Faculty & Research
Our school brings together scholars and practitioners from a range of disciplines—engineering and science, business, information systems, health, social sciences and the humanities—to study the issues critical to success in the new digital economy.
Their past and current involvement in the industry means that they bring fresh, relevant ideas to the classroom. While some are involved in groundbreaking research, others are frequently asked to speak at professional and academic conferences. It's more than just their accomplishments and research that make them valuable to the program - they're also experienced instructors and expert communicators.
Faculty Research Spotlight
March 28, 2019
Check out this recent article published by Dr. Margaret Plaza in the Computers & Industrial Engineering, external link entitled "The implication of learning curve on planning of machining processes"
Abstract
The study offers a decision support model, based on which managers from machining industry will be able to analyze their technology investment decision. The models allows to: (1) calculate the time, at which the costs of CNC machine tools and software that supports machining strategy development can be recovered, and (2) to analyze the impact of resource learning abilities on technology investment.
The project was conducted in collaboration with the Faculty of Mechanical Engineering at Cracow University of Technology and expands on the two previous projects completed in 2016 and 2018. The objective of those projects was to examine the role of machining in Smart Manufacturing (Industry 4.0), which is a revolutionary approach to production. Industry 4.0 amalgamates manufacturing with information technology in order to achieve the maximum output with minimum resource utilization.
The results of the previous two projects are published in: IJPE (https://doi.org/10.1016/j.ijpe.2018.09.007, external link), and CAIE (https://doi.org/10.1016/j.cie.2019.03.028, external link).
January 2019
Dr. Margaret Plaza's recent article entitled "Decision system supporting optimization of machining strategy" was published in Computers & Industrial Engineering, external link, the top ranked journal for 2017, external link.
Abstract
The study offers a decision model that allows to optimize the machining strategy in a virtual environment. The objective of optimization is to balance product quality with process efficiency and to assure the desired level of cost. The decision model allows the managers to explore the possibility of using less expensive grades for challenging applications. Those grades were previously considered unsuitable because of their inconsistent machinability.
The study was conducted as a collaborative effort between Ryerson University and the Faculty of Mechanical Engineering at Cracow University of Technology.
Continuing Education Instructors
| Instructor Name | Email Address |
| Ana Barcus | abarcus@ryerson.ca |
| Khalil Abuosba | abuosba@ryerson.ca |
| Claude Sam-Foh | csamfoh@ryerson.ca |
| David Chan | d22chan@ryerson.ca |
| Djordje Jankovic | d2jankov@ryerson.ca |
| Emad Samwel | esamwel@ryerson.ca |
| Hamid Faridani | faridani@ryerson.ca |
| George Foltak | gfoltak@ryerson.ca |
| Helen Chen | helend.chen@ryerson.ca |
| Ilia Nika | inika@ryerson.ca |
| Inka Bari | inka.bari@ryerson.ca |
| Irene Lee | irene.lee@ryerson.ca |
| Luminata Stubbs | lstubbs@ryerson.ca |
| Mourad Michael | michael@ryerson.ca |
| Mahmoud Jahani | mjahani@ryerson.ca |
| Nawar Hakeem | nawar.hakeem@ryerson.ca |
| Nurul Huda | nurul.huda@ryerson.ca |
| Roger DePeiza | r2depeiz@ryerson.ca |
| Roy Ng | royng@ryerson.ca |
| Soheila Bashardoust-Tajali | sbtajali@ryerson.ca |
| Selcuk Savas | selcuk.savas@ryerson.ca |