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Oxygen manufacturing plant

Client Issue:

In May 2021, India faced a major COVID-19 crisis. They didn’t have enough medical oxygen for sick patients, and the demand was ten times higher than usual. India is a big country, and most hospitals couldn’t produce oxygen. They had to get it from companies in eastern India. The problem was that there was no good way to check if the oxygen was good quality, and they didn’t know how much they had. This made it hard to plan for times when they needed more. This situation showed that India needs better systems to make sure they have enough oxygen during health emergencies.

  • Tasked with monitoring the functioning of 1200 plants spread across 34 states in about 1020 hospitals.
  • 30 different oxygen plant manufacturers supplied the 1200 plants. Each one of them had a different control system. Each of the 30 vendors had different control systems.
  • Applied interacted with all the different vendors and established connectivity with the control system through the Terrier-WP to NIC (National Informatics Data Centre Cloud) through a secured interface.
  • The timeline for the implementation was 6 months and the project was completed

Approach:

  • Applied’s engineers held discussions with 30 oxygen manufacturing plants across the countries in 4 phases based on the volume of production to understand the infrastructure available at the facility
  • Based on the initial analysis, plants with two types of facilities were identified:
    • Advanced PLCs with capabilities to capture the pressure, purity and flow
    • Older PLCs without the capabilities to capture the above three key metrics
  • For the plants with advanced PLCs, Applied’s field engineers visited the locations and installed the Terrier-WP directly with the PLCs on the shop floor
  • For the plants without the necessary sensors, the field engineers installed the necessary sensors with the equipment and then connected it with the Terrier-WP
  • From the data collected KPIs were calculated, data analytics was done to forecast production and any irregularities were notified to the authorities
Impact:
  • Predictive Analytics and machine learning driven decision making that reduced the reduction in shortages by __%
  • Integrated dashboards to highlight issues and show inventory status across the entire supply chain and drill down / root cause analysis capability
  • Helped the manufacturer of oxygen generation plants to better understand the usage of their equipment, common failing points and increase customer satisfaction

For government officials, it was convenient to monitor the availability of oxygen in hospitals through a tracking app. The app also allowed them to keep an eye on important factors like pressure, purity, and system downtime.

Manufacturers saw several advantages, including improved operational efficiency by ensuring uninterrupted oxygen supply, conducting online diagnostics to save on travel costs, updating PLC programs online, and easily pushing software revisions to control systems.