What does AI mean in industry?
In contrast to general AI, AI in industry focuses on specific areas of application, such as quality control, predictive maintenance, process optimization and robotics. AI in industry refers to the use of algorithms and machine learning to automate complex tasks, recognize patterns and make predictions. This involves analyzing and processing large volumes of data from machines and systems.
But why should companies rely on AI in industry?
The analysis can be used, for example, to detect faults in a machine in real time. The use of AI in industry allows for predictive maintenance, ensures product quality (predictive quality) and uses resources more efficiently (predictive energy).
What advantages does AI offer in industry?
This is why companies should use AI software:
- Increased productivity and OEE
- Transformation of the maintenance strategy towards condition-based maintenance
- Reduction in costs, e.g. for energy and production
- Improving occupational safety
- Competitive advantage through differentiation from the competition
- Improving quality
- Less unplanned downtime
The advantages of AI in production are manifold. For example, AI solutions such as predictive maintenance can detect faults before they lead to expensive downtime. If problems occur, maintenance measures can be initiated immediately: Unplanned downtime is avoided, maintenance costs are reduced and the company's productivity is increased. In this context, the data also contributes to occupational safety: Material fatigue can be partially detected and hazardous situations prevented.
Another major advantage of AI in industry is the improvement in product quality. By using AI, companies can detect and correct defects and errors at an early stage. Rejects and rework are reduced. This leads to greater customer satisfaction and a positive image for the company.
Predictive capability is therefore another important aspect of AI. By analyzing large amounts of data, AI algorithms can identify trends and patterns that other experts would normally miss. This enables companies to make well-founded decisions and cope better with future challenges.
The use of AI in industry: Step-by-step guide
The use of AI in industry requires careful planning and preparation. It is important to select the right AI technology for the company's specific requirements. Aspects such as scalability, flexibility and data compatibility should be taken into account. Thanks to the large number of AI projects we have completed in industry, we can provide valuable insights and show what needs to be considered when using AI in companies.
1. Make-or-buy decision:
Before an AI solution can be used, companies must decide whether they want to develop an AI solution internally or purchase one externally. In doing so, they must take their specific requirements, resources and budgets into account. How expensive can the planned solution be? Do we have enough specialists with expertise in AI, data science, IT and production, ...?
Finding the answer is not always easy. Find out more in our make-or-buy guide to AI solutions and use a checklist to find out when in-house or external production is the better option.
2. Data acquisition:
The relevant data sources in production, e.g. sensors, machine logs and quality control data, must be identified. Data connectivity must be guaranteed.
3. Data processing and analysis:
In order to use AI effectively, it is important to have sufficient high-quality data. These need to be cleaned up, structured and prepared for processing by the AI algorithms. The aim is to recognize patterns and correlations in the data.
4. Integration:
The AI solution is integrated into existing production systems. Comprehensive tests ensure that everything works smoothly and that the data can be processed in real time.
5. Training:
The AI models are trained with all the collected data. It is important to regularly review and adapt the training process to improve the accuracy and performance of the AI models. This ensures that the best results are always achieved.
With this step-by-step guide, you have a solid foundation for implementing AI in your production. AI offers enormous potential to optimize your production and increase your competitiveness.
Examples: Use of AI in industry
To illustrate the practical application of AI in industry, we will now look at some specific examples. These companies have decided to purchase an AI solution and have reaped the benefits.
- A company from the automotive industry has used Festo AX Industrial Intelligence to improve machine availability and quality assurance in body-in-white production. The use of AI algorithms made it possible to detect problems such as compressed air loss in real time and take immediate action. This significantly reduced rejects and rework, resulting in considerable cost savings. Unplanned downtimes have been reduced by 25%, the Mean-Time-To-Repair (MTTR) by 20%.
- Another company from the semiconductor industry has used Festo AX Industrial Intelligence to maximize the quality of its wafers. The AI analysis enabled typical sources of error in the sawing process (e.g. rough surfaces) to be recognized in advance. On this basis, quality assurance measures were launched at an early stage. The company has saved €100,000 per year due to the reduced waste per line.
Conclusion and outlook
The use of artificial intelligence in industry has enormous potential. It offers companies a wide range of benefits, such as increased efficiency, cost reduction and a better basis for decision-making.
The future of AI in industry is promising. As AI technologies continue to develop and awareness of their potential grows, the use of AI in industry will continue to increase. Companies should address the topic at an early stage and take advantage of the opportunities offered by AI to remain competitive and develop innovative solutions. There are already standardized AI solutions on the market for various applications, e.g. predictive maintenance of cylinders. These can be connected themselves and thus enable a simple and cost-effective entry for AI in industry.
The practical examples show how companies are already benefiting from AI in production. Whether you develop this AI solution yourself or buy it must be carefully weighed up. Buying an AI solution from experts offers advantages such as fast implementation, proven algorithms and a user-friendly interface. It is important to carefully weigh up the make-or-buy decision and consider the company's specific requirements and resources.
