Date of Award
Master of Science in Information Systems and Technology
Information and Decision Sciences
First Reader/Committee Chair
Advanced manufacturing technologies that enable big data analytics can boost productivity, increase efficiency, and enhance innovation. However, small and medium sized factories face unique challenges when implementing that technology. Plant managers of small and medium sized enterprises (SMEs) are often unsure of how to overcome those challenges in order to reap the benefits of big data analytics. This project examined the opportunities that have arisen due to the Fourth Industrial Revolution, also known as Industry 4.0; how small and medium sized manufacturers in the United States can move from traditional methods of manufacturing to advanced manufacturing, and how the additional data generated can enhance decision-making, specifically for plant managers. An investigation of the factors affecting big data analytics adoption in manufacturing SMEs was conducted, and case studies were examined in order to identify the unique challenges that exist and provide recommendations. The results of the investigation suggest that production managers should prioritize a specific area to focus on, use a big data lifecycle management framework, seek help to build and secure their operation systems, train and encourage employees, and collaborate with others in the industry.
Koppmann, Jolon, "Overcoming the Challenges of Big Data Analytics Adoption for Small and Medium Sized Enterprises in the Manufacturing Industry" (2021). Electronic Theses, Projects, and Dissertations. 1232.