以活動層級時間偵測企業異常流程之研究

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姓名

莊玉成(Yu-Cheng Chuang) 查詢紙本館藏

畢業系所

企業管理學系

論文名稱

以活動層級時間偵測企業異常流程之研究
(Using Contextualized Activity-Level Duration to Discover Irregular Process Instances in Business Operations)

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摘要(中)

高效的時間管理是一個成功企業重要的特徴之一，對大多數的企業而言，它也是一個必須時時精進與改善的議題。在企業每日營運活動中，異常流程會破壞整體的協同性與敏捷性，甚至會導致重大的損失。
優秀的管理者必須能不斷地找出潛在的異常流程，提前做出預防性的動作以避免發生不正確的流程。本研究採用 k-Nearest Neighbor 演算法，能夠計算出各流程的活動層級時間，並利用這些計算的結果，偵測出企業營運流程中異常的流程實例。
這些活動層級的時間，包括執行時間(execution), 傳遞時間(transmission), 等待時間(queuing) and 延遲時間(procrastination). 除此之外，流程的運行過程中，也會受到代理人如業務人員，生管人員，客戶及其他因素影響。這些影響流程運作的本文訊息(contextual information) ，能夠用模糊集合論的歸屬函數(membership functions)呈現出來，並用以校正活動層級的時間。
此演算法被植入一個全球性的中小企業的資訊系統中，經過一年的運作後，我們擷取該企業的資訊系統日誌並用以偵測異常流程. 實証結果經專家驗証，正確性達 81%

摘要(英)

Effective time management is one of the most crucial characteristics of a successful business. For most businesses, time management is an area that can always be improved. Irregularities in execution duration of business processes impede corporate agility and can incur severe consequences, such as project failure and financial loss. Efficient managers must constantly identify potential irregularities in process durations to foresee and avoid process glitches.

This paper proposes a k-nearest neighbor method for systematically detecting irregular process instances in a business by using a comprehensive set of activity-level durations, namely execution, transmission, queue, and procrastination durations. Moreover, because agents, customers, and other variables influence the progress of processes, contextual information is presented using fuzzy values. The values and corresponding membership functions are used to adjust the duration of each activity.

This proposed method was applied to the system logs of a medium-sized logistics company to identify irregularities. Experts confirmed that 81% of the instances identified as irregular were abnormal.

關鍵字(中)

★ 工作流程
★ 活動層級時間
★ 流程異常偵測
★ 流程實例
★ 模糊集合論

關鍵字(英)

★ Workflow
★ Activity-level duration
★ Process irregularities
★ Instances
★ Fuzzy set

論文目次

中文摘要 ..Ⅰ
ABSTRACT Ⅱ
致謝 Ⅲ
INDEX Ⅴ
LIST OF FIGURES Ⅵ
LIST OF TABLES Ⅶ
Chapter 1. Introduction 1
1.1 Research Background Information………………………………………………………................1
1.2 Framework of the Proposed Model ….……………………….....................................................2
1.3 Organization of the Dissertation …………………………………………………………................3
Chapter 2. Literature Review 4
2.1 Enterprise Modeling …….………………………………………………………………………............ 4
2.2 Irregularity Detection in Business Processes …………………………………………............ 5
2.3 Time management ……………………………………………….……………………………….............6
2.4 Durations in Business Process Studies ……………..……………………………………........... 7
Chapter 3. Methodology 10
3.1 Data Derived from eBusiness systems embedded with workflow modules 10
3.2 Outlier Detection based on Activity Level Durations 10
3.3 Identifying Irregular Process Instances 15
Chapter 4. Estmating Activity-Level Durations with Contextual Information 18
4.1 Contextual variables and related fuzzy functions 18
4.2 Estmating Duration with Joined Fuzzy sets 21
4.3 The examples of Estimating durations with joined fuzzy sets 22
Chapter 5. Case Application ………………………………………………………………………………..........26
5.1 Contextual Variables 30
5.2 Evaluation Metrics 31
5.3 The Experiment Result 32
Chapter 6. Conclusion and Future Research 41
6.1 Conclusion 41
6.2 Research Limitation and Futre Research 42
References 43

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指導教授

許秉瑜(PingYu Hsu)

審核日期

2015-6-18

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