SUBJECT: Ph.D. Dissertation Defense
   
BY: Dazhong Wu
   
TIME: Friday, August 1, 2014, 10:00 a.m.
   
PLACE: MARC Building, 401
   
TITLE: Cloud-Based Design and Manufacturing: A Network Perspective
   
COMMITTEE: Dr. David W. Rosen, Co-Chair (ME)
Dr. Dirk Schaefer, Co-Chair (ME)
Dr. Thomas Kurfess (ME)
Dr. Leon F. McGinnis (ISyE)
Dr. Jitesh Panchal (ME, Purdue University)
 

SUMMARY

The overarching objective of this dissertation is to propose a new design and manufacturing paradigm, namely, Cloud-Based Design and Manufacturing (CBDM), for enhancing collaborative product development in distributed settings. In this dissertation, the following challenges pertaining to CBDM are addressed: (1) the systematic development of a conceptual framework that defines the computing architecture, information and communication flow, the design and manufacturing process, the programming model, data storage, and the business model of an idealized CBDM system; (2) the development of a new approach for visualizing distributed and collaborative design processes, and measuring tie strengths in a complex and large design team, detecting design communities with common design interests or activities in cloud-based design (CBD) settings from a social network perspective; and (3) the development of a new approach that helps identify potential manufacturing bottlenecks that determine manufacturing capacity scalability in cloud-based manufacturing (CBM) settings from a manufacturing network perspective. The research described in this dissertation contributes to the current body of knowledge from the following perspectives: It presents (1) a clear and complete vision for CBDM that defines the characteristics and requirements of CBDM systems as well as an idealized design and manufacturing scenario in a hypothetical CBDM setting; (2) a generic social network analysis (SNA)-based approach for modeling, analyzing information flow, and supporting design communication and collaboration in a CBD setting; and (3) a discrete event simulation-based approach for modeling, analyzing material flow, and planning manufacturing scalability in a CBM setting.