Predictive maintenance

Use Lentiq for Predictive Maintenance

Gather sensor data from your machines, aggregate data, push intelligence at the edge and perform predictions based on historical data in a central location while complying with increasing regulatory compliances.

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Why predictive maintenance is important

Predictive maintenance can help improve business operations and reduce overall costs while increasing the OEE of all machines in a factory, fleet, production line. Some of the most important improvement points are:

  • increasing uptime for mission-critical machines
  • reducing maintenance and operational interruption costs
  • extending lifetime for ageing assets
  • reducing safety, health, environment and quality risks
Reduce maintenance time by 20-50%
Increase equipment uptime and availability by 10-20%
Reduce overall maintenance costs by 5-10%

Predictive maintenance using a decentralized data lake

Decrease time-to-value, be agile and obey regulatory compliances

With Lentiq, each disparate factory, production site, fleet operation site within a larger organization can process data closer to the source, promote local data science talent by pushing part of the analysis closer to the edge. The central data team can create machine specific models, define best practices in data preprocessing, push models to the edge to be perform predictions on local data. Model retraining can also be performed in the central/remote location using relevant historical information.

Simplify implementation with Lentiq

A decentralized data lake is the best approach for the IoT industry enabling a microservices-oriented approach that decouples the data processing logic from the computing resource management. Centralized data lakes add an extra overhead to the data collection process as well as analytics, resulting in being extremely expensive and inefficient.

Our platform provides as a service resources, application, data and metadata, notebooks management and helps data teams be independent and focus on data analysis and insight extraction closer to where the data is generated, while also allowing different data pools to communicate data between them. Lentiq empowers users to:

  • Run your notebooks and applications stack in multiple clouds without changing a thing
  • Deploy use case specific application stacks in projects and gain velocity when analyzing data
  • Easily develop and scale machine learning models in notebook environments packed with everything you need
  • Put machine learning models in production through the "reusable code block" technology in seconds
  • Share data across multiple data pools
  • Build an internal knowledge repository out of models deployed in multiple regions and share best practices

How to start?

Access and explore data

Understand data and perform exploratory analysis

Preprocess data

MClean, transform, validate and prepare data for analytics and model training

Develop predictive models

Benchmark multiple predictive machine learning techniques and tweak the best scoring model

Integrate into the system

Generate reports, alerts, build data-driven dashboards that can support the decision-making and improve business processes.

Do you want to try Lentiq with your team?

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