Semester of Graduation
Theses & dissertations (College of Business)
First Major Professor
Dr. Sree Nilakanta
Master of Science (MS)
Information Systems, Statistics
The aim of the project is to increase the productivity of Danfoss’ assembly lines across the manufacturing facility at Ames, Iowa by continuously monitoring the performance with the help of a real-time tracking tool. The efficiency of the employees at each of the stations in the assembly lines, the time taken to procure the products or parts, the test time and the paint time, all impact the performance and production rate within the facility. Also, keeping few attributes constant, the time taken for the machines to pass a particular station within an assembly line determines the health of the assembly line and requires continuous monitoring. Minute errors on the assembly lines could stall production for hours resulting in an immense loss to the giant manufacturing companies like Danfoss. Therefore, the project is about implementing an algorithm that will monitor both the number of workers per shift per day at the assembly lines and the status of the machines on the line as they pass through each station on the assembly lines. On the other hand, a user-interactive dashboard allowsthe workers to monitor their progress versus the expected progress for the day. The live dashboard is scalable to other Danfoss assembly lines as a daily monitoring system
Vuyyuru, Tejaswini, "Using Predictive Maintenance techniques and Business Intelligence to develop smarter factory systems for the digital age" (2018). Creative Components. 114.