Dua Weraikat

Assistant Professor of Industrial Engineering

RIT Dubai

dxwcad@rit.edu

Dua Weraikat

Assistant Professor of Industrial Engineering

RIT Dubai

Bio

Dr. Dua Weraikat earned her Ph.D. in Industrial Engineering from Concordia University- Canada in 2016. She worked as a Postdoctoral Fellow with Forest E-business Research Consortium, FOR@C, at University Laval-Canada where she was involved in research projects that aimed to improve the auctioning systems applied by Québec government for the Forest Industry.

Before moving to Canada, Dr. Dua Weraikat earned her Master’s degree in Manufacturing-Industrial Engineering from University of Jordan. Her research was focused on grains refinement effect on the fatigue rate for Zamak-5 Alloys.

In August 2016, Dr. Dua Weraikat joined RIT-Dubai as an assistant professor in the Industrial Engineering Department. She is teaching courses for undergraduate and graduate students including Probability and Statistics, Project Management, and Engineering Systems.

Dr. Dua Weraikat is a regular member of CIRRELT (Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation), CORS (Canadian Operations Research Society), and informs (Institute for Operations Research and management Science). Dr. Weraikat research interests lie in Operation Research, Green Supply Chain, Collaboration Mechanisms in Reverse Supply Chain for Perishable Products, and Coordination in Pharmaceutical Supply Chains. She has a number of publications in high-ranked journals in the field of Industrial Engineering.

dxwcad@rit.edu

Currently Teaching

ISEE-120

Fundamentals of Industrial Engineering

3 Credits

This course introduces students to industrial engineering and provides students with foundational tools used in the profession. The course is intended to prepare students for their first co-op experience in industrial engineering by exposing them to tools and concepts that are often encountered during early co-op assignments. The course covers specific tools and their applications, including systems design and integration. The course uses a combination of lecture and laboratory activities to cover hands-on applications and problem-solving related to topics examined in lectures.

ISEE-301

Operations Research

4 Credits

An introduction to optimization through mathematical programming and stochastic modeling techniques. Course topics include linear programming, transportation and assignment algorithms, Markov Chain queuing and their application on problems in manufacturing, health care, financial systems, supply chain, and other engineering disciplines. Special attention is placed on sensitivity analysis and the need of optimization in decision-making. The course is delivered through lectures and a weekly laboratory where students learn to use state-of-the-art software packages for modeling large discrete optimization problems.

ISEE-323

Systems and Facilities Planning

3 Credits

A basic course in quantitative models on layout, material handling, and warehousing. Topics include product/process analysis, flow of materials, material handling systems, warehousing and layout design. A computer-aided layout design package is used.

ISEE-499

Co-op

0 Credits

One semester of paid work experience in industrial engineering.

ISEE-561

Data Analytics and Predictive Modeling

3 Credits

In systems where parameters can vary, we often want to understand the effects that some variables exert on others and their impact on system performance. “Data Analytics and Predictive Modeling” describes a variety of machine learning and data analysis techniques that can be used to describe the interrelationships among such variables. In this course, we will examine these techniques in detail, including data cleansing processes, data clustering, associate analysis, linear regression analysis, classification methods, naïve Bayes, neural networks, random forests, variable screening methods, and variable transformations. Cases illustrating the use of these techniques in engineering applications will be developed and analyzed throughout the course.

ISEE-720

Production Control

3 Credits

This course covers the process and the analysis methods used to produce goods and services to support of the production and operations management functions. Topics include: forecasting, inventory policies and models, job shop scheduling, aggregate production planning, and ERP systems. Students will understand the importance of production control and its relationship to other functions within the organization, and the role of mathematical optimization to support production planning. The course emphasizes how a production process can be characterized by a process that requires answering a sequence of decision-making problems. The course will show how the production functions integrate with each other and how their coordination can be automated through mathematical programming. Identifying opportunities for improvement through optimization is also highlighted.

ISEE-752

Decision Analysis

3 Credits

This course presents the primary concepts of decision analysis. Topics important to the practical assessment of probability and preference information needed to implement decision analysis are considered. Decision models represented by a sequence of interrelated decisions, stochastic processes, and multiple criteria are also addressed. We cover EMV and Non-EMV decision-making concepts. Finally, the organizational use of decision analysis and its application in real-world case studies is presented.

ISEE-792

Engineering Capstone

3 Credits

Students must investigate a discipline-related topic in industrial and systems engineering. The general intent of the engineering capstone is to demonstrate the students' knowledge of the integrative aspects of a particular area. The capstone should draw upon skills and knowledge acquired in the program.