Factory™
MicroAI Factory – The Digital Factory of the Future. An Edge-native AI platform that provides OEE optimization, asset lifecycle management, predictive analytics, intelligent workflows, and data visualization.
Challenges for Manufacturers
The vision of predictive manufacturing has been impeded by the reality that existing AI solutions are not close enough to the manufacturing machines, devices, and processes that they are meant to optimize. This problem is compounded by having to send asset data to the cloud for processing. The pathway to the digital factory can be impeded by:
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Shallow Asset Observability
Manufacturing machines and devices lack the deep observability required to produce deep insights into performance and security. Many assets are not fully optimized.
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Lack of Self-Monitoring
Machines and devices have no ability to self-monitor or self-report. Critical performance insights go undetected and/or unreported.
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Inefficient Maintenance Procedures
Continued reliance on legacy preventive maintenance methodologies creates unnecessary downtimes. Maintenance based on empirical data vs personalized predictive insights.
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Siloed Supply Chain Management
Lack of AI-enabled analytics that create an holistic view of the entire supply chain. No ability to predict and mitigate supply issues.
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OEE Barriers
Many manufactures have stalled at OEE levels of 70 to 75%. Improved visibility, automation, and speed-of-insights is required to reach OEE scores of 80 to 85%.
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Security Vulnerabilities
Factory ecosystems are prime targets for cyber-criminals due to a lack of edge and embedded AI security protocols. Machines and their data can be severely compromised by a wide range of Zero-day attacks.
MicroAI Factory – Digital and Intelligent
MicroAI Factory was developed specifically to provide manufactures with AI-enabled intelligence and insights that improve factory floor performance. MicroAI Factory establishes a single point of reference, promotes deep federated learning, and creates accountability for factories on a global scale.
How Does MicroAI Factory Work?
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Asset Data Acquisition
Data is leveraged from a variety of IoT devices and machines. MicroAI Factory is agnostic to sensor values and types. It creates a multi-variant model that utilizes AI inference analysis to generate a wide range of predictive analytics.
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Local Analysis
Device and machine performance data is synthesized and analyzed locally—in real time. Sensitive data is also stored locally, minimizing the amount of data that is transferred to the cloud. Analytic latency is eliminated, and exposure of data reduced.
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Behavioral Algorithms
MicroAI Factory utilizes multidimensional behavioral algorithms to produce recursive analysis, training, and processing. This enables a continuous evolution of the Edge-native AI model that takes place directly on the endpoint.
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Analytics and Alerts
AI at the extreme edge provides deeper, more intimate, insights into asset health and performance that have not been available with traditional AI solutions. Asset optimization is achieved via intelligence instead of assumptions.
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Data Visualization
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.
The Predictive Factory Realized
With MicroAI Factory, operations can now fully evolve into a digital, predictive, manufacturing state that delivers the following features and values:
Feature |
Value |
| Centralized, self-contained, endpoint-based, performance monitoring | 
Deeper observability: Provides real-time device and machine-centric performance monitoring and reporting
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| Edge-native AI embedded and trained into the asset endpoint | 
Predictive insights: Provides predictive analytics that mitigate the impact of performance issues and that enable a transition to predictive maintenance
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| Flexible and scalable implementation | 
Single or multiple factory coverage: Can be integrated into a single factory or scaled across an entire network of factories, creating a network intelligence
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| Historical trend analysis at the individual machine, device, process, or factory level | 
Predictive manufacturing: Enables the prediction of future asset and process behavior as well as productively levels of lines and shifts
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| Embedded intelligent workflows that learn and evolve | 
Optimized processes: Improves process performance, eliminates redundancy, and minimizes human intervention
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| Customizable, scalable, and asset-specific security algorithms | 
Zero Trust Cyber Security: Provides quicker detection and response to Zero-Day cyber-attacks (detection in minutes vs days)
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| All the above | 
Asset optimization, better control, reduced costs, higher OEE, improved security
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Rapid and Cost-Effective Deployment
Unlike other solutions on the market, MicroAI Factory can be deployed and providing predictive factory benefits within a matter of weeks. MicroAI Factory eliminates the prohibitive cost, resource consumption, and risk associated with other AI-enablement products. Deployment advantages include:
- A lightweight, small footprint, digital factory platform that can be rapidly deployed and quickly scaled
- A self-learning, self-adjusting platform that does not rely on heavy human support to onboard
- A “Digital Factory in a Box” that does not require external hardware or software support systems
- MicroAI Factory can be networked across multiple facilities to create a complete network of manufacturing intelligence
- Lower cost, quicker deployment, more comprehensive, less reliant on external support, and faster ROI
Digital Factory of the Future
MicroAI Factory, an AI-Driven Analytics platform, combines lifecycle management, operational excellence, automated reporting, and workflow management capabilities into a single platform to accelerate the digital factory. The proven platform was built to improve manufacturer’s O.E.E. by delivering historical and real-time analysis of Productivity, Machines and Operators. The platform establishes a single reference, promotes deep federated learning and accountability for factories on a global scale.
- Continuous Process Improvements (Kaizen)
- Predictive Manufacturing(Deeper insights to OEE improvement)
- Track Suppliers, Materials and Quality to help in Supply Chain Management
- Single Pane view of the whole operation
- Predictive Maintenance (Predict Machine Outage)
- Develop operational insights into energy consumption, environment for sustainable operations
How we deliver end-to-end solution
We bring in comprehensive ecosystem of partners and in house capabilities to rapidly deliver end-to-end transformative solutions for rapid value realization
Causality Analysis and Feedback Loop
- The causality can be further analyzed by the SMEs and operators for corrective actions
- MicroAI provides automatic generation and assignment of causality
- End to end workflow enabled for anomaly detection , RCA and work order for remediation.
- MicroAI can report across all causality of OEE impacting event providing operations much better insight into fixing the root of the issue
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Alert Generation
AI Generates Anomaly
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SME Classifies Alert
Data Signature is classified and fed back to model
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Alert on Similar Data Signature
X% Confidence Alert Generated
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Reinforcement
SME Validates if Classified Alert was Correct
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Corrective Action
SME Lists Corrective Action Steps for Classified Events
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Automation
SME enables Automates Corrective Action for high-confidence, classified Events
