Challenge and Opportunity
A Keiter Technologies client and farming cooperative wanted to develop a model that could predict when its equipment needed maintenance service to avoid lost revenues from breakdowns or failure.
Our Approach
- The team carefully analyzed the maintenance schedules, recent repairs, brands, and usage hours from all existing equipment.
- Using Python, the team developed a predictive model which specifically outlined when equipment would need repair or maintenance based on the EC unit.
- The development of the model required extensive collaboration between the company’s field crews and our data scientist.
Results
The model successfully predicted construction equipment maintenance needs and reduced unpredictable equipment failure (like onsite ones) rates by 90 percent. This resulted in decreased cost for the company.
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About the Author
Keiter Technologies
Keiter Technologies focuses on serving businesses with their strategic technology needs through data science, cybersecurity, and IT audit and consulting.
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