Predictive Maintenance

Machine data is securely streamed from equipment sensors to a central repository using industrial data protocols and gateways.  IoT behavior analytics are applied to predict failures before they arise.

Implementing predictive maintenance typically starts with rule-based alerts until sufficient data is collected, at which time machine-learning algorithms can be applied to identify complex behavior patterns and anomalies.

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IoT Use Case: Predictive Maintenance
IoT Use Case: Predictive Maintenance
  • Configure rule-based analytics in the IoT Model to define use-cases for asset failure
  • Monitor the occurrences of these rules to deploy immediate rule-based predictive maintenance
  • Apply advanced predictive analytics and anomaly detection algorithms once enough data has been collected
  • Leverage predictive maintenance to lower service costs and improve productivity - to impact the bottom line
IoT Use Case: Remote Asset Monitoring
IoT Use Case: Remote Asset Monitoring

Remote Asset Monitoring

Factories and machinery OEMs get deep visibility into their equipment health and actionable insights to maximize overall equipment effectiveness (OEE), reduce maintenance costs, and cut downtime.

The Condition Monitoring IoT use case involves data acquisition, data analytics, dashboards, and alerts – this is the most common and foundational IoT use case for manufacturers.

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Remote Asset Monitoring

Factories and machinery OEMs get deep visibility into their equipment health and actionable insights to maximize overall equipment effectiveness (OEE), reduce maintenance costs, and cut downtime.

Seebo Condition Monitoring solution includes data acquisition, data analytics, dashboards, and alerts – delivering business outcomes with unmatched speed-to-market and predictable ROI.

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IoT Use Case: Remote Asset Monitoring
IoT Use Case: Remote Asset Monitoring
  • Maintenance becomes proactive and timely, and repairs are done before critical damage occurs - reducing downtime
  • Leverage digital twin visualization for remote diagnostics and to quickly identify root cause of equipment failures
  • Improve compliance adherence with continuous logging and monitoring of conditions affecting your assets
  • Understand equipment behavior patterns to affect future iterations of product design and engineering

IoT Prototyping

Empower rapid, iterative, and collaborative prototyping to deliver product concepts for market validation – at the lowest cost and risks.

Leverage digital prototyping – ahead of physical prototyping – to simulate product concepts, gain internal buy-in, and minimize discarded physical prototypes.

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IoT Use Case: IoT Prototyping
IoT Use Case: IoT Prototyping
  • Validate the functionality and completeness of your concepts with a fully-functional digital prototype
  • Collaborate with all relevant stakeholders to get buy-in, leveraging embedded-discussions and easy sharing
  • Facilitate Design Thinking and support Stage Gating for new product development
  • Leverage an IoT Marketplace with pre-vetted external partners and suppliers for quickest speed-t0-market
IoT Use Case: Digital Twin
IoT Use Case: Digital Twin

Digital Twin

Compare design to actual performance with a Digital Twin that accurately tracks products, processes, and systems in real time. In this IoT use case, engineering teams accurately test optimization ideas by adjusting parameters in the twin, without risking harm to production.

Leverage runtime and usage data collected by the twin by feeding it into the development and manufacturing process, increasing uptime and production throughput.

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Digital Twin

Compare design to actual performance with a Digital Twin that accurately tracks products, processes, and systems in real time. Accurately test optimization ideas by adjusting parameters in the twin, without risking harm to production.

Leverage runtime and customer usage data collected by the twin by feeding it into the development and manufacturing process, increasing product margins, customer satisfaction, and market share.

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IoT Use Case: Digital Twin
IoT Use Case: Digital Twin
  • Construct a digital twin of a product by visually modeling and simulating its behaviors
  • Monitor the product’s behavior in-market, to gain real-time visibility into performance and highlight critical areas that require immediate attention
  • Provide engineers, product managers, and designers with a better understanding of machines and processes, leading to better product design
  • Construct processes that are more efficient, saving time and resources, especially those involved in creating prototypes and testing them

Recurring Revenue Streams

OEMs create new recurring revenue streams and increase asset value by turning products into data-driven services.

By building new subscription-based business models, you can offer analytics-based digital services to customers, strengthen market differentiation, and continue to see revenue from a customer during the lifetime of a single product.

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IoT Use Case: Recurring Revenue Streams
IoT Use Case: Recurring Revenue Streams
  • Provide product-driven data services to customers to optimize their operations and increase customer satisfaction
  • Generate new service-based business models that strengthen brand leadership
  • Drive product adoption by offering new, analytics-based product features, such as root-cause analysis
  • Use services to increase the profit margin of a single product, as well as its profit lifespan.
IoT Use Case: Factory 4.0
IoT Use Case: Factory 4.0

Factory 4.0 Design

Use the Seebo platform to explore how your factory or plant can be transformed with IoT for a range of operational benefits.

Visualize the layout and functionality for any connected factory. Model and simulate machine-to-machine communications and interdependencies between machine throughputs to optimize production and maximize overall equipment efficiency (OEE).

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Factory 4.0 Design

Use the Seebo platform to explore how your factory or plant can be transformed with IoT for a range of operational benefits.

Visualize the layout and functionality for any connected factory. Model and simulate machine-to-machine communications and interdependencies between machine throughputs to optimize production and maximize overall equipment efficiency (OEE).

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IoT Use Case: Factory 4.0
IoT Use Case: Factory 4.0
  • Increase productivity and efficiency with optimized machine-to-machine processes
  • Gaining visibility into factory floor operations with real-time performance dashboards
  • Simulate production process changes to understand performance impact before implementation
  • Iteratively improve business outcomes by making making incremental process optimizations