Abstract
To facilitate the planning of product processes, the Formalized Process Description (FPD) model was proposed. It enables users to graphically describe the requirements of a production process. However, the FPD model has limits. To overcome these limits, this paper describes an extension of the FPD model, which is called the Extended FPD model. The objects in the Extended FPD model are assigned types and logical statements to represent their specifications. Hence, the expressive power of the FPD model is enhanced. In this paper, a formal definition of the Extended FPD model is also presented. Based on this definition, a set of rules is defined to detect the contradictions automatically in the Extended FPD model. In addition, the description of requirements by using the Extended FPD model can also enable the integration of more formal verification methods.
Funding source: Federal Ministry of Education and Research (BMBF), Germany
Award Identifier / Grant number: 01IS20073E
About the authors
Cheng Xin received the B.S. degree in software engineering from Huaiyin Institute of Technology, JiangSu, China, in 2016. He received the M.S. degree in computer science from Hangzhou Dianzi University, Zhejiang, China, in 2019. He is currently working towards the doctoral degree at Otto-von-Guericke-University Magdeburg, Germany. He is also working as a guest researcher at the Institut f. Automation und Kommunikation e.V. Magdeburg, Germany. His current research interests include formal modeling and its applications in industrial areas.
Mario Thron is a member of the ICT & Automation department at the Institut f. Automation und Kommunikation e.V. Magdeburg, Germany. He studied electrical engineering with a focus on electronics and measurement technology. After his studies he planned, designed, programmed and worked on the commissioning of electrical systems for material handling systems. He joined ifak in 2000, where he is involved in research, specification and design of systems for machine and plant control. He is project manager for various research and industrial projects in this field.
Matthias Riedl is currently a member of the ICT & Automation department at the Institut f. Automation und Kommunikation e.V. Magdeburg (ifak e.V.), Germany. His interest is computer science, and he graduated in 1994. After graduation, he became an associate researcher at ifak e.V. He received his doctoral degree in 2005. Since 2008, he has led various research projects at the institute.
Acknowledgements
The authors would like to thank ITEA 3, the national funding authority of Germany (the Federal Ministry of Education and Research), and the partners of the ITEA 3 project AIToC (Artificial Intelligence supported Tool Chain in Manufacturing Engineering, https://aitoc.eu/) for their work and contributions that enabled this paper.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: This work is supported by the Artificial Intelligence supportedTool Chain in Manufacturing Engineering (AIToC) project, which is funded by Federal Ministry of Education and Research (BMBF), Germany (Grant No: 01IS20073E).
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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