Business Objective
Our client manufactures industrial inkjet printers for commercial customers for product labeling and also provides warranty/maintenance plans post-installation.
The client wanted to create customized maintenance plans and enable reliability engineers to embrace data-driven insights. They wanted to segment printers based on usage data and recommend personalized maintenance plans and build an end-to-end application to guide reliability engineers through the maintenance plan recommendation process.
Challenges
- Data is collected from the devices directly by field technicians leading to a lot of data issues
- Data available in multiple languages and different log templates based on machine configuration
- Logs are collected only for ~3-5% of installed printers
Solution MethodologyÂ
- Identified device characteristics from available data
- Modeled stress parameters
- Applied business logic to the imputed stress parameters. Stress parameters that were significant and independent were chosen for clustering.
- Clustered the printers based on the parameters chosen into high/medium and low-stress conditions
Business Impact
- Automated all existing manual processes along with new features to enable the client to generate personalized maintenance plans
- Reduced expense of replacing parts under warranty for many customers due to static plans and estimated to generate additional revenue of $1 million per annum
