A novel approach for predicting Lockout/Tagout safety procedures for smart maintenance strategies: dataset

The data are in Pickle format. Pickle in Python is primarily used in serializing and deserializing a Python object structure. In other words, it's the process of converting a Python object into a byte stream to store it in a file/database, maintain program state across sessions, or transport data over the network. These tables provide the names of the machines and the devices to be locked to secure them. <br> "industry"_name associates each sheet with its name. Each row corresponds to the ID of the Lockout/Tagout (LOTO) cards. The columns consist of the dictionary of machine names. LOTO sheets for different industrial sectors are proposed. The type of "industry" is specified in the title of each dataset. <br> "industry"_device associates each sheet with the types and numbers of devices to be locked. Each line corresponds to the ID of the Lockout/Tagout (LOTO) cards. The columns consist of the list of devices. The "industry"_name and "industry"_device lines refer to the same LOTO sheet. <br> The authors are available for further questions if needed.

本数据集采用Pickle格式存储。Python中的Pickle模块主要用于对Python对象结构进行序列化与反序列化操作。换言之，该过程指将Python对象转换为字节流，以实现将对象存储至文件或数据库、在不同会话间维持程序运行状态，或是通过网络传输数据的目的。

本数据集包含的表格列出了需锁定以保障安全的机器与设备名称。"industry"_name字段用于将每个工作表与其所属行业名称绑定。每一行对应一张上锁挂牌（Lockout/Tagout，简称LOTO）卡片的ID。各列以字典形式存储机器名称。本数据集提供了覆盖不同工业领域的LOTO工作表。各数据集的标题中均标注了其所对应的工业领域类型。

"industry"_device字段用于将每个工作表与需锁定的设备类型及数量绑定。每一行同样对应一张LOTO卡片的ID。各列以列表形式存储设备信息。"industry"_name与"industry"_device对应的为同一份LOTO工作表。

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