Packaging Industry Anomaly DEtection (PIADE) Dataset

PIADE dataset contains data from five industrial packaging machines:

Machine s_1: from 2020-01-01 14:00:00 to 2021-12-31 13:00:00

Machine s_2: from 2020-06-17 08:00:00 to 2021-12-31 07:00:00

Machine s_3: from 2020-10-07 12:00:00 to 2022-01-01 23:00:00

Machine s_4: from 2020-01-01 01:00:00 to 2022-01-01 23:00:00

Machine s_5: from 2020-01-20 08:00:00 to 2022-01-01 12:00:00

## Raw Data

Each row represents a production interval, with the following schema:

interval_start: start of the production interval    

equipment_ID: equipment identifier    

alarm: alarm code of the active stop reason, if it occurred     

type: idle, production, downtime, performance_loss or scheduled_downtime    

start: start of the production interval    

end: end of the production interval    

elapsed: duration of the production interval    

pi: input packages    

po: output packages    

speed: speed (packages per hour)

There are 133 different types of alerts, and 429394 rows.

## Sequences (1h) data

For each piece of equipment, we define sequences of length = 1 hour and we aggregate raw interval data as follows:

'equipment_ID': machine identifier

'#changes': changes in machine state

'%downtime': time spent in 'downtime' state

'%idle': time spent in 'idle' state

'%performance_loss': time spent in 'performance loss' state

'%production': time spent in production

'%scheduled_downtime': time spent in scheduled downtime

'count_sum': sum of all alarm occurrences

'A_': counter of alarm occurrences

'/': number of transitions from to