Silvia Jaqueline Urrea Contreras

Mrs. Silvia Jaqueline Urrea Contreras


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 February 2024 in Applied Sciences
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Journal Article
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SCSilvia Jaqueline Urrea Contreras
Silvia Jaqueline Urrea Contreras
MAMaria Angelica Astorga-Vargas
Maria Angelica Astorga-Vargas
BFBrenda L. Flores-Rios
Brenda L. Flores-Rios
JIJorge Eduardo Ibarra-Esquer
Jorge Eduardo Ibarra-Esquer
FGFelix F. Gonzalez-Navarro
Felix F. Gonzalez-Navarro
CPCarla Pacheco
Carla Pacheco
One of the challenges the organizations confront is to extract data from the information systems to know the reality of their processes to improve their efficiency. In this study, the application of Process Mining is addressed as an opportunity in the specific context of an SME dedicated to software development, implementing the L* life cycle model methodology from a layered Software Engineering approach. This research is carried out based on process improvement in an initial SME project. Subsequently, it is compared with a second project, using different Process Mining perspectives such as control flow, case, organization, and time, with the aim of extending the process model. This holistic view allows not only to better understand the processes involved, but also to identify and analyze the similarities and differences between the two projects. As a result, the Process Mining analysis shows crucial aspects such as the representation of integrated models, traces on sequences of actions, and the interaction of activities with specific roles and deviations in the flow of activities that compromise the quality of the process and the product. At the same time, the challenges that emerged during the improvement cycle are highlighted. These challenges cover issues such as data extraction, fluid communication between those involved, and the documentation associated with the processes. This study contributes to the body of knowledge of Process Mining. Likewise, the case study results offer a vision for other SMEs seeking to incorporate Process Mining as part of their improvement strategies.