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IndustriesManufacturing & Operations

Operational visibility from shop floor to boardroom.

Manufacturing businesses generate enormous volumes of operational data — from machines, quality systems, ERP, and supply chain — but most of it sits in silos. We build the integration and automation layer that turns raw operational data into real-time visibility, predictive capability, and reduced manual overhead across production, maintenance, and supply chain.

35%reduction in unplanned downtime through predictive maintenance
The problems

What we hear from manufacturing & operations teams.

Production scheduling complexity

Scheduling across multiple lines, machines, shifts, and material constraints is often done in spreadsheets or outdated MRP modules. A single late delivery or machine fault cascades through the schedule. Planners spend more time firefighting than planning.

Quality control data in silos

Inspection data, rework logs, and non-conformance records sit in separate systems — or paper forms — and rarely feed back to production decisions in real time. Defect patterns take weeks to surface rather than hours.

Reactive maintenance culture

Most plants still run maintenance on fixed schedules or wait for failures. Neither is optimal. Fixed schedules over-maintain; reactive maintenance causes unplanned downtime that costs far more than the repair.

Supply chain visibility gaps

Supplier delivery status, inbound material tracking, and stock-at-risk data are scattered across emails, portals, and ERP entries. Operations managers are always one late delivery away from a line stoppage they didn't see coming.

What we build

Solutions designed for Manufacturing & Operations.

Production Scheduling AI

Constraint-aware scheduling engine that optimises across machines, labour, materials, and priorities in real time. When a machine goes down or a delivery slips, the schedule reoptimises automatically and surfaces the best recovery path for planners to approve.

Quality Anomaly Detection

Real-time analysis of inline measurement data, vision system outputs, and operator inspection records to detect emerging quality patterns before they become line-stop events. Non-conformances are automatically traced to process parameters, reducing root-cause investigation from days to hours.

Predictive Maintenance System

Sensor data from critical assets — vibration, temperature, current draw — continuously monitored against degradation models. Maintenance work orders generated automatically when signatures indicate impending failure, before the equipment stops. Reduces unplanned downtime by 30-40% in the first year.

Supply Chain Integration Hub

Live feeds from supplier portals, inbound logistics APIs, and ERP purchase orders aggregated into a single operational picture. Automated alerts when confirmed deliveries are at risk of being late, with impact assessment against the production schedule.

Where AI fits

Common automation workflows in manufacturing & operations.

Workflow 1
Production Scheduling AI data input
AI processing & classification
Automated production scheduling ai action
Data InputAI ProcessingAction / Output
Workflow 2
Quality Anomaly Detection event trigger
Rules engine & AI decisioning
Quality Anomaly Detection outcome delivered
Data InputAI ProcessingAction / Output
Workflow 3
Predictive Maintenance System request
Integration & data sync
Predictive Maintenance System result logged
Data InputAI ProcessingAction / Output
35%
reduction in unplanned downtime
92%
early defect catch rate before end-of-line
98%
scheduling accuracy vs. actual throughput
14 hrs
manual reporting hours saved per week

We used to find out a bearing was failing when the line stopped. Now we get a work order two weeks in advance. That shift alone has paid for everything many times over.

MarkOperations Director, Precision Components Manufacturer

Ready to solve your manufacturing & operations challenge?

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