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Predictive Manufacturing – a step beyond Industry 4.0. The vision of predictive manufacturing has been impeded by the reality that existing AI solutions are not close enough to the machines, devices, and processes they are meant to optimize. MicroAI’s embedded and edge AI technologies make predictive manufacturing a reality.
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The MicroAI Predictive Manufacturing solution is powered by a full suite of next-generation AI-enabled products and supporting technologies.
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Mission-critical machines within the manufacturing, telecom, automotive, and infrastructure segments are transformed from opaque entities into assets that are fully transparent. This transparency delivers deeper insights that produce predictive
AI-enabled observability and intelligence that powers improvements in the performance of an entire factory ecosystem (single or multiple factories). Digital Factory establishes a single point of reference, promotes deep federated learning, and enables predictive manufacturing control.
A Kubernetes-based platform that combines intelligent workflows, predictive analytics, and visualization into a single platform. Launchpad provides rapid development, testing, and deployment of fully customized AI/ML capabilities for companies in the manufacturing segment.
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An embedded, self-correcting, semi-supervised learning engine that aggregates data from device and machine sensors to create a behavioral profile of the asset and then actively monitors for abnormal performance and cyber-security intrusions.
An edge-based, agentless, machine learning platform for optimization of IT and OT asset Ecosystems. AtomML+ brings centralized intelligence to groups of devices and machines to deliver optimized performance, enhanced cyber-security, and reduced cost.
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Regardless of the types of products being produced, companies within the manufacturing segment face many of the same challenges and obstacles. Many operations are struggling to close an intelligence gap that blocks the path to predictive manufacturing. Negative impacts include:
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The absence of intelligence embedded and trained at the machine MCU/MPU level restricts the ability to attain asset-specific insights and to develop predictive maintenance models.
Inability to collect, synthesize and analyze machine data locally inhibits the ability to automatically generate alerts and corrective actions. Assets often perform at suboptimal levels for extended periods of time.
Continued reliance on legacy preventive maintenance processes that are unable to self-adjust based on current real-time conditions of the asset. This often results in maintenance that is performed too early or too late.
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MicroAI’s Predictive Manufacturing solution embeds and trains predictive algorithms directly into manufacturing machines, lines, and processes. This embedded and edge intelligence provides developers, operators, and engineers with the predictive analytics required to achieve higher levels of operational efficiency and OEE. Capabilities that include:
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Live data is leveraged from a variety of devices, machines, and processes. MicroAI’s technology is agnostic to sensor values and types, creating a multi-variant model that utilizes AI inference analysis to generate a wide range of predictive analytics.
Multidimensional behavioral algorithms produce recursive analysis, training, and processing. This enables a continuous evolution of the AI model that takes place directly at the endpoint or the edge.
Presentation of real-time asset performance data via user-friendly, customizable, drag and drop dashboards. Data is customized to meet the specific requirements of various operational and business stakeholders.
Deeper, more intimate, more predictive insights into current and future asset health and performance. Manufacturing performance is optimized via acting upon predictive insights instead of static information.
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