Case Study Manufacturing

Securing Shop-Floor Data in the Cloud for a Global Semiconductor Manufacturer

Joining IIoT shop-floor data with sensitive product and pricing metadata through a secured, masked pipeline into a private cloud data warehouse

An estimated $1-2M per factory per year unlocked by secured, real-time data access

Summary

A top-tier, globally distributed Silicon Power IC semiconductor manufacturer needed real-time and historical visibility into shop-floor manufacturing data joined with sensitive product, pricing, and material metadata — but could not securely expose that data across systems. The problem was compounded by COVID-19-driven demand shifts that required fast, low-manpower operational decisions. aiDataWorks combined technology partner GEMBO’s Precare IIoT platform for edge data collection and OEE analytics with Informatica’s data security, masking, quality, and cloud integration stack (TDM, BDE, IICS, IDQ) to build a secured pipeline from the shop floor to a private cloud data warehouse. The engagement progressed from environment assessment through platform installation, selective data masking, quality rule application, and data lake loading for downstream analytics. The customer gained secured, real-time, multi-user access to previously siloed shop-floor and product data, with estimated combined benefits in the millions of dollars annually from improved OEE performance and faster, better-informed operational decisions.

The challenge

  • Shop-floor data isolated from product metadata. IIoT data captured on the factory floor could not be securely connected to sensitive product metadata — pricing and material costs — held in a separate warehouse outside the factory.
  • Real-time optimization blocked. The inability to expose and secure shop-floor data prevented real-time optimization of operations, directly hurting productivity and revenue.
  • Decisions made offline and late. Without a secured, joined data pipeline, operational decisions were made offline, introducing delay and inaccuracy instead of real-time responsiveness.
  • COVID-19 ramp-up pressure. The pandemic forced a rapid ramp-up of operations with reduced manpower, requiring fast, secure, multi-user access to data for capacity and scheduling decisions.

The solution

Solution architecture: shop-floor IIoT data + product metadata → masking & security layer → private cloud data lake → downstream analytics Download diagram (PDF)

How we built it

Environment assessment & architecture

  • Assessed the existing shop-floor and product-metadata environment and collected requirements from stakeholders across the factory network.
  • Produced a consolidated requirements and architecture document to guide the joint deployment of GEMBO and Informatica components.

GEMBO Precare edge deployment

  • Installed, configured, and smoke-tested GEMBO Precare Cloud/Edge for IIoT edge data collection and OEE analytics.
  • Validated edge data collection across factories spread across the USA, Europe, and Asia Pacific.

Informatica security & integration stack rollout

  • Installed, configured, and smoke-tested Informatica Test Data Management (TDM), Platform, IICS Agents, and Big Data Engineering (BDE).
  • Established the integration layer needed to move shop-floor and product metadata securely into a shared pipeline.

Data masking, quality & cloud data lake loading

  • Performed selective source shop-floor data scanning and metadata masking to protect sensitive pricing and material-cost data.
  • Applied data quality and cleansing rules, then loaded secured data into a private cloud data lake and exposed it for downstream analytics.

Outcomes

3-5% OEE performance affected by metadata inaccessibility roughly 33% of overall OEE
$1-2M Estimated annual revenue impact per factory from the metadata-access problem
$2M Estimated quarterly value from real-time visibility during the COVID-19 ramp-up
  • Product metadata inaccessibility was estimated to affect 3-5% of OEE performance, roughly a third of overall OEE, translating to an estimated $1-2 million in lost revenue per factory per year.
  • During the COVID-19 ramp-up, real-time visibility into secured shop-floor and product data was estimated to be worth approximately $2 million per quarter in customer-contract competitiveness.
  • Combined, the customer estimated the benefits of secured, real-time data access at millions of dollars per year — a figure that excludes additional customer-retention value.

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