What Can We Push Left? The Case for Upstream Data in Aerospace Machining
There is a question I have asked throughout my entire career, across very different environments: managing engineering operations in the military, leading Catapult projects at the AMRC, supervising PhD research, and teaching systems engineering to undergraduates.
What can we push left?
The specifics change. The principle never does.
The Cost of Change Curve
Systems engineers have known for decades that the cost of changing something increases exponentially the further downstream you make that change. It is one of the most well-evidenced principles in engineering management, and it applies whether you are designing an aircraft, developing software, or managing a complex machining programme.
The logic is straightforward. Early in any process, decisions are provisional. The commitments are limited and the options are open. Change something at the design stage and the cost might be a few hours of an engineer’s time. Change the same thing on the shop floor and you are looking at scrapped parts, unplanned downtime, rescheduled operations, and the downstream ripple effects that rarely show up cleanly on a cost report but are felt acutely by everyone involved.
In aerospace manufacturing, where part complexity is high, tolerances are tight, and material costs are significant, this dynamic is particularly unforgiving. And yet the dominant model in the industry still pushes the moment of discovery dangerously far to the right.
How Problems Reach the Shop Floor
Consider the typical workflow for a complex aerospace component. A CAM programmer develops toolpath strategies, drawing on experience, established post-processors, and verification software. The programme is verified to a reasonable degree of confidence and released to the shop floor.
Then machining begins.
And it is here (often hours or days into a process that may have taken weeks to plan) that the real picture emerges. A strategy that once looked sound in theory doesn’t perform under actual cutting conditions. Feeds and speeds that appeared achievable cannot deliver the minimum chip thickness. Tooling that was specified at the programming stage turns out to be a poor choice for the actual cutting conditions encountered.
None of this is a failure of competence. It is a failure of information timing. The programmer made the best decisions they could with the data available at the time. The problem is that critical data (about how that machine, that toolpath and those parameters will perform) was not available at the point when decisions were still cheap to change.
By the time it is available, it is not cheap at all.
Upstream Data Changes the Economics
The concept of shifting decisions to the left is not new. Lean manufacturing, concurrent engineering, and digital twin methodologies have all been working at this problem for years. What has changed is the availability of the data required to make early decisions with genuine confidence rather than informed intuition.
This is precisely the challenge that DigitalCNC was built to address.
By giving CAM programmers access to machine specific data at the point of programming (before a single cut is made), the economics of the cost curve shifts fundamentally. The questions that would previously have been answered only by the machine now have answers at the desk. Will this strategy achieve the required chip thickness? Where are the margins, and how sensitive is the outcome to changes in feedrate? These are not small questions. In large-part aerostructure machining, where a single component might represent significant material value and a machining cycle of many hours, getting the answers wrong at the shop floor stage is costly in ways that compound quickly.
Getting the answers right at the programming stage costs very little by comparison.
What This Means in Practice
The immediate effect of upstream data is faster, more confident programme development. CAM programmers are not replacing their expertise. They are augmenting it with a layer of process intelligence that previously only existed in the collective memory of experienced machinists and in post-machining analysis of completed runs.
But the second-order effects are where the real value accumulates.
When problems are surfaced upstream, they inform not just the current programme but the broader knowledge base of what works and what does not for a given strategy, tooling family, or machine configuration. Over time, this builds a data asset that compounds: each programme making the next one faster and more reliable.
There is also a risk reduction dimension that matters particularly in the aerospace supply chain. Late-stage process failures do not just cost money. They affect delivery schedules, they consume engineering resources that should be focused elsewhere, and in the most serious cases they create quality exposure that has consequences well beyond the immediate programme. Upstream data is, in this sense, a risk management tool as much as a productivity one.
The Broader Principle
Pushing left is ultimately about the relationship between information and decision-making. Every engineering process involves a sequence of decisions, and the quality of those decisions is bounded by the quality of the information available when they are made.
The goal is not to eliminate uncertainty (that is not achievable in complex manufacturing environments). The goal is to ensure that the right information is available at the right point in the process, so that the decisions that are most consequential are made when they are still affordable to revisit.
In aerospace machining, that point is at the CAM programmer’s desk. Not the shop floor.
Push Left Today
If you are responsible for machining programme development in the aerospace sector, it is worth asking the same question that has shaped my thinking across every engineering environment I have worked in. Where in your process are problems being discovered that could have been surfaced earlier? What decisions are being made on the shop floor that could be made at the desk, with better data, at a fraction of the cost?
What can you push left today?
Dr Rob Ward, CEO, DigitalCNC
DigitalCNC provides CAM programmers with machining intelligence at the point of programming, enabling better decisions upstream and fewer problems downstream. If you would like to understand how this applies to your specific machining challenges, get in touch.