Flutura* Machine Intelligence Platform for Industrial Insight

Published: 11/05/2018  

Last Updated: 11/05/2018

Flutura* delivers next-generation industrial insight with machine intelligence platform running on Intel® architecture. Achieve the operational efficiency and accuracy for Industry 4.0 and IoT.

Executive Summary

Today’s factories run on a diverse set of complex equipment and robotics that makes comprehensive, data-driven management and holistic operational efficiency challenging. Flutura’s artificial intelligence (AI)-based Industrial Internet of Things (IIoT) platform, Cerebra*, powered by Intel® architecture, provides a depth and breadth of reliable industrial analytics designed to address key manufacturing requirements and move industry forward.

Challenges

Industry and manufacturing rely on diagnostics for efficient operations, compliance, machine maintenance, and worker productivity and safety. But getting accurate data and a holistic understanding of factories—in essence, taking advantage of the benefits of IoT and Industry 4.0—presents numerous challenges. These include diverse, proprietary technologies; incompatible systems and protocols; labor-intensive compliance and maintenance; and limitations to cross-system and cross-factory control.

Solution

Flutura Decision Sciences captures previously undetected machine signals that impact industrial outcomes. It does so by mining streaming IoT sensor, asset, and operations data using its AI-based IIoT platform, Cerebra, combined with Intel® architecture-powered intelligent gateways.

The Cerebra and Intel® solution unlocks a deep level of critical IIoT data via a diverse set of sensors with high-velocity data streams. The solution is designed for manufacturers, equipment providers, and application developers developing and deploying smart industry solutions.

With Cerebra, equipment owners can manage and optimize machine performance in production operations. In addition, industrial and commercial machinery manufacturers can use Cerebra to create new analytics-driven business models and services, such as predictive asset maintenance.

Flutura with the ecosystem
Flutura works with the ecosystem to provide end-to-end smart solutions for industrial manufacturing

Cerebra’s state-of-the-art machine diagnostics and prognostics algorithms enable asset health assessment, calibration, performance benchmarking, safety risk assessment, condition-based maintenance, and other asset-centric functions.

Benefits include

  • Optimised performance and benchmarking
  • Reduced cost of field maintenance with remote digital diagnostics
  • Proactive, predictive maintenance with algorithmic spare parts refurbishment
  • Guaranteed uptime
  • New recurrent, predictable digital revenue streams
  • Remote monitoring and control

Flutura’s holistic asset approach integrates physics (based on first principles), heuristics (based on experiential learning), and machine learning (based on AI) to mine often untapped machine signals. By increasing industrial intelligence, Flutura’s next-generation signal detection platforms running on Intel architecture are helping industrial manufacturing companies meet guaranteed outcomes for asset/residual life, factory yields, and energy savings. The solution supports a wide range of industrial assets, including sensors, engines, meters, boilers, oil pressure units, batteries, chillers, mixers, and weighing and packaging equipment.

fault prediction with Flutura from Cerebra
With Flutura’s Cerebra and Intel® architecture-based IoT gateways, industry can mine deeper value from existing systems and subsystems for a range of use cases, such as fault prediction

Key features for industry

Improve operations
  • Prognostics and diagnostics for industry and Industrial IoT
  • Advanced diagnostic algorithms for equipment health detection
  • Prebuilt machine diagnostic tests
  • Automated predictor ranking
Increase industrial intelligence
  • Advanced diagnostic algorithms for equipment health detection
  • Prebuilt machine diagnostic tests
  • Automated predictor ranking
  • Machine learning from billions of machine events
  • Multidimensional conditional probability algorithms for fault detection
  • Action-oriented real-time nanoapps machine tweets
Achieve holistic insight
  • Integration with workload data from internal systems
  • Triangulation of signals across fragmented data pools, including historical data, SCADA, PLC, maintenance systems, and ambient conditions
  • Intelligence at the edge
  • Automated performance benchmarking
  • Persona-specific user experience

Key features for OEMS

Speed time to market

Out-of-the-box equipment subsystems and fault models for faster time to market

Scale industrial equipment development

Scale value offerings across varied equipment classes

Success Stories

Flutura’s smart industry solutions powered by Intel architecture are providing real-world advantages in manufacturing facilities worldwide.

Shale gas equipment OEM

Enabling asset as a service
Challenges
  • Critical equipment downtime resulting in up to USD 3 million of hourly losses
  • Need for operational efficiency due to low oil prices
  • Need to retain competitive edge due to rapid commoditization
  • Need to increase asset life
  • Increase in quality and materials costs due to lack of know-how and experience of field personnel in handling sophisticated equipment
Solution outcomes
  • Real-time tracking of asset health, utilization, and performance
  • Real-time alerts triggering proactive maintenance and parts replacement
shale gas equipment O E M

specialty chemicals

Specialty chemicals

Optimizing yield
Challenges
  • Increased reprocessing costs due to fluctuating quality outcomes
  • Negative impact on customer satisfaction
  • Unknown causal factors
Solution outcomes
  • Critical signals surfaced from line affecting quality fluctuations
  • Golden batch benchmarking
  • Real-time tracking of variations from golden batch and recalibration of manufacturing process

Heavy engineering

Preventing unplanned engine shutdown events
Challenges
  • Relying on manual methodologies for notification of alarms
  • Not enough time between alarms and engine slowdown/shutdown events, resulting in engine failures and sometimes catastrophic incidents
  • Need for a proactive early warning system
Solution outcomes
  • Early warning system for engines, propulsion systems, and gearboxes fitted on the ship
  • Identifies critical signals with high accuracy 30 to 60 minutes prior to unplanned events
  • Includes edge- and cloud-based deployments
heavy engineering

oil and gas midstream

Oil & gas, midstream

Command central intelligence and edge intelligence of marine LNG carriers
Challenges
  • Existing command center responding manually via satellite calls
  • Ship operators notifying command center after they noticed an abnormal event
  • Command center team operating in a reactive fashion with limited data input
Solution outcomes
  • Edge intelligence offers optimized data transfer and reduced latency for safety situation response
  • Central intelligence now digital and therefore driving proactive responses to incidents
  • Helped the customer launch a differentiated offering by leveraging domain and data-led insight

Advancing Edge and Cloud Intelligence

Intel and its ecosystem help businesses use the IoT to solve long-standing industry-specific challenges. Quickly develop IoT solutions that connect things, collect data, and derive insights with Intel’s portfolio of open and scalable solutions so you can reduce costs, improve productivity, and increase revenue.

Intel® technologies support the rigorous requirements for programmable logic controllers (PLCs), industrial PCs (IPCs), human machine interfaces (HMIs), robotics, machine vision, and many other industrial applications.

How it works in brief

Cerebra provides insight at the edge—its machine intelligence platform combines with high-performance Intel architecture-powered IoT gateways to listen to machine signals and capture micro-episodes indicative of failures or anomalies.

The Cerebra platform works with edge analytics tools analytics and computing power to bring together first principles, heuristics, and statistics and create “grey box” models that detect the slightest anomalies in an asset and predict potential faults. In order to triangulate monetizable signals, the platform looks across fragmented data pools, such as machine events, alarms, sensor streams (vs. single stream signal detection), and calibration changes.

The seamlessly integrated user interface highlights key early warning signals essential to mitigate failure risk and helps to prevent revenue loss.

Cerebra gathers data of industrial assets
Cerebra combines with an Intel® architecture-based gateway to gather data from a broad array of industrial assets

Cerebra machine diagnostics and prognostics

Increase factory-wide visibility into assets, operations, and applications.

Connected assets

Assessment
  • Low latency, deep edge signal detection from IoT sensor fabric
  • 360-degree model of assets, spanning calibration, operator, alarms, maintenance, and systems
  • Smart signaling transmission to reduce network monitoring costs
  • Real-time streaming edge diagnostics monitoring loop effectiveness
  • Next-gen situational awareness for industrial machinery
  • Optimisation of industrial equipment
  • Reduce downtime
Diagnostics
  • Pinpoint failure mode initiation
  • Forensics on industrial failure signature
  • Preventive symptom identification for electromechanical machinery
  • Compute residual useful life (RUL) from digital and IoT sensors
  • Hundreds of prebuilt asset diagnostic tests for fault detection and isolation (FDI)
  • Understand machine operating behaviour by failure modes, duty cycle, and asset usage
Prognostics
  • Failure prognostics via integrated physics, statistics, and heuristic models on sensor streams
  • Advanced machine learning algorithms learn and detect fault mode signatures
  • Triangulate signals across massive industrial data pools spanning sensors, operators, and maintenance events
  • Power next-gen digital business models to unlock massive value for industrial manufacturers

Connected operations

Benchmarking

Benchmark operations by integrating data from assets, people, and processes together

Diagnostics
  • Improve product yield and quality
  • Reduce waste
Prognostics
  • Predict equipment failure and move to proactive maintenance
  • Make factories safer and smarter

The Foundation for IoT

The Flutura solution is just one example of how Intel works closely with the IoT ecosystem to help enable smart IoT solutions based on standardized, scalable, reliable Intel® architecture and software. These solutions range from sensors and gateways to server and cloud technologies to data analytics algorithms and applications. Intel provides essential end-to-end capabilities—performance, manageability, connectivity, analytics, and advanced security—to help accelerate innovation and increase revenue for enterprises, service providers, and industry.

Conclusion

With Flutura Decision Sciences and Intel, industrial manufacturing can achieve the advantages of Industry 4.0 and mine more data from existing equipment and subsystems. From increasing operational efficiency and actionable intelligence to maximizing investments and future-proofing factories, Flutura Decision Sciences and Intel are helping industry optimize and compete.

About Flutura

Flutura Decision Sciences and Analytics is an IoT intelligence company that is powering new monetized business models using machine signals in the engineering and energy industry. These new business models impact operational, process, and asset efficiency outcomes. Flutura’s main offices are located in Houston, Palo Alto, and Bengaluru, India.

Learn More

For more information about Flutura Decision Sciences, please visit flutura.com.

For more information about Intel® IoT Technology and the Intel IoT Solutions Alliance, please visit intel.com/iot.

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.