How Auredia Helped Cut Hidden Cost by 95%

Manufacturing facilities are often a high-mix environment where precision machining and efficient workflows are critical to meeting production demands. With multiple machines, operators, and programmers working in such delicate synchrony, even small inefficiencies can create ripple effects across the shop floor.

As operations continued to scale, our customer’s leadership needed better visibility into recurring issues that were impacting productivity but were not clearly understood. What initially appeared to be routine variation was, in reality, driving significant hidden costs, eventually reaching nearly $36,000 per month in inefficiencies in one activity alone.

Image of lost opportunity cost in programming

The Challenge

On the surface, operations appeared to be running as expected. However, one operator consistently flagged programming issues each time a new job was run. At first, this behavior seemed like normal variation. It was assumed to be related to operator preference, isolated machine differences, or the typical day-to-day adjustments that happen in a machining environment.

Over time, it became clear that something more significant was happening. Programs were regularly being modified at the machine before they could run properly. This meant operators were compensating for upstream issues, introducing inconsistency into the process and increasing the risk of scrap and downtime. These inefficiencies were not just operational, they were costly, contributing to tens of thousands of dollars in monthly losses.

Despite this pattern, there was no clear way to connect these events or understand their root cause, allowing the issue to persist unnoticed within daily operations.

Programming lost opportunity cost by week

The Solution

Auredia introduced real-time visibility into shop floor activity by allowing operators to flag issues as they occurred. These signals were immediately shared across the team, including supervisors, programmers, and leadership, creating a transparent view of what was happening in production.

As messages continued to surface, a pattern became apparent. The repeated programming alerts were not isolated incidents but part of a larger, recurring issue. This visibility created the opportunity to investigate further.

Leadership brought together the operator, programming team, and shop supervision to review what was happening. By aligning around the information captured in Auredia, the team was able to trace the issue back to a shared post-processor error. This error was causing programs to behave differently across certain machines, forcing operators to make manual adjustments before running jobs.

Once identified, the team corrected the post-processor and standardized how programs were delivered to the machines. This eliminated the need for operator-side changes and restored consistency to the process, removing a major source of hidden cost.

The Results

After resolving the root cause, operations became more stable and predictable. Machines were able to run programs as intended without repeated intervention, which reduced downtime and improved overall efficiency. The risk of scrap decreased as variability was removed from the process, and jobs were able to start more quickly without the need for manual corrections.

Financially, the impact was substantial. What had previously cost nearly $36,000 per month in inefficiencies was reduced to a normal baseline of approximately $1,666 per month, a savings of over $34,000 per month, or more than $400,000 annually. This represented a 95% reduction in unnecessary costs, delivering a significant return on investment.

Programming Opportunity Costs from June - December

The improvement also had a noticeable impact on the team. Operators were able to focus on running their machines instead of troubleshooting programs, while programmers gained clearer ownership of program accuracy. Collaboration between teams improved as responsibilities became more defined and aligned.

Most importantly, this situation demonstrated how a seemingly small and routine issue could point to a larger systemic problem. Without visibility into the pattern, the issue would likely have continued indefinitely.