Optimise OEE, inventory and quality in real time
Connect machinery, digitalise production management and unify it with ERP on one AI-native platform — seeing and optimising every machine and every work order, with less downtime and fewer quality defects.
The challenges facing a plant
Machines are not connected
No real-time visibility of equipment effectiveness (OEE) or downtime; decisions are made on stale figures.
Planning, production and inventory are out of step
Insufficient synchronisation between orders, plans, production and stock, leading to surplus or shortage of materials.
Quality and traceability are difficult
Hard to establish the cause of a defect, trace a lot back to source, or control scrap.
Maintenance is reactive
Repairing only once a machine has failed causes sudden stoppages and high cost.
How DBIZ addresses this
How the DBIZ AI-native platform applies specifically to the plant — from machine connectivity and production management through to AI-driven predictive maintenance.
Real-time production management with MES
Monitoring of OEE, work orders, progress and the performance of each machine, with electronic operation tickets and shift reporting.
IoT connectivity and machine data capture
IoT devices capture machine parameters (speed, temperature, vibration, consumption) in real time — including on older equipment.
AI-driven predictive maintenance
AI agents analyse machine data, predict failures and schedule maintenance before a stoppage occurs, reducing downtime.
Planning, production, inventory and purchasing unified
ERP synchronises demand, material planning (MRP), work orders, inventory and purchasing in a single system.
Quality management and lot traceability
QC control at each production stage, end-to-end traceability, rapid isolation of defects and reduced scrap.
Energy and consumption optimisation
Monitoring energy consumption by machine and by stage, to cut cost and emissions.
The value delivered
* Industry reference levels published internationally, not measurements from any specific organisation; actual results vary with each plant’s starting position.
Representative case studies
Plants that have optimised operations and quality with DBIZ technology.
Challenge: Multiple plants, high kiln energy consumption, and material traceability difficult to establish.
The DBIZ solution: ERP, MES and IoT provided real-time kiln monitoring, energy optimisation and end-to-end traceability.
View details →Challenge: Moulding machines and warehousing run manually, with high scrap and no traceability.
The DBIZ solution: ERP and MES digitalised production management, with QC control at each stage and 100% lot traceability.
View details →Challenge: Operations at scale, with monitoring and leakage control difficult across the network.
The DBIZ solution: ERP, Data and IoT standardised the processes and provided real-time monitoring across more than 900 sites.
View details →DBIZ in practice
A selection of DBIZ product screens for plants and manufacturing — with the benefits and capabilities each one delivers.
A production and product development control dashboard
Project KPIs, formulations awaiting approval and compliance levels, together with an action and alert centre — the full picture, and the right priority handled first.
Real-time HACCP/CCP monitoring
Critical control points (temperature, process parameters) tracked in real time, with alerts when thresholds are exceeded — assuring safety, quality and compliance while reducing scrap.
Releasing formulations and BOMs to production
Readiness, formulation, bill of materials and routing are verified before release — moving from R&D to production accurately, with no discrepancy.
Product catalogue and lifecycle
Centralised management of products, versions and lifecycle status — standardising product data end to end across the plant.
A product development AI agent (human-in-the-loop)
The AI agent executes the steps and makes proposals, while people approve at each control gate — accelerating development and operations while keeping risk under control.
Bring your plant into real time
Get advice on an MES, ERP and IoT roadmap suited to your scale and the specifics of your production.
About the figures on this page
The percentages above are industry reference levels — the range of impact international research bodies have recorded where organisations automate processes with AI: McKinsey Global Institute (2017) estimates that around half of today’s work activities are technically automatable; McKinsey & Company (2018) assesses that 42% of finance activities can be fully automated and a further 19% mostly automated with currently demonstrated technology; Brynjolfsson, Li & Raymond — NBER (2023) found a generative AI assistant raised customer-support productivity by 14% on average, and by 34% among newer staff. These are not measurements taken at any specific organisation and are not a performance commitment; actual results vary with deployment scope, data readiness and the current state of each organisation’s operations. Figures DBIZ has measured in the field are published separately together with the measurement method — see AP Agent — figures measured in the field. DBIZ commits to specific targets for each client after the assessment phase.