A cloud-based intelligent decision-making system for order tracking and allocation in apparel manufacturing

Abstract

This paper addressed the order tracking and allocation problem in an apparel manufacturing environment with multiple plants. A cloud-based intelligent decision-making system was developed to tackle this problem, which combined radio frequency identification and cloud computing technologies to capture real-time production records and make remote production order tracking, and employed computational intelligence techniques to generate effective order allocation solutions to appropriate plants. To evaluate the effectiveness of the proposed system, the system was implemented in an apparel manufacturing company with multiple plants, which reported distinct reductions in production costs and increases in production efficiency. This paper also investigated learning phenomenon in production and its effects on production efficiency and decision-making performance.

Keywords:

• order tracking
• order allocation
• intelligent optimisation
• cloud computing

Acknowledgements

The authors acknowledge the financial support from the Sichuan University (Grant No. SKYB201301) and the National Natural Science Foundation of China (Grant Nos. 71302134, 71371130 and 71071102).