role of Artificial Intelligence in Supply Chain Management

Research Title:
A Study of the role of Artificial Intelligence in Supply Chain Management
The Main Research Idea:
Developing the process of supply chain by using the artificial intelligence applications.
Research question:
Investigate how expert systems as an Artificial intelligence application can play a role in the inventory cycle developing as a core area in the supply chain
management.
Project aims:
This research investigate the potential development of the expert system as an efficient tool of balancing the right inventory level rather having extra inventory
level which impacted negatively on the cash flow, space management and inventory control or not having sufficient inventory level which causes lost sales opportunity,
losing market share and an opportunity for direct competitors by doing a periodic review for the whole inventory cycle which forecast the future inventory required
accurately; taking into account history errors to increase the efficiency of forecasting process and proposes better inventory ordering strategy.
Having a user-friendly strong tool to be used effectively by managers to improve the effectiveness of their inventory management either ordering or replenishment.
Theoretical framework:
Table of Contents:

1. Introduction

2. Literature review
2.1. The Supply Chain management cycle
2.2. Inventory Management as a core area in the supply chain management
2.2.1. Inventory management process mapping
2.2.2. Identify the inventory cycle challenges
2.3. The Artificial Intelligence concept
2.4. The expert systems applications
2.4.1. The expert systems mechanism
2.4.2. The expert systems and inventory management

3. Research methodology
3.1. Research Question
3.2. Research Method
3.2.1.1. Questionnaire design
3.2.1.2. Questionnaire sampling
3.2.1.3. Procedures
3.3. Data Collection

4. Data analysis
4.1. Hypothesis examine
4.2. Discussion

5. Conclusion
Research methodology:
The research methodology behind the work presented in this research is based on two methods:
1- A theory-building, started with an extensive literature review for the supply chain cycle specifically the inventory cycle process map to investigate
researchable hypotheses, and how other researchers investigated and examined the expert systems as an application to be used with inventory management ,

2- Design a related questionnaire to collect data from Supply chain expertize to validate and support the academic inventory process mapping, identify inventory
management challenges and investigate how they perceive expert systems as a solution or a development tool for the inventory cycle process.
The literature was mainly collected from journals on supply chain management, operations research, information systems. In order to obtain a general overview on the
literature, book chapters, dissertations, working papers, technical reports and conference papers are also included.

Time Table:
Date 2/14/2016 2/21/2016 2/28/2016 3/6/2016 3/13/2016 3/20/2016 3/27/2016 4/3/2016 4/10/2016 4/17/2016
4/24/2016 5/1/2016 5/8/2016
W/Process W1 W2 W3 W4 W5 W6 W7 W8 W9 W10 W11 W12 W13
Introduction
Literature review
Questionnaire design
Sampling/Distributing
Data collection
Data analysis
Finding and conclusion

References List:
Abo-Hamad, W. and Arisha, A., 2011, Simulation-Optimisation Methods in Supply Chain Applications, Irish Journal of Management, 30 (2).
Bandaru, S., Aslam, T., HC Ng, A. and Deb, K., 2015. Generalized Higher-Level Automated Innovization with Application to Inventory Management. European Journal of
Operational Research, 243 (2).
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Bryman, A. and Bell, E., 2015. Business Research Methods, 4th edition. England: Oxford University Press.
Dymova, L., Sevastianov, P. and Bartosiewicz, P., 2010. A New Approach to the Rule-Base Evidential Reasoning: Stock Trading. Expert System Application by Expert
Systems with Applications, 37 (8).
Ellis, R., Allen, T. and Petridis, M. (Eds.), 2007. Applications and Innovations in Intelligent Systems XV Proceedings of AI-2007, the Twenty-seventh SGAI
International Conference on Innovative Techniques and Applications of Artificial Intelligence.
Emilio, C., 2009. Hybrid Artificial Intelligence Systems, 4th international conference, HAIS, Salamanca, Spain: Springer.
Michalski, G., 2010, Inventory Management Optimization as Part of Operational Risk Management, An Intelligent Supply Chain Planning and Execution Environment.

Min, H. and Green, B. (Eds.), 2008. Artificial Intelligence in Supply Chain Management: Theory and Applications. USA.

Pardalos, P., Chaovalitwongse, W. and Furman, K., 2009. Optimization and Logistics Challenges in the Enterprise. England: Springer Optimization and Its Applications.
Russell, S., Norvig, P. and Canny, J., 2003. Artificial Intelligence: A Modern Approach, 2nd Edition. London: Upper Saddle River, N.J.; Prentice Hall.
Schwartz, J., Wang, W. and Rivera, D., 2006. Simulation-Based Optimization of Process Control Policies for Inventory Management in Supply Chains. Automatica, 42 (8).
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Subramoniam, S. and Krishnankutty, K.V., 2005. Expert Database System for Inventory Management. ProQuest Computer Science Journals, 34 (5), pp. 721 – 733.

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