Use Case
Machine downtime is expensive, so avoid it by performing predictive maintenance. Take advantage of advanced analytics to improve asset availability, keep your supply chain moving and increase customer satisfaction.
Efficiency Gains
Automate predictive models that drive proactive maintenance strategy
Risk Mitigation
Address issues before equipment failure
Bottom-Line Returns
Extend useful life of equipment to improve machine availability and boost customer satisfaction
Business Problem
Your most expensive assets are the ones that cost you money because they’re down. They cost you additional operating expenses, lost sales, supply chain disruption, and, worst of all, customer satisfaction. You can maintain and regularly inspect your machine assets yet still be caught off guard by mechanical failure. The more frequently this happens, the more likely maintenance budgets will be exceeded, and the higher the risk of supply chain disruption. Predictive maintenance schedules reduce the risk of major failure by addressing small issues before they become big ones.
Alteryx Solution
Predictive maintenance helps you connect the dots among data, analytics, and service records. It automates the process of identifying events and conditions that will soon lead to downtime or repairs, then it alerts you to them. Acting on patterns in the data reported by your machines, you can schedule service calls and order parts when it’s convenient for you, instead of having to deal with unanticipated outages. Predictive maintenance is an important tool in improving relationships with customers and keeping the supply chain moving smoothly.
Alteryx provides an easy-to-use, drag-and-drop canvas for predictive maintenance and downtime analytics. By tying your maintenance and labor costs to historical outcomes, you can obtain the best results from technicians, keep machine-related costs of production low, and maximize your uptime and customer service levels.
1 – Data Connection
Connect part, maintenance, and failure data
2 – Prep and Blend
Automatically clean and format data for modeling
3 – Predictive Modeling
Create decision tree model to predict parts failure
Additional Resources
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