Open AccessDiscrete-Events Simulation for Teaching Statistics in Industrial Engineering
Author(s) -
Farida S Said,
Iehann Eveno,
Jeanne Villaneau
Publication year - 2022
Publication title -
athens journal of technology and engineering
Language(s) - English
Resource type - Journals
eISSN - 2407-9995
pISSN - 2241-8237
DOI - 10.30958/ajte.9-1-4
Subject(s) - computer science , key (lock) , scheduling (production processes) , discrete event simulation , quality (philosophy) , industrial engineering , data science , engineering , simulation , operations management , philosophy , computer security , epistemology
This paper presents a discrete events simulation tool developed to support undergraduate students in their Statistics and Data Analysis course. Although the use of modern smart technologies in the industry contributes to a profusion of data, very few enterprise datasets are freely available, resulting in a serious lack of open real-world data for research and education. To overcome this difficulty, we designed a tool that simulates scheduling scenarios in a manufacturing environment. The generated data may be used to put statistical concepts and methods into practice to design cost-effective strategies for optimizing key performance indicators, such as reducing production time, improving quality, eliminating wastes, and maximizing profits. Keywords: industrial datasets, teaching statistics, discrete events simulation