Public Available Data Set of Process Flows from Internal Physical Inspections in the Failure Analysis Laboratory

This data set was generated in accordance with the semiconductor industry and contains data of certain process flows in Failure Analysis (FA) laboratories focusing on the identification and analysis of anomalies or malfunctions in semiconductor devices. It comprises logistic data about the processing steps for the so-called Internal Physical Inspection (IPI).
A so-called IPI job is given as a sequence of tasks that must be performed to complete the job they belong to. It has an assigned unique ID and timestamps indicating the submission, the end, and the deadline to be met. A job also has an IPI classification assigned to it, providing general guidelines on the operations to be performed.
Every task within a job has its own type and working time, as well as the assigned resources. There are two main resources involved:
            - the equipment; the machine used to perform the task,
            - the operator; the person who performed the task.
In addition, general information about the type of the device to be analyzed is also available, such as the given (anonymized) package and basictype. Data also include the number of stressed samples within a device and the samples a task is performed on.
The dataset includes data from 4 years, specifically from January 2020 to December 2022.
Finally, the exact column structure is given as follows (python 3.9.5 datatype):

JOB_ID [int64]: the unique ID of the job
JOB_SUBMISSION_DATE [object]: the date of the job submission
JOB_REQ_END_DATE [object]: the required end date (deadline)
JOB_FINISH_DATE [object]: the actual end date
JOB_BASICTYPE_H [object]: the given basictype denotation
JOB_PACKAGE_H [object]: the package denotation of the device
JSH_QTY_STRESSED [float64]: number of stressed samples
TASK_SUBMISSION_DATE [object]: the date of the task submission
TASK_WORKING_TIME [float64]: the amount of time (hours) the task needs to be completed
TASK_SAMPLE_NO [object]: the samples the task was performed on 
TASK_CEQ_ID [float64]: the ID of the machine used to perform the task
TASK_CTKS_ID [int64]: the ID representing the task type
TASK_USR_ID [int64]: the ID of the operator performing the task
CIPI_LEVEL_0 [object]: a series of IPI classifications, indicating what is required to execute for a specific job