How GPP Increased Machine Utilization by 10% and Optimized Labor
Real-time data empowering smarter manufacturing decisions
Global Precision Parts (GPP), a leader in precision machined parts, partnered with Amper to digitize production and optimize labor utilization. By leveraging Amper’s real-time machine monitoring and OEE tracking, GPP increased machine utilization by 10%, improved their operator-to-machine ratio from 1:2 to 1:6, and achieved paid labor utilization rates of 100% or more. This case study highlights how data-driven insights enable manufacturers to boost productivity and justify investments in automation.
The Challenge
How to Get the Most Out of Paid Labor and Machines
GPP wanted to improve production efficiency by better understanding how their paid labor translated into machine uptime and output. While they had implemented Amper’s OEE tracking system, they needed guidance on how to leverage the data to meet their operational goals and maximize return on investment.
The Solution
Setting Clear Utilization Goals and Tracking Paid Labor
GPP collaborated with Amper and peer customers to develop a strategy focused on paid labor utilization. They set a goal to achieve either two hours of machine uptime or one hour of setup for every hour of paid labor. By involving operators early and using Amper’s real-time data dashboards, GPP was able to track progress and adjust workflows accordingly.
Key Results: Measurable Improvements in Utilization and Labor Efficiency
Within a short period, GPP achieved:
- A 10% increase in machine utilization.
- Paid labor utilization averaging 100% or more, meaning every hour paid resulted in at least one hour of productive machine time or setup.
- An improved operator-to-machine ratio, rising from 1:2 to 1:6, enabled by investments in more automated equipment.
- The ability to justify new equipment purchases while reducing labor costs and improving profit margins.
Continuous Improvement and Insights
Using Data to Drive Ongoing Success
GPP’s Plant Manager, Michael Abbott, emphasizes the importance of honest self-assessment and data-driven decision-making:
"When we started this initiative with Amper, about 80% of what we were paying we were turning into production. We now average over 100% every single week of paid production."
He recommends manufacturers start small, track meaningful data, and use Amper’s clean, raw data to uncover the truth about their operations and drive continuous improvement.
“We just wanted to get the most out of our money—as we all do in manufacturing. Without Amper, we wouldn’t have been able to do this easily. The data is raw and clean—you don’t need to manipulate it to see the truth of what’s happening on the floor.”
Streamline production monitoring & drive continuous improvement
Frequently Asked Questions
Case Study Insights & Implementation FAQ
What utilization goals did GPP set?
GPP aimed for two hours of machine uptime or one hour of setup for every hour of paid labor.
How much did GPP increase machine utilization?
They achieved a 10% increase in machine utilization.
What was the impact on labor efficiency?
Paid labor utilization averaged 100% or more, meaning labor costs were fully converted into productive machine time.
How did operator-to-machine ratios change?
GPP improved their ratio from 1:2 to 1:6 by investing in more automated equipment.
What advice does GPP’s Plant Manager give to other manufacturers?
Start small, track meaningful data, and use clean, raw data to uncover operational truths and drive continuous improvement.
Is Amper easy to implement?
Yes. GPP involved operators early and used Amper’s dashboards to gain quick buy-in and actionable insights.