Abstract
For future manufacturing systems with a high variety in products and a dynamic production environment, concepts for adapting production are becoming more important. Errors in processes need to be detected quickly and a fast reaction is necessary to prevent failures. Minimizing production stops and swiftly getting back to production is one main goal. Manufacturing systems have to become more intelligent to be able to autonomously react on errors. We propose an approach for explicitly modeling error handling steps in production workflows and using these models to influence the production process. Depending on the type of error, different strategies for resolving the error are executed. The error handling is embedded into an autonomous planning architecture for adaptable manufacturing systems. The approach is evaluated using an experimental setup that is designed for educational purposes. The results are presented and discussed in this paper.
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