Enhance your manufacturing processes with advanced AI and data analytics powered by Databricks for smarter, more efficient production.
Manufacturing organisations across the UK and Ireland are under growing pressure to increase throughput, reduce waste and respond faster to market shifts. Transatlantix helps manufacturers unify fragmented operational data and unlock measurable performance gains through modern AI and data platforms.
Most manufacturing organisations operate with data fragmented across MES, ERP, supply chain platforms, IoT sensors and finance systems. The challenge is not a lack of data — it is the inability to connect, govern and act on it in real time.
Production data sits in isolated MES, ERP and scheduling systems, preventing a unified view of operations across lines and plants.
Without real-time visibility, production teams discover supply chain disruptions, equipment failures and bottlenecks too late to respond effectively.
Quality defects are identified downstream rather than at the point of origin, leading to costly rework, scrap and customer complaints.
Finance and production data operate on different timelines, meaning cost overruns are only visible weeks after they occur.
Sensor and IoT data is collected but not integrated into operational workflows, leaving valuable machine intelligence untapped.
Production planning relies on static forecasts rather than real-time demand signals, resulting in overproduction or stock-outs.
Downtime and Throughput Loss
Unplanned equipment failures and bottlenecks reduce production capacity and output.
Waste and Rework
Late-detected quality issues drive up scrap rates, rework costs and material waste.
Budget Overruns
Without real-time cost visibility, budgets are exceeded before finance teams can intervene.
Delivery Delays
Disconnected planning and production data leads to missed delivery commitments and customer dissatisfaction.
Inconsistent Quality
Fragmented quality data makes it difficult to maintain consistent standards across shifts and sites.
Decision Friction Across Teams
Operations, quality and finance teams work from different data sources, slowing cross-functional decisions.
Data fragmentation does not stay contained. It compounds across production, quality, finance and supply chain functions — eroding margins, normalising inefficiency and trapping teams in a cycle of reactive firefighting.
When equipment failures are only addressed reactively, unplanned downtime becomes an accepted cost of doing business. Teams stop questioning lost hours because they lack the predictive data to prevent them. Over time, throughput targets are quietly adjusted downward to accommodate recurring stoppages.
Without real-time quality monitoring at the point of production, small parameter deviations go unnoticed until they compound into batch failures. Rework becomes routine, scrap rates climb, and customer complaints increase — each one eroding trust and margin simultaneously.
When production costs are only reconciled at month-end, overspend is discovered too late to correct. Energy costs, raw material variances and labour inefficiencies accumulate unchecked, turning manageable variances into significant budget overruns.
When operations, quality and finance teams each work from their own disconnected data sets, misalignment becomes structural. Production prioritises volume, quality flags issues after the fact, and finance struggles to attribute costs accurately — creating a culture of blame rather than coordination.
Transatlantix builds Databricks lakehouse architectures combined with ML models and real-time dashboards to unify shop-floor, planning, supply chain, quality and finance data into a single governed platform — giving manufacturing leaders the visibility they need to act decisively.
AI-driven production planning and execution that dynamically adjusts schedules, allocates resources and sequences work orders based on real-time demand and capacity.
Live dashboards tracking production status, line performance, bottlenecks and throughput across all sites and shifts in real time.
Predict defects before they occur using ML models trained on historical quality, process and sensor data — reducing scrap and rework costs.
Use sensor data and ML to predict equipment failures before they happen, scheduling maintenance proactively and preventing unplanned downtime.
Track production costs in real time — energy, materials, labour — with automated variance analysis and budget alerts.
Connect production planning to real-time market demand signals, enabling data-driven forecasting, inventory optimisation and go-to-market alignment.
Reduced
Downtime across production lines
Reduced
Waste & rework costs
Improved
On-time delivery performance
Improved
Cost visibility and control
Purpose-built capabilities for manufacturing data transformation, from real-time production monitoring through to predictive maintenance and market intelligence.
Live dashboards tracking OEE, throughput, cycle times and line status across all sites
Automated alerts for bottlenecks, stoppages and performance deviations in real time
ML models trained on vibration, temperature and process data to predict failures before they occur
Proactive maintenance scheduling that reduces unplanned downtime and extends asset life
Continuous tracking of energy, material and labour costs against budgets with automated variance alerts
Granular cost attribution per production line, batch and product for accurate margin analysis
Demand forecasting models that integrate market signals, order patterns and seasonal trends
Inventory optimisation aligned to predicted demand, reducing carrying costs and stock-outs
Streaming analytics that process production, quality and supply chain data as it is generated
Decision-support dashboards that surface actionable insights for plant managers and executives
Seamless ingestion of IoT sensor data — vibration, temperature, pressure, humidity — into the lakehouse
Unified sensor-to-insight pipeline connecting machine data to operational and business analytics
Single governed data platform with role-based access for operations, quality, finance and leadership
Cross-functional collaboration on a shared data foundation, eliminating version conflicts and silos
Novelis, a global leader in aluminium rolling and recycling, partnered with Databricks and Transatlantix to modernise their manufacturing data infrastructure. The engagement focused on consolidating fragmented production, quality and operational data into a unified lakehouse architecture capable of supporting real-time analytics and advanced AI workloads.
RSA guided the migration strategy, recommending the UCX utility from databrickslabs to overcome technical hurdles during the platform transition. This approach ensured a smooth migration with minimal disruption to ongoing operations, while establishing a scalable foundation for future data initiatives.
The result is a modern, governed data platform that enables Novelis to make faster, more informed decisions across production, quality and supply chain operations.
View Case StudyUnified Data Platform
Consolidated production, quality and operational data into a single governed lakehouse architecture.
Seamless Migration
UCX-guided migration with minimal operational disruption and full data integrity preservation.
Real-Time Analytics
Enabled real-time production and quality analytics across manufacturing operations.
Scalable Foundation
Established a future-ready platform for advanced AI and ML workloads across the organisation.
Deep experience in manufacturing data transformation, with an understanding of the production, quality and supply chain challenges specific to discrete and process manufacturing environments.
Advanced lakehouse architecture design and optimisation, ensuring manufacturing organisations extract maximum value from the Databricks platform for production and operational analytics.
Every engagement is structured around measurable outcomes — reduced downtime, improved quality, lower costs and faster decision-making — not just technology deployment.
Ongoing partnership beyond implementation, with dedicated support to ensure your manufacturing data platform evolves with your operational needs and growth objectives.
Book a 30-minute consultation to assess your production data landscape and identify high-impact opportunities for your manufacturing organisation.