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姓名 傅嘉良(Chia-Liang Fu)  查詢紙本館藏   畢業系所 工業管理研究所
論文名稱 一致化不同顆粒度所衍生企業流程之研究
(Solving multi-level business process consistence issues based on Heuristic algorithm)
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摘要(中) 流程探勘技術被廣泛利用於企業流程管理,而目前許多研究指出利用流程探
勘由事件日誌所推導出的企業流程以及企業預期的流程模型若兩者不一致,則有
可能產生企業內部管理的缺失。由事件日誌推導企業流程的過程中,因為事件日
誌有著不同的階層而產生不同的顆粒度,而本研究要解決的是從同一資料庫由於
顆粒度不同所推導出的企業流程差異問題。
另一方面以事件日誌推導企業流程一般利用活動間互動的頻率來決定企業
流程的方向,但此方式容易忽略了次數少但是價值高的企業流程,導致啟發式演
算法無法找出真實代表企業運作的企業流程,在本研究中提出一種新的方法取代
一般的以次數推導企業流程,而是針對數量以及流程價值對事件日誌進行推導。
本研究利用調整啟發式演算法中的直接相依係數來解決一致性差異的問題。
使用啟發式演算法,並提出一種新的調整直接相依係數的方法,可有效的提升啟
發式演算法的精確度以及求解速度。
本研究利用石材加工業之事件日誌進行案例驗證,比較兩種不同顆粒度所推
導出的企業流程,給定其中一個顆粒度的企業流程直接相依係數門檻值,利用啟
發式演算法求解出相對應的直接相依係數門檻值,此方法可以解決在相同事件日
誌的情況下因為不同顆粒度而產生的企業流程不一致,找出相對應一致的企業流
程。

摘要(英) Process mining technology has been widely used in business process management.
At present many studies have indicated the use of process mining deduced from the
event logs show that if the business process and business process models expected are
inconsistent, it may be a risk of internal mismanagement.
In the process of deduced business processes, the event log has a different levels
result in different of grains. As the result, in this study we try to resolve the
differences business process deduced from the different grain in the same database.

On the other hand, business process derives from the event logs usually use the
frequency of the activities interaction to determine the direction of the business
processes. But this method ignores the few times and high-value business processes,
the heuristic algorithms cannot identify the real business operations business process

This study presents a new method to replace to derive business processes use the
frequency, against quantity and processes value to derive business processes.

In this study, we use the directly dependent coefficient of the adjusted heuristic
algorithm to solve the problem of the difference consistency, and propose a new way
to adjust directly dependent coefficients, which can effectively improve the accuracy
and solving speed of the heuristic algorithm.

In this study, we use the stone industry for case validation, comparing two business
processes deduced from different grain, give one of the business processes a directly
dependent coefficient threshold value, then use of heuristic algorithms for solving the iv

corresponding direct dependent coefficient threshold value. This method can solve the
inconsistent business processes from the different grain in the same database, and
identify the corresponding consistent business processes.
關鍵字(中) ★ 顆粒度
★ 企業流程
★ 流程探勘
★ 啟發式演算法
★ 價值鏈
★ 生產力
關鍵字(英) ★ grain
★ business processe
★ process mining
★ heuristics algorithm
★ value chain
★ productivity
論文目次 目錄
摘要 II
目錄 VI
一、 緒論 1
1-1動機與研究背景 1
1-2研究目的 4
二、文獻探討 6
2-1 流程探勘 6
2-2價值鏈及生產力 8
2-3 啟發式演算法 9
2-4流程一致性 10
三、方法 13
3-1 研究架構 13
3-2 資料前處理 15
3-3 啟發式演算法 20
3-4 資料轉換 21
3-5流程一致性 22
3-6產生斐氏圖 24
四、系統實作 26
4-1 系統實作資料敘述 26
4-2 系統實作流程 26
4-2-1 資料前處理 27
4-2-2 計算活動之直接相依係數 29
4-2-3 資料轉換 31
4-2-4 調整流程一致性 32
4-2-5 建構斐氏圖 36
4-3 實驗分析 38
4-3-1 原研究分析 38
4-3-2 實際實驗及分析 42
五、結論與未來研究建議 44
5-1 結論 44
5-2 未來研究建議 45
六、文獻參考 46
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指導教授 許秉瑜(Ping-yu Hsu) 審核日期 2014-7-17
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