Supplementary quality control features for the production department in Odoo ERP

Abstract

Odoo is one of the top Enterprise Resource Planning (ERP) applications. In particular, it is supported by a quality control module with the ability to control, trigger an alert, and check its purpose. This research strives to supplement the existing Odoo quality control module with parameters from past inspection data obtained before quality control migrates to Odoo. To support the study, we used a machine learning method to discover the intrinsic pattern from the dataset of quality control in the production process of baby biscuit products. The experiment shows that the additional quality control feature can provide the product measurement and tolerance threshold fed into Odoo quality control module. The additional feature is helpful for decision making and error minimization in setting quality control parameters and tolerance threshold. Furthermore, a high accuracy rate of 95.71% is obtained from the employed Decision Tree algorithm.