A configurable partial-order planning approach for field level operation strategies of PLC-based industry 4.0 automated manufacturing systems. (November 2017)

• Record Type: Journal Article
• Authors: Legat, Christoph; Vogel-Heuser, Birgit
• Is Part Of: Engineering applications of artificial intelligence. Volume 66(2017:Jun.)
• Page Start: 128
• Page End: 144
• Publication Date: 2017-11
• Subjects: Industry 4.0 -- Machine and plant automation -- Automated production systems -- Partial order planning -- Linear programming -- Field level automation software; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2017.06.014
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: 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 in strengthening 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 with respect to 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 large planning problems by exhibiting positive scalability characteristics which indicates its applicability for real-size plants.