Engineering Analytics Services (EAS)
Welcome to the world of zettabytes! Companies today have access to a massive, unearthed gold mine – it’s called data.
STATE OF THE MARKET
Welcome to the world of zettabytes! Companies today have access to a massive, unearthed gold mine – it’s called data. According to ARC Advisory, the Industrial Internet of Things combined with analytics offers new approaches for condition monitoring and predictive maintenance. With integration and business process automation, this emerging market dynamic will increase the value of a modern asset management and user adoption. End users are making a connection between typical Enterprise Asset Management objectives (uptime, asset longevity, cost control, and safety) and business metrics (revenue, cash conservation, profitability, and risk management).
The challenges that enterprises face in building & executing the right data analytics strategy include:
- Understanding the right data to be captured for their business
- Poor visibility on key issues that can be solved using data
- Non-availability of a unified data platform – multiple data sources exist in silos
- Shortage of data scientists who could build the right strategy to address potential growth opportunities for the organization
- A proper ROI methodology to track and monitor the investments
- Recognized by NASSCOM in “Top 50 Excellence in Analytics 2015”
- Developed BIG data solutions in Industrial, Utilities and Transportation space
- A Strong ecosystem of academia & partners.
- Technology partnership with companies such as Splunk, Tableau, Qlik, SS, IBM, Microsoft, MathWorks and Amazon.
- Vendor-neutral system integrator with experience in multiple platforms
- Big Data platforms such as Hadoop, Spark, Kafka, Splunk, non-Hadoop systems,
- NoSQL data stores such as Mongo DB, Hbase
- Analytics tools like R, SAS, Python, MATLAB and SPSS
- Visualization tools such as Tableau, QlikView, Spotfire & other open source software
- Readily deployable data models that can enable deep insights in areas such as Vibration Analytics, demand
- Forecasting, Computer Vision, Condition based Maintenance and Warranty analytics.
- Demand Forecasting & Outage management for Utility OEM - A Deep learning predictive analytics solution that forecasts power demand based on historic data generation patterns - improved forecasting accuracy by up to 90%
- Utility Analytics - End to End Smart Meter data analytics and network management solutions for a leading US company. The framework enables connectivity of million meters, analyses energy consumption data (-10Mn records per day) and performs various analytics to provide real-time insights into smart utility operations
- Vehicle Analytics and Fleet Optimization of Construction Equipment - Deployed machine learning solution that predicts equipment health, performs fleet management and optimization (-fleet of 500 trucks)
- Condition based maintenance of rotating equipment - Edge Analytics solution that provides predictive insights into equipment health, operations and failures - reduced maintenance cost by 16%
- Image Processing & Analytics - Developed a deep learning image analytics model (using computer vision) for production line automation, Warranty Analytics for heavy machinery assets- Analytics framework to analyse vendor performance based on assets field failures and warranty claims. Cost savings of approximately 52 Million.