SUBJECT: Ph.D. Dissertation Defense
BY: Ruoyu Song
TIME: Thursday, April 25, 2019, 9:00 a.m.
PLACE: MRDC Building, 4404
TITLE: Towards Automated Guidance for Helping Novices Design for Sustainable Additive Manufacturing and CNC Machining
COMMITTEE: Dr. Cassandra Telenko, Chair (ME)
Dr. Thomas Kurfess (ME)
Dr. Christopher Saldana (ME)
Dr. Yan Wang (ME)
Dr. Frank Durso (Psychology)


Thanks to computer-aided design (CAD) and computer-aided manufacturing (CAM) software, novice engineering designers can engage in product design and production more easily, increasing opportunities for innovation. Despite this increase in computer support, novice designers still make improper design decisions which unnecessarily increase the manufacturing costs and fabrication failures that lead to higher environmental impacts. Manufacturers can provide feedback to novice designers to assist them change design decisions but often not because of knowledge gap and time consideration. Some design for manufacturing (DFM) software have been developed to provide feedback, but these software tools are not designed for novice designers. Novice designers and DFM experts are different in cognition, knowledge level and communication experiences which cause the current approaches cannot assist novices to decrease the environmental impacts. Therefore, this research aims to discover what feedback content should be provided to novice designers, and what strategies best communicate the content. This research proposes to provide new feedback content including DFM guidelines and design suggestions to assist novice designers to change design decisions using automated software. The feedback content and strategies were developed from existing databases, benchmarking studies, interviews and observation studies of communications between machinists and designers in a university machining mall. Feedback content and strategies were tested using prototype software.