Predictive Maintenance App to to detect Faulty ICU Beds

Predictive Maintenance App to to detect Faulty ICU Beds

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The Problem Statement

With a mission to making healthcare better using medical technology, the client wanted to build a professional predictive maintenance app for mobile that would predict the number of faulty beds in an ICU chamber and generate alerts as well. In this app, the company required the addition of two functionalities– request for new bed status and information on faulty beds & number of possible snags in future.  

Screenshots

predictive maintenance app

The Solution

We designed & developed a unique predictive maintenance based mobile application that predicts the number of defective beds likely to need maintenance. Basically, an operation theater bed is made up of 4 electric actuators and 1 battery to adjust the bed in several positions. The Android based application we designed checks the functioning status of those actuators and battery in amperes and voltage respectively.

For example, the low current voltage for an actuator is 0.3 Ampere and high current voltage is 2 Ampere, our application would generate alerts if the low current voltage reaches to 0.5 Ampere and high current voltage reaches to 1.8 Ampere. Similarly, the application checks the battery status and predicts the future problems by analyzing the voltage variations. 

KritiKal developed this predictive maintenance app with a fully-fledged user management function where three kinds of users can register i.e. doctors, technicians, and administration professionals. Leveraging our competency in material design concept, Android app development frameworks, SQLite database & languages like XML & Java, we built this indigenous app that has an intuitive UI and visually rich functionality. Also, our team integrated push notification to generate alerts before failure occurs in the ICU beds. 

Benefits Delivered

KritiKal Solutions has built a revolutionary predictive maintenance app that predicts defects in the operation beds before they even occur. There could be multiple symptoms of failure in different scenarios and robust data analytics techniques are deployed to identify or predict probable failure in the future. This app not only enhances the productivity of doctors but also improves the quality of patient care. 

Technology Used

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