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논문 기본 정보

자료유형
학술대회자료
저자정보
Hind R’bigui (울산대학교) Chiwoon Cho (울산대학교)
저널정보
대한산업공학회 대한산업공학회 추계학술대회 논문집 2018년 대한산업공학회 추계학술대회 및 정기총회
발행연도
2018.11
수록면
368 - 375 (8page)

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초록· 키워드

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Most of the organizations adopt Business Intelligence (BI) tools, and/or Business Process Management (BPM) techniques to enhance their operational performance and gain a competitive advantage in the common market. However, the focus of BI tools is tailored toward data and local decision making rather than end-to-end processes. BPM provides the organization with an end-to-end process understanding, visibility and control while ensuring efficient communication in an organization. BPM systems use process models to analyze the -as-is‖ and -to-be‖ processes. Nevertheless, these models are absolutely disassociated from actual data as they are based on the idealized model of reality rather than real observations. Process mining provides a strong bridge between BI and BPM by combining both process models and event data forming a novel form of process-driven analytics. Process mining analyzes the behavior of companies by extracting process-oriented knowledge from event logs recorded in today`s information systems. This paper describes an industrial application of process mining in a real order fulfillment process of a shipbuilding industry. Event data are extracted from the Shipbuilding Processing Plan Management System and analyzed using process mining techniques. The findings of this application can be used by the company as a foundation to enhance their processes.

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Abstract
1. INTRODUCTION
2. CASE STUDY
3. CONCLUSION
REFERENCES

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