A Fortune 500 energy company with more than two hundred plants globally needed more insight into their plants’ processes. With that insight, the company wants to increase the reliability of its systems and reduce maintenance costs. Hint explained to the company in a demonstration that by gradually expanding the analysis and models of their equipment, the company could automate parts of their maintenance routine and create indications of incoming failures. By building it up gradually, previous experiences can be collected as lessons learned and used to spot the problem before it happens again. Use these lessons from a single piece of equipment and apply these to all the other equipment that shares functionality.
Balancing safety and efficiency
Before COVID-19, cyber security was always chosen over availability and efficiency. Because of the lockdowns throughout the world, something had to change to continue the production of the plants. Information had to become available outside of the plant networks to allow employees to contribute while not at the plants, moving the data from the plant level to the Azure cloud environment. Therefore, a smaller group of people can service the equipment while the others can investigate problems, check key performance indicators, or adjust maintenance schedules.
The conclusion of the conversation Hint had with his client was that there is a need for an application that provides more insight remotely in their equipment but also integrates functionality like events, alarms, key performance indicators, statistical process control, inventory management, automated maintenance schedules, flexible reporting, simple user interface, and advanced diagnostics. Next, the application needs to integrate with systems like PI, SAP, and Maximo to provide a single location that offers all the information needed to execute the work.
The solution for this project comprises the delivery and implementation of a cloud Azure AML Information Management System with a mobile application and the configuration of X number of analyzers.
AML Information Management System (hereafter called AML) is the Hint implementation of AMADAS. AML is a toolbox developed for technicians, engineers, operators, and managers who can monitor, evaluate, and improve the performance of on- and offline analyzers in a cost-effective manner. It collects data from analyzer systems through PI, interprets analyzer performance, and provides guidance for maintenance decisions. AML consists of a centralized application and database with a web and mobile interface. The application does not restrict the number of users or IO points.
Hint has run a pilot for the last 12 months to test X number of analyzers on one location. This pilot was executed successfully, and the Fortune 500 energy company was impressed with the results. In the coming months, Hint will focus on kicking off the project by implementing 100+ analyzers of the first plant.