Training: Strategy Development for Industrial AI

Digitalization has revolutionized the manufacturing industry, and artificial intelligence (AI) plays a central role in this transformation. Industrial AI is a key area that significantly influences a company’s competitiveness and innovative capacity. Through the targeted use of AI, operational processes can be optimized. Predictive maintenance and intelligent process control are just a few examples of how Industrial AI increases efficiency and minimizes downtime. However, to harness this potential of AI in industry, a suitable AI strategy is required. In our training course, you will learn how to develop a tailored strategy that fits your company and delivers concrete results. From identifying and evaluating industrial AI potential, to creating a use case roadmap, to planning concrete analytics projects, we’ll show you how to successfully implement AI strategically in a production environment. Our training offers an ideal platform to exchange ideas with experts facing similar challenges and to benefit from best practices.

The “Strategy Development for Industrial AI” training course is designed for decision-makers, executives, and manufacturing managers who want to develop an effective AI and data strategy for their company and successfully harness the full potential of their data in industrial AI projects.

• You will gain an understanding of the potential, opportunities, and challenges of industrial AI in manufacturing companies.
• Industrial AI: You will learn which methods and tools to use to analyze and evaluate operational and machine data in order to optimize your company’s manufacturing processes.
• You will be familiar with the typical challenges and success factors involved in planning and implementing AI projects.
• You will be able to successfully plan the implementation of industrial AI projects within your company.
• You will be able to define a forward-looking AI and data strategy and successfully embed it within your company.

• What are the fundamental concepts and technologies behind Industrial AI?
• Which concepts and methods are suitable for predictive maintenance, process optimization, and predicting machine failures?
• How can potential risks and challenges associated with the use of AI in industry be identified and minimized?
• What steps are necessary to seamlessly integrate AI systems into existing industrial processes?
• How do you develop an effective Industrial AI strategy?

After an introduction to the field of Industrial AI and its key concepts, methods and tools will be taught using a practical example from the mechanical and plant engineering sector. The following modules will cover the overarching topics of data sources, data infrastructure, data analytics, and use cases:

Day 1: Basic Terms and Concepts of Industrial AI

• Real-world examples and illustrations
• Analysis of business processes, resources, and data sources
• Identification and assessment of Industrial AI potential
• Organization of results into a use case roadmap

Day 2: Implementation Planning & Strategy Development for Industrial AI Projects

• Tools and best practices for a data inventory
• Analysis of the technical and legal framework
• Aligning use cases with a company’s AI, data and digitalization dtrategy
• Identifying changes required for the change process and the implementation of analytics projects
• Current trends and driving technologies in data analysis and AI
• Strategic considerations for the future

Day 3: Implementation Planning

• Applying the methods and concepts you’ve learned to your company’s specific situation
• Identifying opportunities for using AI in your company
• Developing action steps for successfully launching your industrial AI strategy

• Entrepreneurs, executives, managers
• Project management
• IT and manufacturing managers
• Employees in operational excellence and technology management