Manufacturing Data Engine
For manufacturers looking to use AI to gain a competitive edge, dismantling the data silos between IT (business data) and OT (industrial data) is essential. Google Cloud is thrilled to present the most recent version of its flagship product, Manufacturing Data Engine, at Hannover Messe this week. This solution will help manufacturers realise the full value of their operational data and accelerate AI transformation both on and off the factory floor.
Google Cloud provided several improvements to Manufacturing Data Engine in 2024 to improve the integration of OT and IT data, along with preliminary technological foundation additions to integrate MDE with Cortex Framework. The use of Cortex Framework, which enables users to quickly gain business insights from their enterprise IT data, has expanded at the same time, encompassing not just the conventional enterprise IT data sources such as ERP, CRM, and ESG but also marketing and social media.
Building on success, the most recent Manufacturing Data Engine release brings IT/OT integration journey to a close and adds important new features like Development Mode, Configuration Packages, and historical metadata linking to improve data grounding of IT and OT data and accelerate AI results. These developments enable producers to use their data more effectively and gain deeper insights.
Innovation Acceleration with Development Mode
Manufacturers can remove configuration objects more easily with Development Mode, which is especially useful in development and proof-of-concept (PoC) settings. By making it simpler and less time-consuming to test out new data models, this aids in quickening the innovation cycle.
Take in time-shifted data and relate it to historical metadata
This feature maps the appropriate metadata instances which are enhanced with a “valid from” timestamp using event-time. This ensures that your data is accurately represented in the past by allowing manufacturers to import historical data at a later time and having Manufacturing Data Engine insert it into the appropriate location in the timeline. Manufacturers who must import data out of sequence will find this useful, since it facilitates the analysis of past trends and patterns to improve operations.
IT and OT Simplified with Configuration Packages
Through the creation and packaging of Manufacturing Data Engine configurations tailored to specific industries and use cases, MDE Configuration Packages offer a potent new method of integrating factory floor data with your core enterprise systems. By encapsulating their OT data from Manufacturing Data Engine in standardised schemas for integration with supply chain, marketing, financial, and sustainability data within Cortex Framework, manufacturers can close the gap between IT and OT.
A variety of game-changing use cases are made possible by these potent new features as well as quicker IT and OT data integration.
Manufacturers, for instance, can properly estimate financial consequences by comparing machine performance with ERP financial data, or they can visualise optimising production schedules based on real-time demand signals from their marketing efforts. By examining energy use in conjunction with production output, they can improve sustainability activities.
Manufacturers can obtain a comprehensive understanding of their operations by contextualising multimodal data from cameras, sensors, and machines with data from Cortex Framework.
Opening out new applications for Gen AI
In the past, manufacturers could use Manufacturing Data Engine to connect OT data with Google AI services for flexible and scalable visual quality control or faster issue resolution using ML-based anomaly detection.
By making it simpler and quicker to combine IT and OT data for the purpose of establishing large language models (LLMs) for generative AI applications, it is opening up even more possibilities for manufacturing intelligence with this release. For generative analytics and insights, Conversational Analytics enables you to communicate with your BigQuery data, Sheets, Looker Explores/Reports/Dashboards, and more. Imagine being able to quickly request and track down the outlier portion of the production quality data from your factory floor in order to isolate the issue after identifying an anomaly in your existing open support cases from your customer service system.
With the help of Google Cloud’s AI capabilities and the most recent release of Manufacturing Data Engine with Cortex Framework, manufacturers may get instantaneous, data-driven insights that will enable them to make faster, more intelligent decisions throughout their whole value chain.
Partner ecosystem: Using Deloitte to drive client success
Google Cloud take pride in collaborating with a strong network of partners who play a key role in assisting clients in achieving their industrial digital transformation objectives.
It is particularly pleased to announce that Deloitte has introduced a bundled services offering for it most recent Manufacturing Data Engine release, allowing clients to take advantage of the new features right away with services from a reliable partner. To find out how Deloitte can support your activities, get in touch with them or stop by their demo booth at Google Cloud Next and the Google Cloud booth at Hannover Messe.
Considering the future
In it’s quest to equip manufacturers with the resources they require to prosper in the digital era, Google Cloud’s most recent release of Manufacturing Data Engine marks an important turning point. Google Cloud look forward to working with you on your industrial transformation journey and are dedicated to ongoing innovation.
How AI will assist in resolving five pressing manufacturing issues
B2B customers want experiences that are digitally first
Business buyers are eschewing conventional, linear sales cycles in favour of consumer-like behaviours. By 2025, 80% of business-to-business sales will be made online, predicts Gartner. In order to provide smooth, customised experiences throughout the whole consumer journey, this change necessitates a digital-first strategy that goes beyond online stores.
AI-powered user experiences can assist top manufacturers in addressing this behavioural shift. AI can personalise product recommendations, speed up online ordering, and provide real-time customer assistance to tech-savvy consumers.
Resilience cannot be compromised
The pandemic revealed how brittle global supply chains are, and interruptions are still frequent. Businesses lose out on an average of $1.6 trillion in revenue growth possibilities annually due to supply chain disruptions, according to Accenture. It takes a proactive strategy to boost resilience and handle disruption; it’s not only a logistical problem. To detect and reduce possible hazards, manufacturers must increase visibility, forecast better, and use technology.
Multimodal AI improves supply chain management. By combining sensor data, visual inspections, and logistics tracking, Artificial Intelligence can provide a complete supply chain picture and respond quickly to disturbances.
Closing digital skills gaps
Technology’s rapid development is worsening the manufacturing sector’s workforce shortage. Deloitte and The Manufacturing Institute estimate that 3.8 million net additional manufacturing workers may be needed between 2024 and 2033. If the skills gap is not addressed, 1.9 million of these roles may go unfilled. This talent split hinders long-term growth, innovation, and productivity. Multiple strategies are needed to close the industrial talent gap. Manufacturers must invest in retraining and upskilling their present staff and attract and retain top talent with attractive work environments and competitive benefits.
Multimodal assisted search solutions empower current employees and speed up training by providing rapid access to relevant text, audio, and video material. With the use of these tools, users may ask questions aloud, get spoken responses or manual summaries, listen to detailed instructions, and even create training materials that are based on videos, which speeds up learning.
A business mandate is sustainability (enhanced by AI agents)
Business performance and sustainability are now closely related, with 88% of manufacturers acknowledging the importance of technology in being green. Regulations are strengthening environmental standards and consumers seek more sustainable products. From raw material procurement to waste reduction and carbon footprint reduction, organizations must adopt sustainable value chain processes.
AI agents can automate data collecting and analysis to handle complex sustainability reporting. Agents can track appropriate disclosures, confirm adherence to required disclaimers, and cross-reference the components and materials used with sources to aid with compliance.
Unlocking holistic insights
Siloed data from several departments and systems is used by many manufacturing companies. The data is also diverse, including IT from enterprise systems, ET from design and simulation tools, and OT from the shop floor. When combined with sector-specific data formats, structures, and real-time needs, this fragmentation might make it harder for manufacturers to understand their operations. Ineffective decision-making and lost optimisation opportunities occur. Dismantling these silos and integrating OT, IT, and ET data is necessary to fully employ AI and make educated business decisions.
More data from manufacturers increases risk, making AI-powered security essential. In addition to facilitating threat intelligence, which includes prevention, detection, monitoring, and remediation, AI can identify abnormalities and guarantee data integrity across networked systems, protecting sensitive data.
How can manufacturers overcome these five obstacles with the use of MDE and Cortex Framework?
A single data and AI layer offered by Manufacturing Data Engine makes it easier to analyse multimodal data for improved supply chain visibility, supports assistive search to fill skills shortages, and empowers AI agents to maximise sustainability projects. MDE contextualises OT, IT, and ET data for richer insights and stronger AI applications. Manufacturing Data Engine helps create a digital thread that ensures traceability and product lifecycle understanding by linking data to its source. Cortex Framework also integrates corporate and manufacturing data, enabling use cases like leveraging machine data to assess financial impact and demand signals to optimise production planning.