Google has launched new solutions to unify manufacturing shop-floor data and improve factory floor visibility from the cloud. Manufacturing Data Engine and Manufacturing Connect are designed to connect siloed manufactured and assets and enable manufacturing analytics, AI-powered predictive maintenance, and machine-level anomaly detection.

Ford, Kyocera, and Phononic among are among early adopters of Google’s new manufacturing AI solutions. Google partners providing support for the new solutions include Cognizant, C3 AI, GFT, Intel, Litmus, Quantiphi, SoftServe, Sotec, and Splunk.

Manufacturing Data Engine is an end-to-end solution that processes, contextualises, and stores factory data on Google Cloud’s market-leading data platform. It provides a configurable and customisable 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 containerised applications and ML models to the edge enables new dimensions of use cases. Once data is centralised and harmonised by the Manufacturing Data Engine and Manufacturing Connect, it can then be used to address a growing set of industry-specific use cases, including:

Manufacturing analytics & insights, which helps manufacturers quickly create custom dashboards to visualise 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 standardised 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 optimisations that are deployable in weeks.

“Bridging gaps across systems and placing easy-to-use AI directly into the hands of manufacturing engineers leads to better results,” said Hans Thalbauer, Managing Director, Supply Chain and Manufacturing Industries, Google Cloud. “These new solutions can support workforce transformation initiatives by providing engineers with the tools to be self-sufficient, without the need for data scientists or additional integration code.”

“The growing amount of sensor data generated on our assembly lines creates an opportunity for smarter analytics around product quality, production efficiency and equipment health monitoring, but it also means new data intake and management challenges,” said Jason Ryska, Director Manufacturing Technology Development, Ford Motor Company. “We worked with Google Cloud to implement a data platform now operating on more than 100 key machines connected across two plants, streaming and storing over 25 million records per week. We’re gaining strong insights from the data that will help us implement predictive and preventive actions and continue to become even more efficient in our manufacturing plants.”

“With the tight integration of a powerful factory edge solution with Google Cloud, it is easier than ever for factories to tap into cloud capabilities,” said Masaharu Akieda, General Manager, Digital Solutions Division, KYOCERA Communication Systems Co., Ltd. “Google Cloud’s solutions enable a broader group of users beyond data scientists to quickly access, analyse and use data in a variety of use cases. We are excited to partner with Google Cloud as we implement new manufacturing solutions to optimise production operations and consistently increase quality.”

“As the global innovator of solid state cooling and heating technology, we’ve developed a sustainable manufacturing platform that uses less water, less electricity, and less chemical waste,” said Jason Ruppert, Chief Operations Officer, Phononic. “This partnership with Google Cloud allows us to contextualise data across all of our manufacturing processes – ultimately providing us the analytics and insights to optimise our operations and continue to bring to the world products that cool sustainably, reducing greenhouse gas (GhG) emissions and improving the environment.”

“The biggest challenge manufacturers face is collecting data from disparate factory systems and using that data to enable digital transformation,” said Vatsal Shah, Co-founder and CEO, Litmus. “Manufacturing Connect, co-developed with Litmus, bridges the gap between factory and Google Cloud, delivering the critical edge data connectivity and machine learning model deployment needed for closed loop AI. The Google Cloud and Litmus manufacturing solution will help enterprise customers maximise their AI investments and realise unmatched time-to-value.”

“By building modular solutions on the Manufacturing Data Engine from Google Cloud, such as Cognizant’s Asset Performance Excellence (APEx) offering, we are able to offer additional resources to deploy and scale solutions for our customers quickly and confidentially, as well as mitigate design and deployment challenges,” said Manoj Mehta, SVP, Global Head of Industry 4.0, IoT and Engineering, Cognizant. “As industrial transformation takes hold and a massive amount of information is garnered at the edge, putting this data to work, and extracting the most value from it is essential for operational efficiency,” said Christine Boles, VP, Network & Edge Group, General Manager, Industrial Solutions Division, Intel Corporation. “Integrating and optimising Google Cloud’s new manufacturing solutions on Intel edge products allows factories to unlock the potential for data analytics and running AI at the edge. This enables engineers to analyse, and act on, their siloed operational data in near real-time, bringing needed intelligence to improve operations and product quality.”