• BS Industrial Engineering, MUST,
• MSc. Manufacturing Systems Engineering, UPM,
• PhD. Operations Management, NTNU,
Norway (10 th
August 2012- Present)
• Applying a Fuzzy Based Production Scheduling Model in Reconfigurable
,, N, Ismail.
Journal of Manufacturing
• Application of Artificial Intelligent in Production Scheduling: a critical evaluation and comparison of key approaches.
, N, Ismail
. 2nd International
Conference on Industrial Engineering and Operations Management
• Graph Theory for Operations Research and Management: Applications in
Industrial Engineering (2012), Editors: Reza Zanjirani Farahani and Elnaz
Miandoabchi, Chapter Title: Inbound Logistics and Vehicle Routing, Authors: R,
Z. Farahani; H, Rashidi-Bajgan;
, Publisher: IGI Global.
• Complex challenges of real-world production planning and control
• Is MRP an ultimate solution for planning?
To develop a new intelligent adaptive model to handle real time production planning and control of manufacturing.
What kind of planning and control problems a manufacturing line may face? What is the reason behind the problem? What consequences do the control aspects of manufacturing will face?
What technique is currently use in the most of industries for the planning propose? What are the short comings of the current techniques?
Where are the potential points of improvements in current techniques?
Which intelligent technique will fit better to face the shortcoming of the current used techniques? Are techniques characteristics meet the needs for overcoming with existing problem?
How will these intelligent technique effect on the manufacturing line control? How will the adaptive real time model effect on the plan and control
(in terms of performance measures)?
1. Practical model to fit the real case problem situations.
2. Responsive tool to overcome the changing environment while taking advantage of meta heuristic techniques.
3. Improve production plan/schedule in terms of measures like; Makespan, Throughput, etc.