论文标题
修复活动开始时间以改善业务流程模拟
Repairing Activity Start Times to Improve Business Process Simulation
论文作者
论文摘要
业务流程模拟(BPS)是估计业务流程变化的影响的常见技术,例如如果迹线数量增加,则过程的周期时间是多少? BPS的起点是用仿真参数(BPS模型)注释的业务过程模型。几项研究提出了通过过程挖掘技术自动从企业信息系统中提取的事件日志中自动发现BPS模型的方法。这些方法根据事件日志中记录的开始时间戳对每个活动的处理时间进行建模。但是,在实践中,常见的是,记录的开始时间不能准确反映活动的实际开始。例如,资源开始从事活动工作,但是直到与系统进行交互后,才记录其开始时间。如果没有纠正,这些情况会引起等待时间,而在实际工作时,她/她实际上在工作时被认为是免费的。为了解决这一限制,本文提出了一种技术,以确定资源实际上在其中工作的每个活动实例之前的等待时间,并修复其开始时间,以反映实际的处理时间。提出的技术的想法是,就仿真而言,一旦启用了活动实例,并且可以使用相应的资源。因此,对于每个活动实例,提出的技术根据事件日志中可用的信息估算活动启用和资源可用性时间,并修复包括未录制的处理时间的开始时间。涉及八个现实生活事件日志的经验评估表明,所提出的方法导致BPS模型密切反映了过程的时间动态。
Business Process Simulation (BPS) is a common technique to estimate the impact of business process changes, e.g. what would be the cycle time of a process if the number of traces increases? The starting point of BPS is a business process model annotated with simulation parameters (a BPS model). Several studies have proposed methods to automatically discover BPS models from event logs -- extracted from enterprise information systems -- via process mining techniques. These approaches model the processing time of each activity based on the start and end timestamps recorded in the event log. In practice, however, it is common that the recorded start times do not precisely reflect the actual start of the activities. For example, a resource starts working on an activity, but its start time is not recorded until she/he interacts with the system. If not corrected, these situations induce waiting times in which the resource is considered to be free, while she/he is actually working. To address this limitation, this article proposes a technique to identify the waiting time previous to each activity instance in which the resource is actually working on them, and repair their start time so that they reflect the actual processing time. The idea of the proposed technique is that, as far as simulation is concerned, an activity instance may start once it is enabled and the corresponding resource is available. Accordingly, for each activity instance, the proposed technique estimates the activity enablement and the resource availability time based on the information available in the event log, and repairs the start time to include the non-recorded processing time. An empirical evaluation involving eight real-life event logs shows that the proposed approach leads to BPS models that closely reflect the temporal dynamics of the process.