The Challenge


Procogia’s Approach

  • Designed logical and physical databases (3NF) from scratch, considering business requirements for staging data and processed data for the web-app with triggers, stored procedures, and views.
  • Created ETL scripts that run every day in batch processing to load data from the historian database to the in-house staging database.
  • Developed a complex R Shiny web application for 8 plant units and its respected trains (Total: 8 Menu-Items and 56 Sub-Menu-Items) through shiny modules with various inputs to analyze time-series data.
  • Deployed the app on RStudio Connect with load-balancing and user controls, but it could be installed and run locally through a docker container or deployed as an R package (golem philosophy) with minor patchwork.

The Results


  • Provided a plant-wide web application to analyze various domain-specific tags and trends for chemical gasification processes in plant units using IoT sensors data for multi-level internal stakeholders from senior upper-level management.
  • Allowed users to make smart decisions by ensuring the plant is running smoothly and minimizing downtimes.
  • Reduced a significant amount of time of data preparation for manual reporting and sudden breakdown times.
  • Modernized the Shiny app, reducing user wait time, ensuring reproducibility, and improving the app’s performance.
  • Enabled the company to make data-driven decisions, thus improving operational efficiency and providing new insights.
  • Upskilled the team in using advanced technologies for analysis and decision-making.


Services Used


r 2
introduction to posit connect
mysql logo
docker 2
iot edge sensors

Related Blogs


Let’s Connect