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중소 조선기자재 업체를 위한 클라우드 컴퓨팅기반 BPM-ERP 시스템 개발 및 적용
정동규(Donggyu Jung),조지운(Chiwoon Cho),남용식(Yongsic Nam) 대한산업공학회 2010 산업공학 Vol.23 No.2
Marine equipment makers today face a multitude of challenges including the needs of an internal system for easy management of their business processes and a collaboration system to streamline communications with the parent company, increasing product complexity and heightened requirements for information technology. In this research, a BPM-ERP system called Biz Tower<SUP>®</SUP> was implemented based on cloud computing for especially, small and medium marine equipment makers to standardize and visualize the entire business process from order placement to release. This system also provides their parent company with visibility into the status of orders and user can easily access the system on the web at a low price through cloud computing service. Thus far, this paper demonstrates the applicability of Biz Tower<SUP>®</SUP> to improve management visibility, process performance, and collaboration with the parent company for small and medium marine equipment makers.
Hind R’bigui(르비기 힌드),Chiwoon Cho(조지운) 대한산업공학회 2018 대한산업공학회 추계학술대회논문집 Vol.2018 No.11
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.