Do you want to develop and deploy a prototype for condition monitoring, anomaly detection, and predictive maintenance of your assets? Work with MathWorks Consulting to overcome the following challenges:
- You have collected data from your machines and want to perform predictive maintenance, but you don’t know where to start.
- You are not interested in a time-consuming pilot project, where the outcome is not clear and the risk for you and your team is high.
- You have little or no data science expertise within your team.
Our experts will evaluate your data and give an assessment of its usability for condition monitoring and predictive maintenance applications. Analyze your data and systems together with us, before committing to a proof-of-concept.
- Expertise: MathWorks has successfully implemented several predictive maintenance and condition monitoring solutions with our customers. You’ll learn about projects with Mondi and Baker Hughes where we were able to design and deploy these solutions—at scale—quickly and efficiently.
- Collaboration: MathWorks Consulting works closely with you to ensure that you and your team can later adapt, extend, and maintain the solution on your own.
- Data science and digital twins: For more than 30 years, engineers and scientists have used MATLAB® to analyze data and develop mathematical models. MATLAB makes data science easy with tools to access and import data from various sources, preprocess and visualize the data, and train machine learning and deep learning models for tasks like anomaly detection, condition monitoring, and predictive maintenance. You can also build digital twins of your systems to track and predict the operation of individual assets in near real time.
- Deployment: Solutions built using MATLAB are production ready and can be securely deployed and integrated at scale with edge devices, enterprise IT systems, data sources, and operational technologies that can be on-premise, hybrid, or cloud based.