Hexaview Technologies

Transformation of Business Operations & Device Maintenance via Predictive KPIs

Business Scenario

A wealth management firm assisting their clients in financial planning, asset management, tax management, Investment Advisory, and Portfolio Management incurred high maintenance costs. They wanted to manage their risks of device failure.

Client’s Challenges

  • Predict KPIs to take proactive steps for effective operating & maintenance of the devices before it fails to operate.
  • Reduce effective service & maintenance costs.

Hexaview’s Solution

  • Implemented Machine Learning capabilities to process the historical data about different input & load parameters of the IoT-enabled devices & performance data.
  • Formulated various KPIs for the device like life expectancy for dynamic components & fault probability based on real-time operational & performance parameters.

Tools & Technologies Used

  • Languages: Spring boot, Spark Hadoop HDFS, Hive, Impala & React JS.
  • Algorithms: PCA, Decision Tree Classification for Rule-based engine, SVM Regression.
  • Libraries: SparkStreaming, SparkML, PySpark+Python Scikit Learn.

Impact of the implementation

  • Effective maintenance policy, the servicing schedule for the devices, and predicting component fault saved costs and downtime for the company & the end user.

Key success factors

Empowering our solutions with AI & ML helped us in creating more sustainable products for our clients.

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