AI in manufacturing: use cases and examples
Artificial intelligence is revolutionizing the production industry. Today, it helps companies optimize processes, reduce costs, and improve product quality. But how exactly does it work? In this article, we will show how AI is applied in areas such as knowledge management, IT support, and approval processes. We will look at practical examples and provide insights into which technological approaches are best suited for different production environments.
AI in manufacturing: Beyond automation
What used to apply to simple automation — efficiency gain, relief, cost savings, speed increase — now applies to AI. But what is the advantage of AI over simple automation?
Artificial intelligence (AI) and traditional automation are two different approaches to optimizing production processes.
While automation is specialized in executing predefined tasks, AI goes a step further. AI refers to the ability of systems to perform human-like cognitive functions, such as learning, problem-solving, and decision-making.
Unlike automation, which is rigid and inflexible, AI can react flexibly to new situations and learn from experiences. This enables dynamic adaptation to changing production requirements and continuous process improvement. AI thus offers a higher level of adaptability and efficiency beyond the possibilities of traditional automation.
Just as automating certain processes has been indispensable in recent years — in the future, reinforcing certain processes with AI systems will become indispensable as well.
The significance of AI in manufacturing
The production industry faces numerous challenges and must adapt to ever-changing market conditions at an unprecedented speed. AI systems can address these challenges. AI can help manufacturing companies increase their efficiency, reduce costs, improve product quality, and achieve a variety of positive effects in human resources.
Efficiency increase
The manufacturing industry, like any other, is marked by increasing competition. AI can help companies increase their efficiency and productivity. By automating and optimizing workflows, manufacturing processes can be accelerated. This leads to faster production and allows companies to better utilize their resources and achieve their production goals more efficiently.
Cost reduction
Rising costs are a significant challenge for the manufacturing industry. AI provides solutions to reduce these costs. By automating and optimizing workflows, companies can reduce their operating costs. This leads to more cost-effective manufacturing, as less manual intervention is required and the efficiency of processes increases. Companies can thus improve their competitiveness and increase their profit margins.
Quality improvement
Another benefit of implementing AI is improving product quality. AI systems can monitor manufacturing processes in real-time and respond immediately to deviations. This reduces errors and scrap, increasing product quality. Automated inspections and fault detection ensure precise monitoring and control of production processes.
Addressing the skilled labor shortage
The wave of retirements and the shortage of skilled workers are massive problems in the manufacturing industry. AI can help mitigate this issue by taking over a portion of the tasks — routine tasks. This allows the remaining employees to be deployed where they are most needed. By automating routine tasks, companies can optimally use their existing skilled workforce and increase their productivity.
In this context, a reference to the term “augmented intelligence” is essential: AI will never fully replace the human workforce, and it is not meant to. Rather, we should view AI as a tool that supports employees in their work.
Increased employee satisfaction
Relieving employees from routine tasks through AI can lead to higher job satisfaction. Employees are freed from monotonous tasks and can focus on more challenging and fulfilling tasks, which can boost their motivation and satisfaction.
This can also help reduce turnover, as employees feel valued and challenged. Higher employee satisfaction ultimately has a positive impact on the overall work environment and the company’s productivity.
Use cases and applications of AI in manufacturing: Examples
Let’s now look at various applications and concrete use cases that show how AI is being used in practice. AI technologies are transforming the manufacturing landscape and offering companies significant benefits.
Quality control
Automating inspection and fault detection
Knowledge management
Simplified documentation and providing expertise to all employees
Predictive maintenance
Predicting maintenance needs based on sensor data
Production planning and control
Optimizing manufacturing processes through real-time data analysis
Warehouse management and logistics
Efficiently managing inventory and optimizing transportation routes
Quote generation
Automating the generation of quote drafts from existing data
Quote analysis and verification
Analyzing the extensive requirements of the customer and distributing the feasibility check to teams
IT support
Automatically answering common IT inquiries and relieving the support team
Approval processes
Searching and analyzing documents and reports, as well as automating responses to recurring questions
Let’s now take a closer look at some of the use cases.
AI for knowledge management in manufacturing
Problem: In many manufacturing companies, valuable information is lost because it is unstructured, scattered across chats and documents. This leads to inefficient processes and wasted time.
Solution: AI can help make this information accessible. By implementing an AI system, employees can get answers immediately without having to search for a long time.
Technical implementation
- RAG solution: RAGs help query internal data across platforms through natural language and ensure that any AI hallucinations are suppressed.
- AI-based audio documentation: Employees can document their expertise via voice messages; the AI transcribes and maintains it in the knowledge database.
Benefits
- Quick and direct answers to specific questions.
- Reduction of time loss and improvement in efficiency.
The AI solution for knowledge management in the manufacturing industry
ONTEC AI is an augmented intelligence platform that provides employees with easy access to internal knowledge. Document knowledge, chat with documents, trigger actions with AI agents… customized to the needs of the company.
AI-supported quote generation in manufacturing
Problem: Generating quotes is often time-consuming and resource-intensive. Information is scattered and must be painstakingly compiled.
Solution: AI can automatically generate quote drafts from existing offers and additional data. This includes analyzing and reusing customer inquiries, searching documents and emails, and recognizing recurring technical challenges.
Benefits
- Less manual effort
- Faster quotes, especially for simple offers
- Better decisions and higher closure rates
Technical implementation
- Analysis of customer inquiries: Comparison with previous offers and products.
- Searchability of documents: Immediate availability of relevant information.
- Recognition of technical challenges: Automated classification based on realization probability.
- Integration with existing systems: AI can be connected to different systems, such as SAP, to extract prices, customer data, and other relevant information.
AI for quote analysis and verification
Problem: Potential customers send detailed documents of 100 pages or more that describe the desired product. Multiple teams need to review the offer and assess its feasibility — manually, this is not scalable.
Solution: AI can analyze documents and forward relevant parts to the respective teams. The documents are compared with historical products, for example: “Didn’t we already have this heat treatment issue? How did we solve it back then?”
Benefits
- Reduced manual effort
- Faster and optimized offers
- Increased efficiency, especially for complicated offers
Technical implementation
- Analysis of customer inquiries: Comparison with previous offers and products.
- Searchability of documents: Immediate availability of relevant information.
- Recognition of technical challenges: Automated classification based on realization probability.
AI-supported IT support in manufacturing
Problem: Routine inquiries block the IT support team, leaving complex issues unresolved.
Solution: AI can automatically answer frequent inquiries by searching previous tickets, manuals, and knowledge databases.
Benefits
- Faster solutions for users
- Less ticket volume
- More efficient IT support
Technical implementation
- Automatic answering of frequent inquiries: Before ticket creation.
- Relief for support teams: Focus on more complex topics.
AI-supported monitoring of approval processes
Problem: Approval processes are often lengthy and require the review of large amounts of data.
Solution: AI can search documents for relevant information and automate responses to recurring questions, making the process more efficient.
Benefits
- Faster retrieval of important documents and decisions.
- Automated responses to recurring questions.
- More efficient approval process.
Technical implementation
- Targeted document search: Find relevant information in seconds.
- Automated answers: Efficiently answer recurring questions.
Future prospects
The implementation of AI in manufacturing companies will continue to increase. Future developments could offer even more efficient and flexible solutions that adapt to market changes and customer requirements.
In the long term, AI will revolutionize the manufacturing industry by optimizing processes, reducing costs, and improving quality.
Since 2025, “AI agents” are particularly being discussed, which can even perform actions autonomously. For example, an agent can recognize that a particular building material is running low, actively search for the best offer, and automatically trigger a reorder.
The long-term impacts of implementing AI in manufacturing companies are profound. Companies that invest early in AI technologies will be able to improve their processes in time and adapt to new challenges. This leads to sustainable competitiveness and a stronger market position.
Conclusion and key takeaways
Artificial Intelligence is now indispensable in modern manufacturing. It provides solutions to numerous challenges and enables companies to significantly increase their efficiency and productivity.
From quality control to predictive maintenance to quote generation and IT support — AI is versatile and offers numerous benefits.
Additionally, the implementation of AI can positively impact employees by reducing routine tasks and increasing job satisfaction.
- AI has diverse applications: It can be used in various areas of manufacturing, including quality control, maintenance, production planning, inventory management, quote generation, IT support, and approval processes.
- AI can increase efficiency while reducing costs: AI optimizes workflows, reduces errors, and lowers manufacturing costs, leading to faster and more cost-effective manufacturing.
- AI can have many positive impacts on employees: AI relieves employees of routine tasks, increases job satisfaction, and can reduce turnover by enabling more challenging and fulfilling tasks.
Through continuous development and adaptation of AI technologies, manufacturing companies can revolutionize their processes and achieve long-term success.