THE CHALLENGES OF APPLYING LEAN PRINCIPLES TO SMART MANUFACTURING
Open Access
Author:
Rusack, James Nathaniel
Area of Honors:
Supply Chain and Information Systems
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
John Jordan, Thesis Supervisor John Spychalski, Thesis Honors Advisor
Keywords:
smart manufacturing manufacturing big data IoT Internet of Things smart sensor sensor security quality lean principles lean methodology lean
Abstract:
This paper seeks to define and evaluate a set of important challenges that companies must solve to effectively implement smart manufacturing with a lean perspective. It is a qualitative analysis utilizing past research papers, business principles, and logic to decide which challenges are the most difficult to solve, as well as providing potential solutions to these problems. These challenges are managing big data and machine learning, managing the data security of the smart factory, implementing new technologies within ERP programs, and managing the data quality of the operation. There is a particular focus on managing data quality and data security as pressing concerns for a lean implementation of smart manufacturing. Additionally, the paper features cultural change as a major strategic element for defeating the technical challenges. Ideally, manufacturing companies will be able to use this paper to evaluate the current risks and benefits of implementing smart manufacturing in their operations while considering a lean perspective and will have a general guide of the areas for additional quantitative research to test the validity of these challenges and solutions.
