Simplify the complexity of anomaly detection in equipment and ensure safety with real-time data insights
Prevent unscheduled maintenance and quality issues early in the production process to scale your organization quicker
Minimize error-prone human inspection by automating the process of identifying and resolving deviations
Leverage Data-driven Approach
Gather and access all measurable data through user-friendly dashboards with the ability to make changes
- Real-time intelligence based on ML algorithms
- Mathematical models for visualization and anomaly detection tailored for each dataset
- Concise data visualization through dashboards and analytical reports with detailed actionable insights
- User feedback is used for the solution recalibration and improvement
Path to Value
- Understand the operational processes and how equipment works
- Collect and process data from industrial systems and equipment
- Apply the existing ML approaches or build a customized one
- Continuously train end-users/engineers how to use the solution properly
- Transform your business via actual integration into operational processes
Case for Digital Innovation Company
Convolutional Neural Network for Manufacturing NeedsA digital initiatives provider was looking to develop a Computer Vision and IoT solution for their metal manufacturing client. See how Infopulse trained and implemented a convolutional neural network (CNN) that helped the client save development costs and achieve high fault tolerance.
Case for Large Group of Steel & Mining Companies
Reducing Production Defects with Predictive Quality ModelsThe customer needed to implement an advanced analytics solution to predict and prevent defects in their steel sheet manufacturing. Infopulse team built predictive quality models that helped decrease the number of defects and costs for their detection.
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