Transforming Manufacturing Intelligence:
Unified, Real-Time Analytics & AI Platform on Databricks

A global manufacturing enterprise operating multiple geographically distributed plants was struggling with data silos, fragmented systems, and rapidly expanding IoT sensor data. With limited analytics capabilities, the organization lacked real-time visibility into machine performance, production bottlenecks, and predictive insights for maintenance and scheduling.

Intellify partnered with the client to build a modern, unified analytics and AI platform on Databricks—breaking down silos, enabling real-time data processing, and unlocking actionable intelligence across operations.

Key Results

%

reduction in unplanned machine downtime

%

faster production cycle insights

%

reduction in manual analytics efforts

Goals

Break down siloed data spread across individual plants, ERP, MES, and IoT systems.
Build a scalable platform capable of ingesting and processing high-volume IoT sensor data in near real time.
Enable advanced analytics and AI/ML use cases such as predictive maintenance, energy optimization, and production scheduling.
Create a governed, democratized analytics ecosystem for plant managers, operations, and data science teams.

Solution

Implemented a unified Delta Lake architecture to consolidate ERP, MES, historian, and IoT data into a single governed platform.
Built streaming ingestion pipelines using Auto Loader and structured streaming to process millions of sensor signals per day in real time.
Developed predictive maintenance and anomaly detection models using Databricks ML runtime, accelerating data science experimentation.
Designed a production scheduling optimization engine leveraging historical production runs, machine availability, and sensor data.
Created role-based operational dashboards providing real-time equipment health, downtime patterns, and plant-wise KPIs.
Established end-to-end governance and CI/CD automation with Unity Catalog, data quality checks, and automated deployment workflows.

Results

35%↓

Reduction in unplanned downtime

by proactively identifying machine failures before they occurred.

50%

Faster Insight Generation

through real-time streaming pipelines that empowered quick decision-making.

70%

Enhanced Data Transperancy

via a unified Delta Lake enabling cross-plant analytics and benchmarking.

40%

Reduction in Manual Analytics Efforts

with automated pipelines and standardized data models.

Unified Platforms: Simplified operations and reduced silos, enhancing cross-regional collaboration.
Scalable Architecture: Supported seamless onboarding of new data sources and scaled to future requirements.
Cost and Time Efficiency: Reduced manual effort through automation and consolidated tools for cost savings.
Comprehensive Governance: Delivered robust compliance and access control mechanisms.