Abstract
In this chapter, we discuss the description of two related yet different notions—connectivity and causality. Connectivity shows a physical or information linkage between process units; this linkage illustrates qualitative process knowledge without using first-principle models. The main resources for establishing connectivity are process flow diagrams (PFDs) and piping and instrumentation diagrams (P&IDs); thus we need to convert them into standard formats, such as adjacency matrices, digraphs, and semantic web models, which are easily accessible and computer-friendly. Causality between process variables can be built through process data as well as process knowledge; thus it can be described qualitatively, yet sometimes with certain quantitative information, by structural equation models, matrices and digraphs, and matrix layout plots.
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Yang, F., Duan, P., Shah, S.L., Chen, T. (2014). Description of Connectivity and Causality. In: Capturing Connectivity and Causality in Complex Industrial Processes. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-05380-6_3
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DOI: https://doi.org/10.1007/978-3-319-05380-6_3
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