Integrated Framework of Process Mining and Simulation Approaches for the Efficient Diagnosis and Design of Business ProcessIntegrated Framework of Process Mining and Simulation Approaches for the Efficient Diagnosis and Design of Business Process
- Other Titles
- Integrated Framework of Process Mining and Simulation Approaches for the Efficient Diagnosis and Design of Business Process
- Authors
- 아체 사레이도렛하니; 한관희
- Issue Date
- 2017
- Publisher
- 한국콘텐츠학회
- Keywords
- Process Mining; Simulation; Diagnosis & Design; Business Process; Process Innovation; 프로세스 마이닝; 시뮬레이션; 진단 및 설계; 비즈니스 프로세스; 프로세스 혁신
- Citation
- 한국콘텐츠학회 논문지, v.17, no.5, pp 221 - 233
- Pages
- 13
- Indexed
- KCI
- Journal Title
- 한국콘텐츠학회 논문지
- Volume
- 17
- Number
- 5
- Start Page
- 221
- End Page
- 233
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/14624
- DOI
- 10.5392/JKCA.2017.17.05.221
- ISSN
- 1598-4877
2508-6723
- Abstract
- To survive in the ever-changing environment, organizations need to improve or innovate their business processes. As a result, to attain this objective, BPM (Business Process Management) concept is widely adopted in modern enterprises. BPM life cycle consists of diagnosis, design, implementation and enactment. Conventionally, diagnosis of business process within the BPM life cycle is usually conducted by manual methods such as interviews, questionnaires and direct observations of process. And (re)designing business processes is also usually done manually under supervision of business experts from scratch. It is time-consuming and error-prone tasks.
The objective of this research is to integrate the diagnosis and (re)design phase of BPM life cycle by sharing automatically generated process model and basic statistics in the diagnosis phase based on the process mining method. Eventually, this approach will lead to automate the tasks of diagnosis and design of business process. To implement and to show the usefulness of the proposed framework, two case studies were conducted in this research.
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Collections - 공과대학 > Department of Industrial and Systems Engineering > Journal Articles

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