Abstract
The leading manufacturers are now investing in predictive maintenance, which holds the potential to reduce cost yet increase margin and customer satisfaction. Though traditional techniques such as statistics and manufacturing have helped, the industry is still plagued by serious quality issues and the high cost of business disruption when components fail. Advances in machine learning offer a unique opportunity to improve customer satisfaction and reduce service downtime. This chapter shows how to build models for predictive maintenance using Microsoft Azure Machine Learning. Through examples we will demonstrate how you can use Microsoft Azure Machine Learning to build, validate, and deploy a predictive model for predictive maintenance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2014 Valentine Fontama
About this chapter
Cite this chapter
Barga, R., Fontama, V., Tok, W.H. (2014). Building Predictive Maintenance Models. In: Predictive Analytics with Microsoft Azure Machine Learning. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-0445-0_8
Download citation
DOI: https://doi.org/10.1007/978-1-4842-0445-0_8
Published:
Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-0446-7
Online ISBN: 978-1-4842-0445-0
eBook Packages: Professional and Applied ComputingProfessional and Applied Computing (R0)Apress Access Books