Data Science Starter Kit for Predictive Maintenance
Improve equipment management, reduce downtime, improve safety, and avoid costly breakdowns with data science for predictive maintenance.
Managing maintenance operations can be complex, difficult, and expensive. Understanding which equipment assets are headed for a breakdown can help your organization avoid surprise repair costs, reduce unnecessary maintenance tasks, improve safety, and streamline parts supply.
From plant equipment to fleet vehicles, a predictive algorithm that provides early warnings of equipment breakdowns can significantly improve your maintenance strategy.
A data science for predictive maintenance starter kit from 2nd Watch will help your organization develop a predictive algorithm using cutting-edge techniques. In just 6-8 weeks, you will be able to visually see which specific equipment or vehicles are most at risk and you will be able to act on improving your maintenance process.

The Benefits of a Data Science Starter Kit:
Avoid breakdowns
Ability to avoid costly breakdowns before they happen.
Improve Planning
Better operations planning and maintenance.
Prevent Downtime
Cost control by avoiding unforeseen equipment downtime.
Reduce Waste
Improved supply chain management by reducing unneeded parts costs.
Control Costs
Avoiding unnecessary maintenance tasks that are costly and labor intensive.
Streamline Operations
Streamlined operations by automating maintenance schedules.
Increase Visibility
Visibility into your equipment and fleet health.
Improve Safety
Improved plant safety and reduced accidents.
What We’ll Do:
Conduct interviews with your stakeholders to understand your current methods and factors that could impact data science for predictive maintenance.
Identify, clean, and transform your most relevant sensor data.
Develop a high-quality predictive model that meets your accuracy expectations.
Integrate the model into a BI tool and dashboards for easy tracking, reporting, and scenario building.
Provide a short summary of driving factors and how they affect predictive maintenance.
What You’ll Get:
A state-of-the-art predictive model that provides early warning signs to let you know when equipment needs maintenance before a major breakdown occurs.
Enhanced understanding of your equipment.
A dashboard displaying at-risk units along with other fleet health indicators.
A short summary of our findings, including how factors affect output, model limitations, and recommendations for improvement.
A Tech Stack That
Works for You
Our tech-agnostic approach means that we can build a data science for predictive maintenance solution with the leading cloud platforms, data management tools, and analytics technologies.
Here are some of the technologies our team will use to build the right solution for your organization.













