The machine and plant automation domain is faced with an ever increasing demand for ensuring the adaptability of manufacturing facilities in context of Industry 4.0. Field level automation software plays a dominant role for strengthen the overall flexibility of manufacturing resources. Classical programming approaches based typically on signal-oriented languages result in disproportionate effort for ensuring necessary flexibility. To address this challenge, a novel approach based on artificial intelligence planning techniques is presented which is able to handle domain specific requirements while facilitating efficient, scalable problem solving. Throughout this article, a discussion of specific requirements on automated planning techniques for field level automation software in the machine and plant automation domain towards Industry 4.0 is provided. An intensive study on existing works and their drawbacks towards addressing these requirements is presented. The proposed configurable partial-order planning approach is based upon a combination of an adapted goal-based planning formulation and its reformulation by means of linear programming techniques. It is shown that
the proposed approach is able to efficiently solve larger planning problems exhibiting positive scalability characteristics indicating its applicability for real-size plants.
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The machine and plant automation domain is faced with an ever increasing demand for ensuring the adaptability of manufacturing facilities in context of Industry 4.0. Field level automation software plays a dominant role for strengthen the overall flexibility of manufacturing resources. Classical programming approaches based typically on signal-oriented languages result in disproportionate effort for ensuring necessary flexibility. To address this challenge, a novel approach based on artificial i...
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