garments-worker-productivity
OpenML dataset with id 42989
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22045660/garments-worker-productivity.arff
Upload date: 28 May 2021
Dataset Characteristics
Number of features: 15 (numeric: 11, symbolic: 0 and in total binary: 0 )
Number of instances: 1,197
Number of instances with missing values: 506
Number of missing values: 506
Productivity Prediction of Garment Employees Data Set
The Garment Industry is one of the key examples of the industrial globalization of this modern era. It is a highly labour-intensive industry with lots of manual processes. Satisfying the huge global demand for garment products is mostly dependent on the production and delivery performance of the employees in the garment manufacturing companies. So, it is highly desirable among the decision makers in the garments industry to track, analyse and predict the productivity performance of the working teams in their factories. This dataset can be used for regression purpose by predicting the productivity range (0-1) or for classification purpose by transforming the productivity range (0-1) into different classes.
This dataset includes important attributes of the garment manufacturing process and the productivity of the employees which had been collected manually and also been validated by the industry experts.
Attribute information
01. date : Date in MM-DD-YYYY
02. day : Day of the Week
03. quarter : A portion of the month. A month was divided into four quarters
04. department : Associated department with the instance
0.5 team_no : Associated team number with the instance
06. no_of_workers : Number of workers in each team
07. no_of_style_change : Number of changes in the style of a particular product
08. targeted_productivity : Targeted productivity set by the Authority for each team for each day.
09. smv : Standard Minute Value, it is the allocated time for a task
10. wip : Work in progress. Includes the number of unfinished items for products
11. over_time : Represents the amount of overtime by each team in minutes
12. incentive : Represents the amount of financial incentive (in BDT) that enables or motivates a particular course of action.
13. idle_time : The amount of time when the production was interrupted due to several reasons
14. idle_men : The number of workers who were idle due to production interruption
15. actual_productivity : The actual % of productivity that was delivered by the workers. It ranges from 0-1.
This page was built for dataset: garments-worker-productivity
