• Title/Summary/Keyword: 프로세스마이닝

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Comparison between Planned and Actual Data of Block Assembly Process using Process Mining in Shipyards (조선 산업에서 프로세스 마이닝을 이용한 블록 조립 프로세스의 계획 및 실적 비교 분석)

  • Lee, Dongha;Park, Jae Hun;Bae, Hyerim
    • The Journal of Society for e-Business Studies
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    • v.18 no.4
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    • pp.145-167
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    • 2013
  • This paper proposes a method to compare planned processes with actual processes of bock assembly operations in shipbuilding industry. Process models can be discovered using the process mining techniques both for planned and actual log data. The comparison between planned and actual process is focused in this paper. The analysis procedure consists of five steps : 1) data pre-processing, 2) definition of analysis level, 3) clustering of assembly bocks, 4) discovery of process model per cluster, and 5) comparison between planned and actual processes per cluster. In step 5, it is proposed to compare those processes by the several perspectives such as process model, task, process instance and fitness. For each perspective, we also defined comparison factors. Especially, in the fitness perspective, cross fitness is proposed and analyzed by the quantity of fitness between the discovered process model by own data and the other data(for example, the fitness of planned model to actual data, and the fitness of actual model to planned data). The effectiveness of the proposed methods was verified in a case study using planned data of block assembly planning system (BAPS) and actual data generated from block assembly monitoring system (BAMS) of a top ranked shipbuilding company in Korea.

A Study on Procurement Audit Integration Real Time Monitoring System Using Process Mining Under Big Data Environment (빅 데이터 환경하에서 프로세스 마이닝을 이용한 구매 감사 통합 실시간 모니터링 시스템에 대한 연구)

  • Yoo, Young-Seok;Park, Han-Gyu;Back, Seung-Hoon;Hong, Sung-Chan
    • Journal of Internet Computing and Services
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    • v.18 no.3
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    • pp.71-83
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    • 2017
  • In recent years, by utilizing the greatest strengths of process mining, the various research activities have been actively progressed to use auditing work of business organization. On the other hand, there is insufficient research on systematic and efficient analysis of massive data generated under big data environment using process mining, and proactive monitoring of risk management from audit side, which is one of important management activities of corporate organization. In this study, we intend to realize Hadoop-based internal audit integrated real-time monitoring system in order to detect the abnormal symptoms in prevent accidents in advance. Through the integrated real-time monitoring system for purchasing audit, we intend to realize strengthen the delivery management of purchasing materials ordered, reduce cost of purchase, manage competitive companies, prevent fraud, comply with regulations, and adhere to internal control accounting system. As a result, we can provide information that can be immediately executed due to enhanced purchase audit integrated real-time monitoring by analyzing data efficiently using process mining via Hadoop-based systems. From an integrated viewpoint, it is possible to manage the business status, by processing a large amount of work at a high speed faster than the continuous monitoring, the effectiveness of the quality improvement of the purchase audit and the innovation of the purchase process appears.

Analysis of Munitions Contract Work Using Process Mining (프로세스 마이닝을 이용한 군수품 계약업무 분석 : 공군 군수사 계약업무를 중심으로)

  • Joo, Yong Seon;Kim, Su Hwan
    • Journal of Intelligence and Information Systems
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    • v.28 no.4
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    • pp.41-59
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    • 2022
  • The timely procurement of military supplies is essential to maintain the military's operational capabilities, and contract work is the first step toward timely procurement. In addition, rapid signing of a contract enables consumers to set a leisurely delivery date and increases the possibility of budget execution, so it is essential to improve the contract process to prevent early execution of the budget and transfer or disuse. Recently, research using big data has been actively conducted in various fields, and process analysis using big data and process mining, an improvement technique, are also widely used in the private sector. However, the analysis of contract work in the military is limited to the level of individual analysis such as identifying the cause of each problem case of budget transfer and disuse contracts using the experience and fragmentary information of the person in charge. In order to improve the contract process, this study analyzed using the process mining technique with data on a total of 560 contract tasks directly contracted by the Department of Finance of the Air Force Logistics Command for about one year from November 2019. Process maps were derived by synthesizing distributed data, and process flow, execution time analysis, bottleneck analysis, and additional detailed analysis were conducted. As a result of the analysis, it was found that review/modification occurred repeatedly after request in a number of contracts. Repeated reviews/modifications have a significant impact on the delay in the number of days to complete the cost calculation, which has also been clearly revealed through bottleneck visualization. Review/modification occurs in more than 60% of the top 5 departments with many contract requests, and it usually occurs in the first half of the year when requests are concentrated, which means that a thorough review is required before requesting contracts from the required departments. In addition, the contract work of the Department of Finance was carried out in accordance with the procedures according to laws and regulations, but it was found that it was necessary to adjust the order of some tasks. This study is the first case of using process mining for the analysis of contract work in the military. Based on this, if further research is conducted to apply process mining to various tasks in the military, it is expected that the efficiency of various tasks can be derived.

The Knowledge-Based Design Paradigm through Web Data Mining and Knowledge Management Framework (웹 데이터 마이닝과 지식경영 프레임웍을 통한 지식-기반 디자인 패러다임 구축)

  • 양종열
    • Archives of design research
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    • v.15 no.4
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    • pp.159-168
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    • 2002
  • The world has rushed into knowledge information society. Information technology is one of the causes to show up knowledge management and one of the motives to accelerate knowledge management. And, these days information technology and internet have made staffing progress. Therefore, the objective of this study is to take out latent knowledge of customers through web data mining in a vast amount of data on the internet in rapidly developing digital environments, to develop the knowledge-based design paradigm applied to knowledge management framework, and finally to develop design which satisfies customers' needs. To reach the objective, knowledge management process and varied previous studies related to web data mining are reviewed on a theoretical basis, and then a new knowledge-based design paradigm (in this study, eCRM in a true sense which combines web data mining with knowledge management process is called knowledge-based design paradigm) combining knowledge management process with web data mining is suggested.

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Workflow Mining Technique(Heuristic Approach) (워크플로우 마이닝 기법(휴리스틱접근))

  • Lee Myoung-Hee;Chang Young-Won;Yoo Cheol-jung;Jang Ok-bae
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07b
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    • pp.412-414
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    • 2005
  • 최근들어 기업의 업무가 더욱 전문화되고 복잡해짐에 따라 워크플로우 시스템도 복잡해지고 다양해 지고 있다. 이러한 문제로 인하여 실제 필요로 하는 프로세스의 관리 및 도출이 요구된다. 본 논문에서는 영향력있는 프로세스를 도출하고 지원하기 위한 워크플로우 마이닝에 관하여 분석한 후 분석을 바탕으로 상관관계분석과 주성분분석을 통하여 워크플로우를 보다 효율적으로 관리할 수 있는 마이닝 규칙을 제시한다.

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Usage Pattern Analysis and Comparative Analysis among User Groups of Web Sites Using Process Mining Techniques (프로세스 마이닝을 이용한 웹 사이트의 이용 패턴 분석 및 그룹 간 비교 분석)

  • Kim, Seul-Gi;Jung, Jae-Yoon
    • The Journal of Bigdata
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    • v.2 no.2
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    • pp.105-114
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    • 2017
  • Today, many services are supported on the web sites. Analysis of usage patterns of web site visitors is very important to optimize the use and efficiency of the web sites. In this study, analysis of usage patterns and comparative analysis of user groups were conducted by analyzing web access log provided by BPI Challenge 2016. This data provides access logs to the web site in the IT system of a Dutch Employee Insurance Agency (UWV). The customer information, and the click data describing the customers' behavior when using the agency's web site. In this study, we use process mining techniques to analyze the usage patterns of customers and the characteristics of customer groups, and ultimately improve the service quality of customers using web services.

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Research on Data Acquisition Strategy and Its Application in Web Usage Mining (웹 사용 마이닝에서의 데이터 수집 전략과 그 응용에 관한 연구)

  • Ran, Cong-Lin;Joung, Suck-Tae
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.3
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    • pp.231-241
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    • 2019
  • Web Usage Mining (WUM) is one part of Web mining and also the application of data mining technique. Web mining technology is used to identify and analyze user's access patterns by using web server log data generated by web users when users access web site. So first of all, it is important that the data should be acquired in a reasonable way before applying data mining techniques to discover user access patterns from web log. The main task of data acquisition is to efficiently obtain users' detailed click behavior in the process of users' visiting Web site. This paper mainly focuses on data acquisition stage before the first stage of web usage mining data process with activities like data acquisition strategy and field extraction algorithm. Field extraction algorithm performs the process of separating fields from the single line of the log files, and they are also well used in practical application for a large amount of user data.

A Workcase Mining Mechanism using Activity Dependency (액티비티 의존성을 이용한 워크케이스 마이닝 메커니즘)

  • Kim Sang-Bae;Kim Hak-Seong;Paik Su-Ki
    • Journal of Internet Computing and Services
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    • v.4 no.6
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    • pp.43-55
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    • 2003
  • Workflow mining is a newly emerging research issue for rediscovering and reengineering workflow models from workflow logs containing information about workflows being executed on the workflow engine. In this paper, we proposed workcase mining which was used dependency among activities. Main purpose of this paper is to minimize discrepancies between the modeled workflow process and the enacted workflow process as it is actually being executed. That is, we can get a complete set of activity firing sequences on buildtime. Besides, we can discover from workflow logs that which path out of all reachable paths a workcase has actually followed through on runtime. For this purpose we proposed two algorithm, the one is 'Activily-Dependent Net Algorithm' and the other is 'E-Walk Series Analysis Algorithm'.

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Analysis of Business Process in the SCM Sector Using Data Mining (데이터마이닝을 활용한 SCM 부문에서의 비즈니스 프로세스 분석)

  • Lee, Sang-Young;Lee, Yun-Suk
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.6 s.44
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    • pp.59-67
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    • 2006
  • If apply BPM that is a business process management tool to SCM sector, efficient process management and control are available. Also, BPM can execute integrating process that compose SCM effectively. These access method does to manage progress process of SCM process more efficiently and do monitoring. Also, It is can be establish plan about improvement of process analyzing process achievement result. Thus, in this paper, introduce this BPM into SCM environment. Also, SCM process presents plan that executes integration and improves business process effectively applying data mining technique.

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Aspect Mining Process Design Using Abstract Syntax Tree (추상구문트리를 이용한 어스팩트 마이닝 프로세스 설계)

  • Lee, Seung-Hyung;Song, Young-Jae
    • The Journal of the Korea Contents Association
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    • v.11 no.5
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    • pp.75-83
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    • 2011
  • Aspect-oriented programming is the paradigm which extracts crosscutting concern from a system and solves scattering of a function and confusion of a code through software modularization. Existing aspect developing method has a difficult to extract a target area, so it is not easy to apply aspect mining. In an aspect minning, it is necessary a technique that convert existing program refactoring elements to crosscutting area. In the paper, it is suggested an aspect mining technique for extracting crosscutting concern in a system. Using abstract syntax structure specification, extract functional duplicated relation elements. Through Apriori algorithm, it is possible to create a duplicated syntax tree and automatic creation and optimization of a duplicated source module, target of crosscutting area. As a result of applying module of Berkeley Yacc(berbose.c) to mining process, it is confirmed that the length and volume of program has been decreased of 9.47% compared with original module, and it has been decreased of 4.92% in length and 5.11% in volume compared with CCFinder.