inspection station at final assembly that checks for missing parts and wrong labels, with uncertain items set aside for a quality inspector.
- 03A textile mill tracks yarn and fabric lots from goods-in to dispatch, so a customer complaint can be traced to the batch, machine and shift involved.
- 04A maintenance team fits vibration and temperature sensors to its most critical motors and receives alerts when readings trend away from normal, alongside its planned maintenance schedule.
- 05A food producer connects shop-floor completions to its ERP, so stock levels and order status update as production is booked rather than at month end.
Services and solutions
How we help manufacturers
Manufacturing FAQ
Frequently asked questions
No. Most manufacturers can start with what they already have: operator entries on tablets, barcode scans, ERP data and any machine counters that are already accessible. That alone usually shows where time and material are being lost. Sensors and direct machine connections are then added where manual recording is unreliable or the line runs too fast to log by hand, so spending on hardware follows a demonstrated need rather than coming first.
Often yes, using whichever route suits each machine. Newer equipment may expose data through its controller or industrial protocols such as OPC UA, Modbus TCP or MQTT, collected by an edge gateway on the factory network. Older machines can be fitted with simple retrofit sensors for cycle counts, run state or power draw. We use read-only connections wherever possible so data collection does not affect how a machine runs, and we never change PLC logic without your engineers' involvement and approval.
It is installed as a fixed station at a point where every item passes in a consistent position, such as after assembly or before packing. A camera with controlled lighting captures each item, a model trained on your own images decides pass, fail or uncertain, and the result goes to a screen, a reject mechanism or a log. It first runs alongside your current inspection so results can be compared, and your quality team decides when it may divert items itself.
You need a record of how machines behave and when they failed or were repaired. Useful inputs include vibration, temperature, motor current, pressure, cycle counts and alarm logs, paired with maintenance records describing what was fixed and when. Many plants have too few recorded failures to train a reliable model at first, so we usually begin with condition monitoring and trend alerts, then build predictive models as the history grows.
Yes, in most cases. We integrate through the ERP's API, database views or scheduled imports and exports, so goods-in, transfers, material consumption and dispatch update stock without double entry. Where the ERP is limited or heavily customised, a separate inventory service can own floor-level detail such as bin locations and lot numbers, and post summarised movements back to the ERP for finance and planning.
Every lot is labelled when it arrives and scanned each time it moves or is consumed, so the system builds a chain from supplier lot to work order, machine, shift and customer shipment. A backward trace starts from a finished item and finds its materials; a forward trace starts from a suspect material lot and lists every order it reached. Running a trace before a customer audit or a mock recall shows where scans are being missed so the process can be fixed.
It depends on how standard your processes are. An off-the-shelf manufacturing execution system suits plants whose workflows match the product and who are willing to adopt its way of working. Custom software suits manufacturers with unusual processes, a mix of old and new equipment, or a need for something lighter that can be rolled out line by line. We often build focused tools for reporting, inventory or inspection beside an existing ERP, and we will say when buying is the better option.
They will if it is quicker than the paper it replaces. We design screens with operators: large touch targets, barcode scanning, short pick lists for stoppage and scrap reasons, and local languages such as Urdu where needed. Supervisors use the data during the shift, which gives everyone a reason to record it accurately. We pilot on one line, collect feedback from the people using it and adjust before rolling out further.
Timelines and costs depend on the number of lines, the systems to integrate and whether hardware such as cameras or sensors is involved. A focused first release, such as digital production sheets and a dashboard for one line, is far smaller than plant-wide traceability or an inspection station. After a discovery call we study sample production records and photos or video of the line, then set out the first phase in a written proposal at a fixed price.
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