A prediction model of Lockout/Tagout safety procedures for smart maintenance strategies

Published: 23 December 2022| Version 1 | DOI: 10.17632/vy6rxr85cr.1
Contributor:
Victor Delpla

Description

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. df_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. df_dispo 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 df_name and df_dispo lines refer to the same LOTO sheet. The authors are available for further questions if needed.

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Institutions

Ecole de technologie superieure

Categories

Machine Learning, Safety, Deep Learning, Industrial Machinery

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