Container Logistics Object-centric Event Log

General Description Our company sells goods overseas. After receiving an order, the shipment of goods is scheduled. According to this schedule, the goods are picked up from the local production site and brought to a terminal where a logistics service provider receives and ships them. This is an artificial event log according to the OCEL 2.0 Standard simulated using CPN-Tools. Both the CPN and the SQLite can be downloaded. Process Overview From a customer order perspective, the process begins when the order is registered at our company (register customer order). After registration, a transport document is created in which details of the further process are recorded (create transport document). Using this information, the logistics service provider is contacted to coordinate the transport of the ordered goods to the seaport. Twice a week, that provider sends a vehicle to a terminal, with a limited capacity for containers of ordered goods to be transported from the terminal to a seaport. For our company, available capacties vary from vehicle to vehicle, as we are not the only company booking spots. Once the logistics service provider receives our transport documents, they book capacities according to availability and container prioritizations in the upcoming weeks (book vehicles). Once the dates for transporting the goods to the terminal are set, our company contacts a container depot to reserve the required containers (order empty containers). When a container’s vehicle departure approaches, the goods are prepared, packed and shipped to the terminal. For this purpose, a truck is sent to the container depot (pick up empty container). Meanwhile, the ordered goods to be shipped are packed into handling units at the production site. After loading the handling units (load truck), the truck drives the full container to the terminal (drive to terminal). At the terminal, the container is picked up by a free forklift and weighed (weigh). Unless the vehicle departure is imminent, the container is placed in the storage location at the terminal (place in stock). Finally, it is moved to the vehicle (bring to loading bay, load to vehicle) which departs at a fixed time (depart). Despite careful planning, containers sometimes miss a vehicle’s departure. In this case, the container is rescheduled to the next possible vehicle (reschedule container) and kept near the loading ramp until then. Further information can be found at: https://www.ocel-standard.org/beta/event-logs/simulations/logistics/ General Properties An overview of log properties is given below. Property Value Event Types 14 Object Types 7 Events 35761 Objects 14013 Control-Flow Behavior The behavior of the log is described by a respective object-centric Petri net. Also, individual object types exhibit behavior that can be described by simpler Petri nets. See below. Container Transport Documents Customer Order Truck Forklift Vehicle Handling Unit Object Relationships During the process, object-to-object relations can emerge at activity occurrences as follows. Activity Source Object Type Target Object Type Qualifier Create Transport Document Customer Order Transport Document TD for CO Book Vehicle Transport Document Vehicle Regular VH for TD Book Vehicle Transport Document Vehicle High-Prio VH for TD Order Empty Containers Transport Document Container CR for TD Pick Empty Container Truck Container TR loads CR Load Truck Container Handling Unit CR contains HU Reschedule Container Transport Document Vehicle Substitute VH for TD Simulation Model The CPN used to create this event log can also be downloaded.To obtain simulated data, extract the linked ZIP file and play out the CPN therein, e.g., by using CPN Tools. The play-out produces CSV files according to the schema of OCEL2.0. This Python notebook can be used to convert these files to an SQLite dump. For a technical documentation of the simulation model, please open the attached CPN with CPN Tools and see the annotations therein. Acknowledgements Funded under the Excellence Strategy of the Federal Government and the Länder. Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC-2023 Internet of Production - 390621612. We also thank the Alexander von Humboldt (AvH) Stiftung for supporting our research.

总体说明
本公司开展海外商品销售业务。在收到订单后，我们会规划货物的发运日程。依据该日程，工作人员会从本地生产场地提取货物，并将其运送至物流服务商接收并负责发运的终端场站。本数据集是一套遵循OCEL 2.0标准（OCEL 2.0 Standard）、通过CPN-Tools模拟生成的人工事件日志。CPN模型与SQLite数据库文件均可下载。

流程概览
从客户订单的视角来看，本流程始于客户订单在本公司的登记环节（登记客户订单）。订单登记完成后，系统会创建一份运输单据，用以记录后续流程的相关细节（创建运输单据）。凭借该单据的信息，我们会联系物流服务商，协调将订购货物运送至海港的相关事宜。该物流服务商每周会两次安排车辆前往终端场站，其用于将货物从场站转运至海港的集装箱运载能力存在上限。由于本公司并非唯一预订舱位的客户，可供使用的运载能力会因车辆不同而有所差异。当物流服务商收到我方的运输单据后，他们会根据未来几周的舱位可用情况与集装箱优先级来预订运力（预订车辆）。
待货物运至终端场站的日期确定后，本公司会联系集装箱堆场，预订所需的空集装箱（预订空集装箱）。当集装箱的车辆发运时间临近时，我们会完成货物的准备、包装，并将其运送至终端场站。为此，我们会安排卡车前往集装箱堆场提取空集装箱（提取空集装箱）。与此同时，待发运的订购货物会在生产场地被打包为装卸单元。在完成装卸单元的装载后（装载卡车），卡车会将满载的集装箱运送至终端场站（驶往终端场站）。在终端场站，空闲的叉车会将集装箱吊起并进行称重（称重）。除非车辆即将发运，否则集装箱会被放置在终端场站的存储区域（入库存放）。最终，集装箱会被移送至待装车辆（移至装载区，装载至车辆），车辆将按固定时刻发车（发车）。
尽管已进行周密规划，部分集装箱仍可能错过车辆的发运班次。在此情况下，该集装箱会被重新安排至下一班可用车辆（重新调度集装箱），并会被放置在装载坡道附近直至该班次发车。
更多相关信息可访问：https://www.ocel-standard.org/beta/event-logs/simulations/logistics/

通用属性
以下为日志的属性概览：
- 事件类型：14
- 对象类型：7
- 事件总数：35761
- 对象总数：14013

控制流行为
本日志的行为由对应的以对象为中心的Petri网（object-centric Petri net）描述。此外，各独立的对象类型也具备可通过更简易的Petri网进行描述的行为，详见下文。
对象类型包括：集装箱、运输单据、客户订单、卡车、叉车、车辆、装卸单元。

对象关联关系
在流程执行过程中，活动执行时会产生对象间的关联关系，具体如下：
| 活动 | 源对象类型 | 目标对象类型 | 限定符 |
| --- | --- | --- | --- |
| 创建运输单据 | 客户订单 | 运输单据 | TD for CO（对应客户订单） |
| 预订车辆 | 运输单据 | 车辆 | Regular VH for TD（常规车辆对应运输单据） |
| 预订车辆 | 运输单据 | 车辆 | High-Prio VH for TD（高优先级车辆对应运输单据） |
| 预订空集装箱 | 运输单据 | 集装箱 | CR for TD（对应运输单据的集装箱） |
| 提取空集装箱 | 卡车 | 集装箱 | TR loads CR（卡车装载集装箱） |
| 装载卡车 | 集装箱 | 装卸单元 | CR contains HU（集装箱包含装卸单元） |
| 重新调度集装箱 | 运输单据 | 车辆 | Substitute VH for TD（运输单据对应替代车辆） |

仿真模型
用于生成本事件日志的CPN模型同样可供下载。如需获取仿真数据，请解压所附的ZIP压缩包，并通过CPN Tools运行其中的CPN模型。运行该模型将生成符合OCEL2.0 schema的CSV文件。本Python Notebook可用于将这些文件转换为SQLite数据库导出文件。如需查看仿真模型的技术文档，请使用CPN Tools打开所附的CPN模型，并参阅其中的注释说明。

致谢
本研究受联邦政府与各州卓越战略资助。本研究由德国研究基金会（Deutsche Forschungsgemeinschaft, DFG）资助，项目为德国卓越战略 - EXC-2023 生产互联网 - 390621612。我们同时感谢亚历山大·冯·洪堡基金会（Alexander von Humboldt Stiftung, AvH）对本研究的支持。