Process Data Analysis Using Visual Analytics and Process Mining Techniques

Abstract

The research is carried out in the area of production process data analysis. The aim of this research is to explore the applicability of production process visualization methods using process mining techniques for production process analysis. The process mining is considered as a technique for process data analysis from event logs. Event logs store actual information about the course of investigated processes. In order to use this information in the most appropriate way for decision-making, raw event log data is transformed into a suitable format. One of these formats is visual representation. The transformation of data from event logs into informative visualizations is under consideration by approaches of visual analytics. The paper presents methods for analysing data on various levels, such as case, activity, and resource levels. Data is analysed from performance and bottleneck identification perspectives and visualised as area, column, and line graphs. The visualisation type is chosen to best fit the process analysis goals.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 10 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.