Toronto, Canada · Production Manager
Additive manufacturing leadership, built around real production.
I am an additive manufacturing production leader who translates shop-floor constraints and customer requirements into clear system needs. My work connects operating judgment with process improvement, software, automation, and a developing practical knowledge of AI systems.
My engineering background helps me understand customer requirements and translate technical conversations efficiently. Experience in application discovery, DFAM, equipment service, and production has taught me how a design decision, machine setup, process choice, or handling method can affect the result.
From application to operation
Responsibility grew with the problems that needed solving.
I joined Designfusion as an Applications Specialist, working directly with additive equipment, customer applications, troubleshooting, and field service. That exposure developed into responsibility for nesting and end-to-end production, followed by production planning, staffing, quality, maintenance, materials, delivery recovery, and the systems used to control the work.
Today, I manage a multi-technology additive operation producing more than 50,000 parts in a typical year under my control. The responsibility extends beyond keeping printers running. It includes deciding what should be produced, how work should move, where risk needs to be addressed, and what information people need to make reliable decisions.
Software, automation, and AI have become useful extensions of that work. I use them when they fit the operating problem, while keeping production decisions deterministic and human-controlled where reliability and accountability matter.
Explore my work →Featured professional work
Professional practice
The printer is not the starting point.
A successful additive application begins with the problem being addressed. Mechanical requirements, operating conditions, logistics, economics, design, material behaviour, post-processing, inspection, and quantity all influence whether an application is viable.
Sample parts and concept validation help replace assumptions with direct evidence that can guide the design, process, and production plan.
- Application discovery
- DFAM
- Process selection
- Production planning
Featured independent project
Paused learning build
UtilityOps Readiness
UtilityOps was built to explore what AI could contribute to operational readiness decisions. It combines deterministic checks with indexed reference material and language-model interpretation to identify missing documents, blockers, and required actions in synthetic work-order packages.
I defined the problem, data flow, examples, and test cases. AI coding assistance contributed substantially to the application architecture and code.
- Retrieval
- Deterministic checks
- Citations
- Human review
For the love of learning
Questions have driven human progress and my own development. Learning begins by identifying gaps, taking apart assumptions, and rebuilding a clearer understanding of the whole.More about my approach →
Contact
Let's continue the conversation.
I am interested in conversations around additive manufacturing, production systems, technical implementation, and useful technology built around real operating problems.