Case Study Manufacturing
Industry 4.0 and OEE Analytics Transition for a Semiconductor Manufacturer
Unifying legacy and modern factory-floor machine data into real-time OEE, MTBF, and MTBA analytics — in partnership with technology partner GEMBO's Precare platform
OEE gains of 30-40%, scores as high as 90%
Summary
A semiconductor manufacturer with fragmented, hard-to-access machine data across legacy and modern equipment, siloed IT and OT teams, and incompatible protocols and formats was unable to optimize Overall Equipment Effectiveness (OEE) across its manufacturing sites. aiDataWorks, working with technology partner GEMBO's Precare platform, conducted an infrastructure assessment and architecture plan — using Precare itself to accelerate discovery — then deployed an edge-agent architecture to normalize machine data and deliver real-time OEE, MTBF, and MTBA analytics through a unified dashboard, without a full OT hardware overhaul. The engagement concluded with a transition to managed production-monitoring services, delivering OEE gains of 30-40% with resulting OEE scores as high as 90%.
The challenge
- Legacy, heterogeneous factory-floor machines. Equipment from different OEMs running older operating systems and PLCs lacked the real-time status, performance, quality, and availability data needed to predict maintenance and optimize OEE.
- Siloed IT and OT teams. IT and operational technology teams and systems had been kept apart for legacy reasons, hindering the cross-functional collaboration a digital transformation like this required.
- Incompatible protocols and formats. Machine data access was often batch-only or missing entirely, delivered in formats incompatible with standard IIoT formats and spread across multiple incompatible communication protocols.
- Decision-makers without the data to act. Stakeholders from the factory floor to the corporate office lacked the data needed to make informed decisions to optimize OEE and grow revenue.
The solution
How we built it
Infrastructure assessment & architecture planning
- Performed an assessment of the customer's factory-floor infrastructure across its manufacturing sites and defined the target architecture and project plan.
- Used the GEMBO Precare platform itself as an accelerator during the initial investigation, making the assessment faster, more comprehensive, and more accurate.
Edge-agent deployment & data normalization
- Executed a holistic deployment of edge agents to collect real-time data from both legacy and modern machines across the shop floor.
- Normalized disparate data formats — carried over SECS/GEM, SCADA, RS232/485, Industrial Ethernet, and OPC-UA — into a uniform format, with low-latency edge processing and secure agent-to-cloud connectivity.
Unified OEE, MTBF & MTBA analytics dashboard
- Delivered big data analytics — OEE, MTBF, MTBA, and predictive maintenance — through a unified, machine-agnostic dashboard.
- Configured a visually programmable rule engine with multi-channel notifications, so stakeholders from the factory floor to the corporate office could act on the same data.
Managed production monitoring
- Rolled out managed services for ongoing production monitoring once the platform was live, hosted on hybrid cloud infrastructure.
- Kept the analytics environment observed and tuned after go-live, in support of maximum uptime for the new OEE capability.
Outcomes
- OEE gains of 30-40% translated into higher effective capacity across the customer's monitored production lines, with post-deployment OEE scores reaching as high as 90%.
- Reaching those gains required no full overhaul of existing OT infrastructure, delivering significant cost savings compared with replacing shop-floor equipment outright.
- The transition to managed production-monitoring services after deployment gave the customer maximum uptime, sustaining the new analytics capability without standing up an in-house monitoring function from scratch.
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