We are a team of reasearchers and developers at NED University of Engineering & Technology.We are working on the technique that uses data analysis tools and techniques to detect anomalies in your operation and possible defects in equipment and processes so you can fix them before they result in failure.
It helps in:
- Minimizing the time the equipment is being maintained
- Minimizing the production hours lost to maintenance
- Minimizing the cost of spare parts and supplies
When predictive maintenance is working effectively as a maintenance strategy, maintenance is only performed on machines when it is required. That is, just before failure is likely to occur. This brings several cost savings and It answers three questions:
- Is your machine operating normally?
- Why is your machine behaving abnormally?
- How much longer can you operate your machine ?
01 Acquire Data
Collecting historical data about the machines’ performance and maintenance records to form predictions about future failures. Usage history data is an important indicator of equipment condition.
02 Preprocess Data
Cleaning the data and convert it into a form from which we can train our model.
03 Identify Condition Indicators
Condition indicators are the features in your system data whose behavior changes in a predictable way as the system degrades. A condition indicator can be any feature that is useful for distinguishing normal from faulty operation or for predicting Remaining Useful Life (RUL).
04 Train Model
To do predictive maintenance,sensors will be added to the system that will monitor and collect data about its operations.Training model on your data, as per your requirement.
05Deploy and Integrate
Deployment or integration of a predictive maintenance algorithm is typically the final stage of the algorithm-development workflow.
Our targed sections to satify our users will be:
Alarms, Hand held devices
Maintenance needs simple, quick information .
Integrated IT and OT Systems
That will be provide operations a birds-eye view
It is important that customers have easy access to information.
Dr Majida KazimiPrincipal Investigator
Dr Arshad AzizCo-Principal Investigator
Dr Hashim RazaCo-Principal Investigator
Lubaba RehmanResearch Associate
Shabeeh AbbasResearch Assistant
Maria ShoaibResearch Assistant
Our Industrial Partner
Our Commercial Partner
Our Research Partner
Neurocomputation Lab, NCAI Computer and Information Systems Department NED University of Engineering & Technology University Road, 75270, Karachi.
+92 219 9261203