The visual Miner is a free and open source process mining tool, which makes it easy to explore an event log.
Once you have an event log, the visual Miner will:
- Discover a process model using Directly Follows Miner or Inductive Miner;
- Align the discovered process model with the event log;
- Show where the discovered process model deviates from the event log;
- Compute performance measures for the model and for each activity; and
- Animate the event log on top of the discovered process model.
The visual Miner does not use an internet connection, and does not require data to be uploaded to a server, thus your data will not be transferred to anyone, anywhere.
The visual Miner is developed by Sander Leemans, and has been contributed to by Wil van der Aalst, Dirk Fahland, Erik Poppe and Moe Wynn from the Queensland University of Technology and the Eindhoven University of Technology.
The visual Miner has been applied by us in several organisations, including:
IBM: the visual Miner was used to compare purchasing processes and their performance accross geographic regions.
Maikel L. van Eck, Xixi Lu, Sander J.J. Leemans, Wil M.P. van der Aalst. PM ^2 : A Process Mining Project Methodology. CAiSE: 297-313, 2015.
A major Australian Government organisation: the visual Miner was used to document processes, to check conformance to prescriptive models, and to identify performance bottlenecks.
Sander J.J. Leemans, Erik Poppe, Moe T. Wynn Directly Follows-Based Process Mining: Exploration & a Case Study. International Conference on Process Mining 2019 in print
Queensland University of Technology: the visual Miner was used to analyse and optimise the student journey of PhD students.
Testimonial: "Utilising the Directly Follows visual Miner tool during workshops has been beneficial. Being able to visually see the deviations, frequencies and performance of the processes has facilitated robust discussion. All workshop participants, whether process focussed or not, are able to quickly comprehend the model and leverage the findings to identify process inefficiencies and drive potential process transformation." J. Barnes, Project Manager – Research Systems Upgrade Project.
Paper in progress
A major Queensland Government organisation: the visual Miner was used to perform performance analysis on their business processes.
Furthermore, the visual Miner has been applied by others in the following industries and processes:
- Breast cancer treatment (Italy, Netherlands)
Marazza F, Bukhsh FA, Vijlbrief O, Geerdink J, Pathak S, van Keulen M, Seifert C. Comparing Process Models for Patient Populations: Application in Breast Cancer Care.
- Lab test processes (India)
Ganesha K, Soundarya M, Supriya KV. The best fit process model for the utilization of the physical resources in hospitals by applying inductive visual miner. In 2017 International Conference on Inventive Communication and Computational Technologies (ICICCT) 2017 Mar 10 (pp. 318-322). IEEE.
- Operative medical processes (Thailand)
Toyawanit T, Premchaiswadi W. Applying inductive Visual Miner technique to analyze and detect problems in procedures of a hospital in Thailand. In2016 14th International Conference on ICT and Knowledge Engineering (ICT&KE) 2016 Nov 23 (pp. 98-104). IEEE.
- Hospital Information System processes (Cuba)
Garcia AO, Armenteros OU, Ramirez YE, Alfonso DP. Inductive visual miner plugin customization for the detection of eventualities in the processes of a hospital information system. IEEE Latin America Transactions. 2016 Jun 2;14(4):1930-6.
- Oncology (MIMIC-III, USA, UK, Indonesia)
Kurniati AP, Hall G, Hogg D, Johnson O. Process mining in oncology using the MIMIC-III dataset. InJournal of Physics: Conference Series 2018 Mar (Vol. 971, No. 1, p. 012008). IOP Publishing.
- Colorectal cancer treatment (Hungary)
Tóth K, Machalik K, Fogarassy G, Vathy-Fogarassy Á. Applicability of process mining in the exploration of healthcare sequences. In2017 IEEE 30th neumann colloquium (NC) 2017 Nov 24 (pp. 000151-000156). IEEE.
- Hepatitis treatment (the Netherlands, China)
Naeem MR, Naeem H, Aamir M, Ali W, Abro WA. A multi-level process mining framework for correlating and clustering of biomedical activities using event logs. International Journal of Advanced Computer Science and Applications. 2017 Mar 1;8(3):393-401.
- Curriculum adherence (Germany)
R. Buck-Emden, F-D Dahmann. Analyse von Studienverläufen mit Process-Mining-Techniken. HMD Praxis der Wirtschaftsinformatik: August 2018 Volume 55 Issue 4 (pp 846-865).
- Semi-structured learning processes (Canada)
Emond B, Buffett S. Analyzing student inquiry data using process discovery and sequence classification. International Educational Data Mining Society. 2015 Jun.
- Gas network malfunctioning alarm handling (France)
Es-Soufi W, Yahia E, Roucoules L. A process mining based approach to support decision making. In InIFIP International Conference on Product Lifecycle Management 2017 Jul 10 (pp. 264-274). Springer, Cham.
- Telecom incident management (Saudi-Arabia)
AlShathry O. Process mining as a process discovery technique: an incident management process as a case study. In J Comput Eng Inf Technol 5: 1. doi: http://dx. doi. org/10.4172/2324. 2016;9307:2.
- Production of industrial custom control panels (Brazil)
Meincheim A, dos Santos Garcia C, Nievola JC, Scalabrin EE. Combining Process Mining with Trace Clustering: Manufacturing Shop Floor Process-An Applied Case. In2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI) 2017 Nov 6 (pp. 498-505). IEEE.
- Warehouse moves & production traceability (Poland)
Markowski P, Przybyłek MR. Process mining methods for post-delivery validation. In 2017 Federated Conference on Computer Science and Information Systems (FedCSIS) 2017 Sep 3 (pp. 1199-1202). IEEE.
- Outsourced IT helpdesk (Brazil)
Richetti PH, de AR Gonçalves JC, Baião FA, Santoro FM. Analysis of knowledge-intensive processes focused on the communication perspective. In International Conference on Business Process Management 2017 Sep 10 (pp. 269-285). Springer, Cham.