CASE STUDY • HARLEY-DAVIDSON
Revolutionizing Inventory Management and Maintenance:
A Data Driven Approach
NexStratus leveraged its data-driven approached to transform how Harley-Davidson handles supply chain disruption.
3 min read
10% Increase
in production
capacity
4 Weeks
project
engagement
30% Decrease
in unplanned machine
downtime
OBJECTIVE
NexStratus was engaged to conduct a comprehensive data assessment at Harley-Davidson's XYZ plan to evaluate their inventory management data and identify opportunities to predict downtime due to parts inventory shortages, as well as forecast maintenance requirements for manufacturing machines.
Real-time Insights
Using the existing data generated by the machine's on-board controllers, NexStratus leveraged advanced predictive analytics and synthetic data capabilities to forecast critical production downtime.
APPROACH
1
Data Collection and Analysis
Our team collaborated closely with Harley-Davidson to gather extensive historical data on inventory levels, parts usage, machine performance, and maintenance records from multiple plant locations.
2
Predictive Modeling
We developed predictive models to forecast inventory shortages and downtime, and implemented machine learning algorithms to analyze machine performance and predict maintenance needs based on key indicators.
3
Geospatial Analysis
To account for variations in inventory demand and machine usage across different geographic locations, we conducted geospatial analysis to identify regional trends and patterns that could impact inventory management and maintenance planning.
4
Data Visualization and Insights
We created interactive dashboards and visualizations to present our findings in a clear and actionable manner, enabling stakeholders at Harley-Davidson to gain valuable insights into inventory dynamics and machine health across their plant network.
Real-time anomaly detection empowers operators to anticipate tool and machine faults, before unplanned downtime occurs.
Harley-Davidson, the iconic American motorcycle manufacturer, faced challenges in maintaining optimal inventory levels of manufacturing machinery parts and ensuring the efficient operation of manufacturing machines across its multiple plant locations in the United States.
With a vast and complex supply chain, they recognized the need to leverage data-driven insights to enhance inventory management practices and proactively address maintenance needs.
BACKGROUND
NexStratus's data-driven approach revolutionized inventory management and
maintenance planning at Harley-Davidson, enabling the company to enhance operational
efficiency, minimize downtime, and drive cost savings across its manufacturing operations.
By harnessing the power of data analytics and predictive modeling, Harley-Davidson transformed its supply chain practices and positioned itself for continued success in a rapidly evolving industry landscape.
CONCLUSION
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RESULTS
1
Predictive Downtime Forecasting
Our analysis uncovered significant insights into the relationship between inventory levels and production downtime, enabling Harley-Davidson to use predictive models to anticipate and mitigate potential disruptions.
2
Proactive Maintenance Planning
Our machine learning algorithms accurately forecasted maintenance needs for Harley-Davidson's manufacturing machines, enabling proactive scheduling of preventive maintenance to reduce downtime, extend machine lifespan, and optimize costs.
3
Implementation of New Solutions
With actionable insights from our data assessment, Harley-Davidson implemented automated inventory replenishment, predictive maintenance scheduling, and real-time monitoring solutions across its U.S. plants.
4
Operational Efficiency and Cost Savings
By leveraging data-driven insights, Harley-Davidson optimized inventory management and maintenance practices, significantly improving operational efficiency and cost savings by reducing stockouts, excess inventory, downtime, and maintenance costs.
