Business Process Simulation (BPS) is a common approach to estimate the impact of changes to a business process on its performance measures. For example, it allows us to estimate what would be the cycle time of a process if we automated one of its activities, or if some resources become unavailable. The starting point of BPS is a business process model annotated with simulation parameters (a BPS model). In traditional approaches, BPS models are manually designed by modeling specialists. This approach is time-consuming and error-prone. To address this shortcoming, several studies have proposed methods to automatically discover BPS models from event logs via process mining techniques. However, current techniques in this space discover BPS models that only capture waiting times caused by resource contention or resource unavailability. Oftentimes, a considerable portion of the waiting time in a business process corresponds to extraneous delays, e.g., a resource waits for the customer to return a phone call. This article proposes a method that discovers extraneous delays from event logs of business process executions. The proposed approach computes, for each pair of causally consecutive activity instances in the event log, the time when the target activity instance should theoretically have started, given the availability of the relevant resource. Based on the difference between the theoretical and the actual start times, the approach estimates the distribution of extraneous delays, and it enhances the BPS model with timer events to capture these delays. An empirical evaluation involving synthetic and real-life logs shows that the approach produces BPS models that better reflect the temporal dynamics of the process, relative to BPS models that do not capture extraneous delays.

翻译：业务流程仿真（BPS）是评估业务过程变更对其性能指标影响的常用方法。例如，它使我们能够估计：若自动化某活动或某些资源不可用，流程的周期时间将如何变化。BPS的起点是带有仿真参数注释的业务流程模型（即BPS模型）。传统方法中，BPS模型由建模专家手动设计，这一过程耗时且易出错。为解决此缺陷，多项研究提出通过过程挖掘技术从事件日志中自动发现BPS模型的方法。然而，当前该领域的技术仅能发现仅捕获由资源争用或资源不可用导致的等待时间的BPS模型。通常，业务流程中的大部分等待时间源于外部延迟（例如，资源等待客户回电）。本文提出一种从业务流程执行事件日志中发现外部延迟的方法。所提方法为事件日志中每组因果连续的活动实例，计算在相关资源可用条件下目标活动实例理论上应开始的时间。基于理论开始时间与实际开始时间的差异，该方法估计外部延迟的分布，并通过定时事件增强BPS模型以捕获这些延迟。涉及合成日志与真实日志的实证评估表明：相较于未捕获外部延迟的BPS模型，该方法生成的BPS模型能更准确地反映流程的时间动态特性。