CASE STUDY: Global Predictive Maintenance for MFP
Predictive Analytics Revolutionizing Customer Support
Our client, a global leader in the printing and imaging industry, faced issues with varying lifespans of leased equipment parts depending on customer usage. Delayed replacements decreased customer satisfaction, while premature replacements increased part costs. By accurately predicting parts’ lifespans based on individual customer usage, the developed model and operational framework resolved these issues, achieving a reduction in complaints and an extension of parts’ lifespans.
About Our Client
A global leader in the printing and imaging industry.
Key Challenge
Delayed parts replacement led to increased malfunctions and customer complaints.
Premature replacement escalated parts costs.
Usage varied by market, making prior testing infeasible.
Data collection methods and management formats were highly unstable.
Previous in-house attempts had failed.
Outcome Delivered
Reduction in Complaints: Complaint frequency decreased by 30%.
Extended Parts Lifespan: Parts’ lifespans extended by 10%, reducing parts costs.
Operational Excellence: Optimized maintenance scheduling significantly reduced service costs.
Global Deployment: Rolled out a similar framework model across international branches.
Our Approach
Predictive Maintenance Framework:
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Data Correction Model: Developed models that detect and correct inconsistent data format.
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Predictive Model Development: Developed a predictive maintenance framework and models.
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MLOps: Built an infrastructure for model operations, including monitoring and retraining.
Operational Framework & Support:
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Cost Simulation: Designed & Implemented operational simulations to estimate models’ impact.
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Reporting: Designed & Implemented reporting functionalities for service personnel.
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In-house Support: Executed trainings related to model development & operations.
Project Type
Industry
Location
Services
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