THE IMPACT OF AI IN TRAINING AND DEVELOPMENT ON FORGE SHOPS OF THE FUTURE

By THORS eLearning Solutions

As one of the oldest and most reliable manufacturing processes, the fundamentals of forging – such as controlled deformation, heat, force, and material flow – have changed little over time. Yet the industry itself is anything but static. Competitive pressures, workforce demographics, and expectations around productivity and consistency continue to rise.

Forging leaders routinely evaluate investments in equipment, tooling, and process improvements to meet these demands, but what is less visible, but equally critical, is employee development – evolving how people learn and how knowledge flows through the organization. Structured training programs are designed to develop people’s skills, which in turn directly influence quality, safety, production, and risk. As modern-day AI (artificial intelligence) tools like ChatGPT, Gemini, Claude, CoPilot and others become a normal part of how people learn and solve problems, the cost of relying solely on traditional or conventional training approaches is becoming harder to ignore.

With new classes of AI tools emerging and advanced AI capabilities now embedded in many commercial LMS platforms, the question for forging organizations is no longer whether AI-powered learning solutions are too futuristic for this industry. It is whether organizations can afford not to adapt as employee learning behavior itself changes.

There are many benefits to be gained from adding AI-based learning tools to the forging work environment, which we’ll explore in this article.

Learning Behavior Has Changed, While Training Systems Have Not

Outside the workplace, many employees already rely on AI tools to answer questions, summarize information, and explore cause-and-effect relationships. For new workers entering forging roles, this behavior is not new or experimental; it has become normal and natural.

When new employees encounter shop-floor training systems built around printed materials, physical manuals, or scattered digital files, friction appears. Initially, this shows up as lost time spent searching for answers or seeking help from a knowledgeable co worker. Over time, it becomes a deeper issue. Employees either accept “time-outs” for knowledge retrieval as standard operating procedure or they develop informal workarounds to get the information they need.

These all-too-common “blind spots” reflect a growing gap between how people expect to learn and solve problems – and how organizations provide information. When internal systems are difficult to navigate, employees do not stop learning – they simply look elsewhere.

Let’s look at ‘Closed-Die Forging’ as an example because it is widely used on shop floors.

Typical shop-floor challenges

New operators often learn the sequence of steps quickly: billet heating, placement, press operation, and part removal. What takes much longer to develop is the understanding behind those steps. How billet temperature affects die fill. How forging force influences flash formation. How lubrication impacts die life.

This difference – between knowing what to do and understanding why – matters. Operators who lack cause-and-effect understanding may struggle when conditions change, defects appear, or equipment behaves unexpectedly. Traditionally, this knowledge develops slowly through experience, trial and error, and mentoring. While effective, this approach consumes time, scrap, and supervisory resources, putting a strain on limited resources.

In contrast, AI-powered learning tools offer a way to accelerate this understanding without increasing production risk.

Why Traditional Training Struggles to Scale

Conventional forging training relies heavily on experience. Shadowing and mentoring new team members remains essential, but it can be difficult to scale this model consistently across shifts, facilities, and workforce turnover.

Documentation helps standardize expectations, but static instructions are unable to convey dynamic processes such as metal flow or defect formation. Manuals explain procedures, but they rarely build intuition. As a result, learning often remains reactive – focused on trial and error to gain experience, and correcting problems after they occur rather than preventing them.

With AI-powered learning solutions, hands-on training is paired with a learning layer that allows operators to explore processes, visualize outcomes, and build their decision-making skills before mistakes occur on the shop floor.

Practical Applications of AI in Closed-Die Forging Training

The following examples illustrate how AI-powered learning tools can support closed-die forging training in practical, shop-floor-relevant ways.

1. Parameter–Effect Exploration

AI-based learning tools allow learners to explore parameter effects virtually by enabling them to adjust variables such as billet temperature, forging force, lubrication level, and die alignment and immediately see the impact. Outcomes such as underfill, excessive flash, or die damage can be explored virtually using AI.

This approach builds cause-and-effect understanding rather than rote memorization. Operators develop intuition that helps them respond more effectively to real-world variability – without scrap or downtime.

2. Visual Demonstration of the Forging Sequence

Certain aspects of forging, such as internal metal flow and die cavity filling, are difficult to observe during production. AI-driven visual demonstrations address this gap by showing animated simulations of the forging sequence.

Operators can replay steps, isolate stages, and explore “what if” scenarios. For example, seeing how insufficient billet temperature leads to underfill reinforces concepts that are difficult to convey through text alone. It’s like having instant, interactive video replays – directly in the flow of work.

3. AI-Based Defect Recognition Training

Defect recognition is a skill typically built through experience. AI-based learning tools accelerate this process by presenting real images of forged parts and prompting learners to identify defects, probable causes, and corrective actions.

This reinforces the connection between process variables and outcomes, strengthening diagnostic judgment on the shop floor.

4. Voice-Based AI Assistants

Voice-based AI assistants allow operators to ask questions in plain language and receive concise explanations supported by images or short clips. This type of “hands-free” interaction is especially valuable in fast-paced environments – or for operators with limited English reading proficiency.

By reducing reliance on manuals or informal guidance, these tools help standardize understanding without slowing production.

5. Skill-Level Adaptive Learning

AI-powered learning tools can adjust content based on the learner’s experience level. New operators can focus on fundamentals, while more experienced personnel can explore more advanced skills such as process control, defect prevention, and die wear considerations.

This allows a single system to support multiple roles, reducing the need for separate training tracks.

The examples outlined above show how AI-powered learning tools can support learning at the individual skill level, making employees more efficient, confident and empowered. Moreover, giving employees easy access to accurate, approved knowledge not only improves overall efficiency, but also has direct consequences for consistency, safety, and risk across the operation.

When Access to Knowledge Falls Behind, Risk Increases

When access to accurate, approved information is inconsistent, variability follows. Operators rely on memory, coworkers, supervisors, outdated files, or whichever source is most readily available. When SOPs change, different teams or shifts may unknowingly work from obsolete/outdated versions of procedures or specifications. Over time, the impact of information gaps can compound – increasing rework, complicating audits, and introducing risk that is difficult to trace back to a single cause.

As all-purpose AI tools like ChatGPT, Claude, Gemini and others become common outside the workplace, another risk emerges. Employees may turn to these tools for explanations – without knowing whether the information they provide aligns with company-specific standards or safety requirements. The issue is not the AI tools themselves, but the lack of control over how knowledge is accessed and applied to company-specific challenges.

Commercially available AI tools from companies like OpenAI (ChatGPT), Google (Gemini), Anthropic (Claude), and Microsoft (Copilot) can be purchased and installed inside a company firewall to secure and protect any proprietary knowledge and information that’s shared. When properly implemented, this type of AI assistance can reduce risk by consistently surfacing approved procedures, specifications, and vetted institutional knowledge.

The Strategic Cost of Losing Control of Organizational Knowledge

Forging is a knowledge-intensive industry. Decisions related to die wear, press behavior, and process sequencing reflect years of experience. When the appropriate subject matter experts are not accessible – or if they retire – the company stands to lose the context, judgment, and continuity of their decision-making rationale.

AI assistants and AI-powered learning tools cannot replace expert judgment, but they can make that judgment accessible and reusable. The greatest cost of doing nothing is not measured in training hours, but in the gradual loss of control over how knowledge is shared and applied.

For forging leaders, the question is no longer whether or not AI-powered learning tools have an important role to play in employee training and development. The choice is whether to proactively embrace AI tools to shape employee learning and knowledge sharing – or allow that decision to be made informally, one workaround at a time.

Final Takeaways

AI-powered learning does not replace experience – it harnesses the knowledge that’s already there. By providing a way to capture and share the valuable knowledge the company has built up over time, AI learning tools democratize access to expertise.

When considering whether AI-powered learning tools are right for your organization, here are the key factors to remember:

  • Workforce learning has changed faster than traditional training systems.
  • AI-powered learning tools help operators build cause-and-effect understanding without scrap or downtime.
  • When properly used, AI tools can reduce risk by keeping learning aligned with approved processes.
  • The greatest risk is not adopting AI but losing valuable knowledge that benefits the wider organization.

In forging, knowledge has always been a competitive advantage. Using AI-powered learning tools helps companies leverage their knowledge as an asset, while ensuring that it remains controlled, accessible, and scalable, so that organizations can thrive and employees can excel.

About THORS eLearning Solutions:

THORS eLearning Solutions is a leading global provider of online technical courses and AI-powered productivity tools specifically designed for the manufacturing industry.

Founded in 2010, THORS eLearning Solutions has been transforming manufacturing education through THORS Academy, a visually engaging and ever-expanding eLearning library of over 230 expert-developed courses. Covering topics from manufacturing fundamentals and materials to quality standards and emerging technologies, THORS Academy empowers professionals to increase their knowledge base to keep up with today’s fast-paced manufacturing environment. To date, over 250,000 manufacturing professionals worldwide have advanced their expertise using THORS Academy.

The company’s newest offering, MFG Genius, is a powerful generative AI assistant providing technical knowledge on demand at the point of need. Trained on the vetted manufacturing knowledge of THORS Academy, as well as customer-supplied content, MFG Genius enables manufacturing teams to quickly resolve production challenges and optimize operational efficiency —all while supporting continuous improvement initiatives.

Trusted by Fortune 500 companies and their Tier 1 and Tier 2 suppliers across a diverse array of manufacturing sectors, THORS eLearning Solutions helps organizations boost productivity, empower learners, and optimize decision-making, while saving time and money.

Learn more at www.thors.com.

Senthil Kumar
Founder and CEO
THORS eLearning Solutions
Phone: 330-576-4448
Email: senthil.kumar@thors.com