Transforming Maintenance Operations: A Success Story

Written by Ashling | Feb 6, 2025 8:56:42 PM

$2M

in freed capacity

41%

reduction in machine malfunctions

18%

reduction in machine breakdowns

An established American manufacturer faced mounting challenges from unplanned downtime, driven by a reliance on reactive maintenance and short-term break-fix solutions. These challenges disrupted production, increased operational costs, and led to significant revenue leakage, ultimately impacting both the bottom line and overall productivity.

The Challenge

In a fast-paced manufacturing environment where every minute of downtime has a measurable cost, the customer’s reactive approach to plant maintenance proved unsustainable. Short-term fixes and inconsistent repair strategies not only escalated downtime but also undermined capacity management. With technician shortages compounding the issue, the traditional maintenance model led to:

Increased operational costs and revenue leakage
Reduced productivity and capacity utilization
A fragmented view of machine performance and operator efficiency

The Solution

Ashling Partners introduced the Maintenance Control Center, powered by Celonis, as a comprehensive answer to these challenges. This innovative application is an integral part of our core manufacturing command center and is built on Ashling’s lean analytical framework. Key elements of the solution included:

Real-time monitoring delivers critical alerts on machine breakdowns and operator activities, while proactive notifications enable technicians to address high-risk issues before escalation.

Consolidated machine data streamlines maintenance scheduling. Predictive analytics forecast needs using historical downtime and activity trends, shifting maintenance from reactive to proactive.

Smart visualizations and process intelligence provide a unified view of operations, empowering data-driven decisions that boost capacity, quality, and efficiency.

Results & Benefits

The implementation of the Maintenance Control Center led to transformative outcomes:

Freed $2M in Capacity: Enhanced predictability and efficient scheduling unlocked previously under-utilized capacity.
41% Decrease in Machine Malfunctions: Improved monitoring and proactive maintenance strategies reduced malfunction incidents, translating to a 45% decrease in hours lost.
18% Decrease in Machine Breakdowns: By addressing potential issues before they escalated, machine breakdowns dropped significantly, with a corresponding 26% reduction in lost operational hours.

These improvements not only bolstered revenue and productivity but also enhanced product quality and vendor accountability—ultimately positioning the client for sustainable, long-term growth.

Looking Ahead

As manufacturers continue to navigate the digital transformation landscape, integrating real-time monitoring with predictive analytics is essential. Ashling Partners recommends that organizations:

Leverage comprehensive command centers to unify maintenance data across systems
Invest in proactive, data-driven maintenance strategies to optimize capacity and reduce downtime
Utilize integrated insights to drive continuous improvement in operational performance

This case study underscores how a strategic pivot from reactive maintenance to a proactive, predictive model can fundamentally enhance operational efficiency. The Maintenance Control Center is not just a tool—it’s a platform for leaders in operations and finance to drive measurable improvements and secure a competitive edge in today’s fast-evolving manufacturing environment.

Technology Used

Enhance productivity, increase capacity and reduce maintenance costs with the Maintenance Control Center, powered by Celonis. Offering a comprehensive, system-agnostic solution designed for any industry that relies on machinery for production, it uses real-time data and analytics to monitor and control manufacturing processes. Get event and value-based monitoring of plant floor machine operations, alerts for line stoppages or break-fix activities, and predictive analytics to forecast maintenance needs and preempt critical incidents.

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