SELECTED EXPERIENCE

Real work.
Lessons that carry forward.

Examples from my manufacturing and engineering career—and how that experience shapes the way I help teams use AI today.

MANUFACTURING EXPERIENCE. APPLIED AI.ADVANCE NOW / MIKE MAIER

These summaries draw from my career records and recollections. They describe earlier manufacturing work; the AI applications are opportunities for today.

01 / MOLDING PROCESS IMPROVEMENT

Better cycles start
with a better system.

The work

In a molding operation with hundreds of parts, I helped establish setup information, train process technicians, and systematically optimize high-volume jobs. That foundation made it possible to extend improvements across more of the operation.

What mattered

The improvement was supported by documented processes, capable people, quality checks, and a way to surface exceptions. Changing a target was only one piece of the work.

How that experience helps today

AI can help organize setup records and compare process histories. Manufacturing judgment is still needed to decide what can change, how to test it, and how to keep the result under control.

02 / PLANT COOLING & INFRASTRUCTURE

Understand the network
behind the machine.

The work

I modeled a plant water network using a large system of equations to understand flow and pressure drop through the piping. Field pressure measurements were then used to check the model.

What mattered

Cooling performance depends on the network, not just the setting on a pump. The analysis linked individual branches and equipment to the behavior of the system as a whole.

How that experience helps today

AI-assisted calculations and focused software can make this kind of analysis easier to develop and explore. The assumptions, units, and agreement with physical measurements still need engineering review.

03 / EQUIPMENT EVALUATION

Look beyond the
machine specification.

The work

I spent extensive time evaluating injection molding presses, using pressure and position measurements and data acquisition to examine repeatability and machine response.

What mattered

Equipment that looks similar on paper can behave very differently in production. Instrumented testing makes those differences visible and gives equipment decisions a stronger basis.

How that experience helps today

The same discipline applies to AI and software: define the task, test representative work, examine repeatability, and measure performance before relying on a result.

04 / MAINTENANCE SYSTEMS

Make the right parts
easier to find.

The work

Maintenance-area improvement included sorting obsolete stock and organizing useful spares and preventive-maintenance supplies around the equipment they supported.

What mattered

Moving parts into another cabinet does not solve the problem. People need to know what a part belongs to, where it lives, and whether it will be there when needed.

How that experience helps today

A better inventory structure, clear naming, and a practical information system can reduce searching and make existing maintenance knowledge more useful.

GOVERNMENT & MILITARY EXPERIENCE

Practical products.
Demanding requirements.

A substantial part of my career has involved military-related products, packaging, testing, and approval work.

From specialized tool storage and molded products to equipment used by the warfighter, the work required attention to requirements, documentation, testing, and production.

Earlier, I served in the U.S. Air Force, working on fighter jets.

Explore government & military experience

WORK WITH MIKE

If you’d like
my help, I’m here.

My personal consulting is a premium service for people and organizations that want my direct involvement. If your budget is tight, start with AN Creation. The resource is there to help you make progress without hiring me.

Talk with Mike