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GFT Leverages Google Cloud to Simplify AI Deployments at Scale in Manufacturing, Reducing Dependencies on Data Science Experts

Recruiting data scientists is one of the greatest challenges in the current labor market: analysts say that there was a shortage of 250,000 data scientists globally even in 2020.  The situation has only exacerbated since then.

AI solutions have the potential to significantly boost productivity in manufacturing. Usually, skilled data scientists are key for AI projects to be successful. Google Cloud has now introduced new purpose-built solutions that can be used by manufacturing engineers without requiring the help of specialized data scientists or additional integration code in order to scale digital transformation pilots into production. This will facilitate the digital transformation efforts in the manufacturing segment. As a Google Cloud Global Partner, GFT has tested and implemented these solutions in Top 10 automotive and manufacturing leaders.

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“These solutions will democratize access to data on the manufacturing floor. They will generate more competitiveness for industries, and manufacturing engineers will gain the opportunity to acquire AI based skill sets,” says Marco Santos, President of GFT USA and Latin America. “Our first-hand experience tells us manufacturers can expect a major boost in their manufacturing floor.”

“Transforming factory-floor operations with data and analytics is hugely important to manufacturers today,” said Charlie Sheridan, Technical Director, Industry Solutions, Manufacturing, Google Cloud.  “We’re thrilled to work with partners like GFT to extend the outreach of our core technology and provide customers with the foundational technologies needed to solve business challenges and scale smart factory implementations.”

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The new Google Cloud solutions supported by GFT include:

  • Manufacturing Data Engine is an end-to-end solution that processes, contextualizes, and stores factory data on Google Cloud’s market-leading data platform. It provides a configurable and customizable blueprint for the ingestion, transformation, storage, and access to factory data. It integrates key Google Cloud products, including Cloud Dataflow, PubSub, BigQuery, Cloud Storage, Looker, Vertex AI, Apigee, and more, into a manufacturing-specific solution.
  • Manufacturing Connect is a factory edge platform co-developed with Litmus Automation that quickly connects to, and streams data from, nearly any manufacturing asset and industrial system to Google Cloud, based on an extensive library of more than 250 machine protocols.  Deep integration with the Manufacturing Data Engine unlocks rapid data intake into Google Cloud for processing machine and sensor data. The ability to deploy containerized applications and ML models to the edge enables new dimensions of use cases.

The exposed data can be further applied to a growing set of industry-specific use cases, such as:

  • Manufacturing analytics & insights, which helps manufacturers quickly create custom dashboards to visualize key data—from factory KPIs such as Overall Equipment Effectiveness (OEE), to individual machine sensor data. Integrated with the Manufacturing Data Engine, engineers and plant managers can automatically set up new machines and factories, enabling standardized dashboards, KPIs, and on-demand drill-downs into the data to uncover new insights opportunities throughout the factory. These can then be shared easily across the enterprise and with partners.
  • Machine-level anomaly detection, which helps manufacturers identify anomalies as they occur and provides alerts—leveraging Google Cloud’s Time Series Insights API—on real-time machine and sensor data such as noise, vibration, or temperature.
  • Predictive maintenance, which enables manufacturers to anticipate an asset’s need for service, helping reduce downtime and maintenance cost. Manufacturers can leverage ML models and high-accuracy AI optimizations that are deployable in weeks.

With Google’s new solutions, it is possible to collect data, normalize it, analyze it, then use it for strategic decisions providing factory-floor engineers with the tools to be self-sufficient. This is also an opportunity to introduce more engineers to AI-based engineering.

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[To share your insights with us, please write to sghosh@martechseries.com]

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