The increasing complexity of industrial processes leads to complex process visualizations. Amongst other things, this is often due to the fact that a visualiza-tion engineer does not have deep knowledge of all physical and logical relations inside a plant. Additionally, different operators have to work with the same vis-ualization despite the fact, that their personal preferences, abilities and needs dif-fer. Having to work with unclear and confusing visualizations leads to an in-creased workload for plant operators and thus to higher error rates. Due to cost and time constraints, creating better or user-specific visualizations manually is not possible, especially because taking the operators' specific knowledge and ex-perience into account is difficult. This paper presents a concept to automatically generate process visualizations and support systems by the usage of a knowledge base and an influence model. This allows for operator-specific visualizations, considering preferences, abilities and needs. It also eases the visualization engineer's work by automatically choos-ing suitable diagrams and their properties. Additionally, by providing a system to acquire the operator's knowledge, complex relations inside a plant can be made accessible and utilized for optimizing the production process and visualization.
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The increasing complexity of industrial processes leads to complex process visualizations. Amongst other things, this is often due to the fact that a visualiza-tion engineer does not have deep knowledge of all physical and logical relations inside a plant. Additionally, different operators have to work with the same vis-ualization despite the fact, that their personal preferences, abilities and needs dif-fer. Having to work with unclear and confusing visualizations leads to an in-creased workloa...
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