How this Manufacturer increased CNC Uptime to 50% on key lines

 

Results

Project Highlights

• Eliminated night shift while maintaining output, reducing labour and energy costs

• Increased CNC uptime from around ~30% to ~50% on key machines using real-time performance data

• Reduced scrap below the previous baseline through targeted, data-driven improvements

• Established a single, trusted view of machine performance across 10 CNCs

• Enabled confident, evidence-based decisions around capacity, shifts and production planning

Project Overview

The business’s CNC operations sit at the heart of its production output, with every door passing through four CNC processes across seven machines.

Prior to implementing FourJaw, the team believed the equipment was already running at maximum capacity and that further investment in machinery would be required to increase output. However, the data being captured focused primarily on operator efficiency rather than true asset utilisation, the activity that genuinely adds value to the product.

This data relied heavily on manual collection and retrospective entry, making it difficult to gain a clear and timely understanding of performance. Analysing results shift-to-shift was challenging, and reacting to issues in real time was nearly impossible.

Even when data was available, it often raised more questions than answers. Reported efficiency regularly exceeded 100%, yet this did not reflect actual output or the reality on the shop floor.

As production demands increased, the CNC department became a clear bottleneck, but with limited visibility into the root causes, decisions around shifts, overtime and process changes remained high-risk and largely based on experience rather than evidence.

Key challenges included:

• No clear visibility of true machine utilisation across CNC operations

• Reliance on manual, retrospective data collection

• Reported efficiency not aligning with actual output

• Difficulty identifying bottlenecks and lost capacity

• High-risk operational decisions made without trusted data

The Solution

Real-Time CNC Visibility without complexity

The business deployed FourJaw's CNC machine monitoring system across five CNC machines and supporting assets to bring clarity to an area that had previously relied on experience and fragmented data. Installation was simple and non-invasive, with FourJaw automatically tracking when machines were running, idle or stopped, without the need for complex integration or IT projects.

Almost immediately, production and maintenance teams gained access to a shared, real-time view of machine performance. Live production dashboards became part of daily and weekly reviews, giving everyone a consistent and trusted understanding of what was happening on the shop floor.

As data built over time, previously hidden patterns began to emerge. Downtime was categorised using structured reason codes, making it easier to identify where time was being lost and which issues were having the greatest impact on output.

Rather than focusing on the easiest machines to measure, the team concentrated on the CNC operations and assembly-line processes that were constraining production. With accurate, real-time data in place, they were able to move away from assumptions and make decisions based on evidence, giving them the confidence to take action and improve performance.

Results

Turning fundamental production data into confident operational change

With real-time data across their CNC operations, the team gained the confidence to make meaningful changes to how the factory operated. Within 18 months, FourJaw became central to performance reviews and decision-making.

The result wasn’t just improved visibility, it was the ability to act with confidence, enabling the business to optimise shifts, improve uptime and stabilise production.

By analysing performance across shifts and validating improvements through data-led trials, the team identified where time and efficiency were being lost. This gave them the confidence to remove night shift entirely,  reducing labour and energy costs while maintaining output.

At the same time, machine data allowed production to be rebalanced across remaining shifts, improving uptime and overall efficiency. Key operational gains included:

• Night shift eliminated while maintaining output

By analysing performance across shifts, the operations team identified where time and efficiency were being lost, and was able to simulate the impact of proposed improvements through trials validated using FourJaw. This gave them the confidence to remove the night shift entirely.

The change reduced premium labour and energy costs while simplifying operations, all without impacting output.  

• CNC uptime increased toward ~50% on key lines

Using machine data, production was rebalanced across remaining shifts, with uptime on key lines improving toward ~50%. 

• Scrap rate reduced below the previous baseline

The transition introduced some initial instability, but real-time data made it clear where issues were occurring.

The business was able to quickly identify the causes of scrap, target improvements and track progress as changes were made. As a result, scrap fell below previous levels, and the new operating model became more stable and efficient.

• Improved confidence in capacity and production planning

With better visibility, management also gained a clearer understanding of what drives strong performance.

By aligning materials, sequencing and quality processes, they were able to achieve more consistent, reliable output, moving away from reactive firefighting to controlled, repeatable production.

Summary

This company’s journey shows what’s possible when manufacturers move from instinct to evidence. By gaining a clear, real-time view of their operations, they were able to make confident decisions that reduced costs, improved performance and stabilised production, all without investing in new machinery.