AI Is a Journey for Foundries and Equipment

Artificial intelligence is reshaping manufacturing, and yet for foundries and their equipment suppliers the path forward is not simply software installation. It is a transformation, one that will blend tools, data, people, and workflow into something more efficient, more responsive, and more competitive than any of these has been anticipated to be. But achieving that success depends on preparation, navigation, and choosing the right partners.

The AmatriumGPT AI platform designed specifically for industrial environments reflects this approach to the challenge. GPT stands for “generative pre-trained transformer,” meaning it is an AI model trained on large volumes of text to generate human-like responses. The technology is powerful, but it reinforces a critical truth: 80% of AI adoption challenges are rooted in change management, not algorithms. Teaching teams how to incorporate AI into their daily workflow, trust its output, and rely on it for efficiency is far harder and far more important than any line of code. Only about 20% of the challenge is the software itself.

Success with AI comes down to three essentials:

• The right tool for the job
• The right data to support the task
• A sufficient amount of data

When these fundamentals align, the transformation is profound. What once required searching through binders, old folders, handwritten notes, or the memory of a single veteran employee becomes instantly accessible. What took hours now takes seconds. What once required tribal knowledge now becomes generational knowledge.

Let’s study real-world examples of how AI tools - especially company specific solutions like AmatriumGPT - deliver efficiency in the foundry and equipment sectors every single day.

Case Study 1: AI for metalcasting

A modern foundry is a complex ecosystem of machines, processes, and people. The casting operation includes:

• Melting furnaces
• Transfer ladles and automated handling systems
• Gate and riser removal equipment
• Shakeout and sand-removal systems
• Heat-treat ovens and quench tanks
• Inspection tools such as X ray and CT scanning

All the equipment for this is backed by specific sources of information: manuals, spare parts catalogs, safety guidelines, wiring diagrams, troubleshooting tips, PLC details, recipes, calibration instructions, operator training documents, and more. For decades, these materials have lived as PDFs, often thousands of them, spread across desktops, shared drives, email threads, and file cabinets.

AI transforms this. Within a secure GPT, every document becomes searchable, understandable, and instantly usable. Instead of an operator spending 20 minutes searching for a heat-treat cycle for a specific part number, they simply ask: “What is the heat-treat recipe for Part 2378, and what are the quench requirements?”

The AI responds with the exact information, citing the internal document where it was found. Citations of internal documents is a tremendous capability not available in any other tool today.

Maintenance teams benefit even more. A technician facing a furnace fault code could ask: “What does Error 4.13 mean on the melt furnace, and what steps do I follow to fix it?”

The system extracts the answer directly from the equipment manual or past maintenance logs and displays spare part numbers, diagrams, or safety warnings as needed.

Tribal knowledge is powerful in foundries, and often fragile. A single engineer or supervisor may be the only person who remembers a certain casting behavior, a specific warm-up routine, or why a process deviation was made five years ago. AI changes that. When internal documents, notes, historical fixes, and past process decisions feed into the system, that expertise becomes institutional knowledge available to every employee.

The foundry becomes more consistent. Training becomes easier. Safety improves because employees get correct, vetted answers immediately. Downtime shrinks because troubleshooting moves faster.

AI does not replace foundry workers. It amplifies them, giving each one access to the collective knowledge of the entire operation. Answers are available as needed, even on a third shift when most engineers and managers are sleeping.

Case Study 2: AI for foundry equipment manufacturers

If foundries are complex, the equipment that serves them is even more complicated. A single machine - a molding line, furnace, shotblast system, automation cell, etc. - is an assembly of many components, each with its own documentation. Equipment makers typically manage:

• Drawings, diagrams, and schematics
• Engineering specifications
• Assembly details
• Spare parts lists and pricing
• Troubleshooting and repair procedures
• Preventive maintenance instructions
• Upgrade packages
• Optional features and configuration variations
• Safety documents and certifications
• Case studies for multiple market segments

Add to this the fact that equipment manufacturers serve customers across different industries and continents. That means documents are often duplicated, adapted for variations, or translated into multiple languages. This magnifies complexity, and complexity creates friction.

With AI, equipment manufacturers can deliver clarity, speed, and support at a completely new level. Imagine a customer operator in Mexico scanning a QR code on a control panel. The AmatriumGPT interface opens and the customer asks, in Spanish: “Cómo ajusto el flujo de aire de enfriamiento en esta máquina para la pieza 118C?” [“How do I adjust the cooling airflow on this machine for part 118C?”]

The system finds the relevant procedure (even if the original manual was written in German or Chinese, or English) and returns the request information in the Mexican dialect. For the equipment OEMs, this provides improved Customer Service with faster responses reflecting internal data.

The Company GPT concept

Free AI tools are powerful but they are not enough for industrial operations. Thet present a two-fold risk: data security, and that they learn from the user’s data uploads, search techniques, search topics (business and personal), and writing style. One should ask, ‘What are they doing with their knowledge of me?’

What manufacturers need - and what AmatriumGPT delivers - is a company-wide tool with unlimited seats, and one customer summarized it best: “The real power of AI is when it’s secured within a fence and using your own corporate data.”

This approach ensures:

• Data security
• Answers drawn from verified company documents
• Control over permissions and access
• Confidence that workflows remain consistent and protected

When every department - maintenance, engineering, safety, HR, EHS, marketing, sales  - can get answers in seconds, creativity and productivity surge. A young engineer has the same access to tribal knowledge as someone with 30 years of experience. A salesperson can produce a polished proposal in minutes. A maintenance tech can solve problems on the floor instantly. Perhaps the best ROI today is in Marketing, as they can now generate brochures, presentations, video scripts, blogs, and case studies in a fraction of the time. Much of a company’s literature is not public information, and it's the role of Marketing to apply the internal information to tell a story that informs the public.

The journey begins

AI is not a switch. It is a journey - a series of steps toward a smarter, more efficient manufacturing environment. For foundries and equipment producers, that journey is already underway. Company GPT is the first step, one taken by advanced companies like Ryder Systems.

Partner with an AI provider that will walk this journey together sharing experience on how to adopt tools into daily workflow and take advantage of decades of documentation. The partner will help you identify the first ROI, train your employees, and soon your company will be improving its global competitive position.

It’s a great time to get started toward the future.