Artificial intelligence approach to support statistical quality control teaching

Abstract Statistical quality control – SQC (consisting of Statistical Process Control, Process Capability Studies, Acceptance Sampling and Design of Experiments) is a very important tool to obtain, maintain and improve the Quality level of goods and services produced by an organization. Despite its importance, and the fact that it is taught in technical and college courses, as well as in companies’ training sectors, SQC has been largely misused. An inappropriate teaching approach may be the cause of such problem; therefore it has motivated the development of a model for SQC teaching, allowing its learners to correctly apply SQC techniques. After a survey regarding the concept needed to correctly apply SQC, its use and teaching/training methods, the model’s contents and methodology were defined. We also realized the opportunity of incorporating a computer environment for the model, permitting the practice of the needed SQC concepts and skills. An Artificial Intelligence approach was used to develop the computer environment, resulting in an Intelligent Tutoring System, the STCEQ. The paper discusses the main characteristics of the system, its functioning, benefits of using such a system and the results we obtained while using this system.