Dr. Mohammed Alnahhal


 

Title:  Assistant Professor – Industrial Engineering
School: School of Engineering
Department: Mechanical and Industrial Engineering Department
Office:  Bldg. G-308
Phone: +971 7 246 8748
Email: mohammed.alnahhal@aurak.ac.ae

Dr. Mohammed Alnahhal holds Bachelor and Master Degrees in Industrial Engineering. He was employed at the Islamic University of Gaza for three years. In 2015, he received his PhD degree from the University Duisburg-Essen in Germany for his thesis on efficient material flow in mixed model assembly lines. For one year subsequent to his PhD graduation he was a logistics consultant in a German company called Müller ‒ Die lila Logistik AG. Then he worked as a research fellow at Deggendorf Institute of Technology for about two years and a half. Currently he is working in the American University of Ras Al Khaimah as an Assistant Professor in the school of industrial Engineering.

His research includes supply chain management especially in-house logistics, Simulation, Operations Research, Genetic Algorithm, Neural Networks, data analysis, and Project Management.

  • PhD in Industrial Engineering (Transportation and Logistics Systems) – Duisburg-Essen University, 2015
  • PhD Candidate – Duisburg-Essen University, 2015
  • M.Sc. Industrial Engineering  and Management- University of Jordan, 2010
  • Bachelor Degree in Industrial Engineering- Islamic University of Gaza, 2005

 

Research Interests

  • Supply chain management
  • Simulation
  • Operations research
  • Data analysis

Publications

  • Alnahhal, M.; Ahrens, D.; Salah, B. (2021), Optimizing Inventory Replenishment for Seasonal Demand with Discrete Delivery Times. Applied Sciences, 11(23), 11210. https://doi.org/10.3390/app112311210.
  • Soumar, B. Alnahhal, M. Al Hazza, M., Sakhrieh, A., Tabash, M. I. (2021). Factors motivating governmental employees in the United Arab Emirates. Problems and Perspectives in Management, 19(4), 248- 257. doi:10.21511/ppm.19(4).2021.20
  • Alnahhal, M., Ahrens, D., and Salah, B. (2021). Dynamic Lead-Time Forecasting Using Machine Learning in a Make-to-Order Supply Chain. Applied Sciences 11( 21), 10105. https://doi.org/10.3390/app11211010
  • AlShehhi, N., AlZaabi, F., Alnahhal, M., Sakhrieh, A., Tabash. M., (2021). The effect of organizational culture on the performance of UAE organizations. Cogent Business & Management, 8(1), 1980934, DOI: 10.1080/23311975.2021.198093
  • Almemari, K. Almazrouei, R. Alnahhal, M. (2021). The impact of green human resource management on the sustainable performance of the manufacturing companies in the UAE. Journal of southwest Jiaotong University. 56(4), 436-447
  • Farooq, U., Mosab, M. I., Anagreh, S., Alnahhal, M. (2021). Assessing the Impact of COVID-19 on Corporate Investment Behavior. Emerging Science Journal, 5, 130- 140
  • Alnahhal, M., Al Zaabi, F., Al Shehhi, N., Al Shehhi, M., Sakhrieh, A. and Al Hazza, M. (2021). Green supply chain management in the UAE construction industry, Indian Journal of Economics and Business, 20(2), 43-56
  • Alnahhal, M.; Ahrens, D.; Salah, B. (2021). Modeling Freight Consolidation in a Make‐To‐Order Supply Chain: A Simulation Approach. Processes, 9, 1554. https://doi.org/10.3390/pr9091554
  • Al Safarini, N., Hasan, A., Sakhrieh, A., Alnahhal, M., Al Hazza, M. (2021). Crucial role of efficient communication on construction projects progress, deliverables and conflicts reduction in the United Arab Emirates. Polish Journal of Management Studies23 (1), 9-22.
  • AlZaabi, Fatima, Maryam AlShehhi, Noora AlShehhi, Ranya Wadi, Ruqayya Alhebsi, Muataz Hazza Al Hazza, Mohammed Alnahhal, and Ahmad Sakhrieh. “An Investigation Study of Challenges in the Transition from Traditional to Virtual Teamwork During COVID-19 in UAE Organisations.”15(5), 455-468
  • Alnahhal, M., Tabash, M. I., & Ahrens, D. (2021). Optimal selection of third-party logistics providers using integer programming: a case study of a furniture company storage and distribution. Annals of Operations Research, 1-22.
  • Al Shehhi, A., Al Hazza, M., Alnahhal, M., Sakhrieh, A., & Al Zarooni, M. (2021). Challenges and Barriers for Renewable Energy Implementation in the United Arab Emirates: Empirical Study. International Journal of Energy Economics and Policy11(1), 158-164.
  • Alnahhal, M., & Ahrens, D. (2018). A simulation-based system for calculating optimal numbers of forklift drivers in industrial plants. Bavarian Journal of Applied Sciences, 4, 354- 369.
  • Alnahhal, M., & Noche, B. (2015). Dynamic material flow control in mixed model assembly lines. Computers & Industrial Engineering, 85, 110-119.
  • Alnahhal, M., & Noche, B. (2015). A genetic algorithm for supermarket location problem. Assembly Automation, 35(1), 122 – 127.
  • Alnahhal, M., Ridwan, A., & Noche, B. (2014). “In-plant milk run decision problems”. IEEE International Conference on Logistics and Operations Management (GOL) (pp. 85-92).
  • Alnahhal, M., & Noche, B. (2014). “Capacity planning in in–plant milk run system”. International Journal of Service and Computing Oriented Manufacturing, 1(3), 197-210.
  • Alnahhal M., Ramadan M., Noche B. (2014) “Static Versus Dynamic Control of Material Flow in In-Plant Milk Run System” 4th International Conference on Dynamics in Logistics, Bremen/Germany
  • Ramadan M., Alnahhal M., Noche B. (2014) “RFID- enabled Real-time Dynamic Operations and Material Flow Control in Lean Manufacturing” 4th International Conference on Dynamics in Logistics, Bremen/Germany
  • Agha, M. S., Alnahhal, M. J., Agha, S. R., & Alafeefy, A. S. (2014). Industrial Sectors Eligibility for Rehabilitation Programs: An Integrated AHP–TODIM Approach. International Journal of Strategic Decision Sciences (IJSDS), 5(1), 95-110.
  • Alnahhal, M., & Noche, B. (2013). Efficient material flow in mixed model assembly lines. SpringerPlus journal, 2(1), 415.
  • Agha, S. R., & Alnahhal, M. J. (2012). Neural network and multiple linear regression to predict school children dimensions for ergonomic school furniture design. Applied ergonomics, 43(6), 979-984.
  • Abbasi, Gh. S., Alnahhal, M., A. (2012) Neural Network Model for Predicting Budget Performance of Construction Projects in Jordan, International Journal of Construction Project Management, 4 (1), 75-86
  • Abbasi, Gh. S., Alnahhal, M. J. (2011) Contractors View of Project Management Best Practices in the Jordanian Construction Sector, International Journal of Construction Project Management, 3 (2), 159- 175
Last updated: Nov 28, 2021 @ 12:29 pm

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