Engineering Science and Materials Commons^™

Impulse, Fall 2022, University Marketing And Communications, Jerome J. Lohr College Of Engineering

Impulse (Jerome J. Lohr College of Engineering Publication)

2 | Sanjeev Kumar Takes Helm as College’s 12th Dean
5 | College Develops Partnerships in India, Turkey
6 | Faculty News
8 | Aerofly — Profs, Alum Partner To Build Unique Drone
10 | Researchers Find Way to Extend Produce Shelf Life
12 | SDSU Claims National Title in Quarter-Scale Tractors
14 | Nation’s Top ASCE Chapter Housed at SDSU
16 | National Geo-Video Title Won By State Students
18 | Summer Brings Engineering Camps to Campus
20 | Haleigh Timmer — Money on the Court, In Classroom
22 | Daniel Burkhalter — Day in the Life of Student-Athlete …

A Deep Reinforcement Learning Approach With Prioritized Experience Replay And Importance Factor For Makespan Minimization In Manufacturing, Jose Napoleon Martinez

LSU Doctoral Dissertations

In this research, we investigated the application of deep reinforcement learning (DRL) to a common manufacturing scheduling optimization problem, max makespan minimization. In this application, tasks are scheduled to undergo processing in identical processing units (for instance, identical machines, machining centers, or cells). The optimization goal is to assign the jobs to be scheduled to units to minimize the maximum processing time (i.e., makespan) on any unit.

Machine learning methods have the potential to "learn" structures in the distribution of job times that could lead to improved optimization performance and time over traditional optimization methods, as well as to adapt …

Grinding And Super-Finishing Test Machine Project, Michael Simon

Williams Honors College, Honors Research Projects

A research project in The University of Akron to study grinding and super-finishing of silicon nitride ceramic was initiated by Dr. Siamak Farhad and sponsored by the Timken Company, with the assistance of undergraduate students Michael Simon, Ryan Hosso and Mathew Rozmajzl. The study required analysis of forces and scratches generated during grinding processes of silicon nitride samples. A testing assembly was designed and constructed to record the forces generated during grinding and super-finishing of silicon nitride samples in a computer-numerical-control machine. Silicon nitride samples were subjected to desired grinding and super-finishing operations and all forces generated during the process …