NAMES and NUMBERS of students in the group (2 Students):
1. El-Iraki, Youssef (10448517)
2. Badr, Noureldin (10445226)
MODULE CODE : MBM5204
MODULE NAME : Logistics, Supply Chains, Systems and Methods
Lecturer : Professor Dongping Song
DEADLINE : 11th February 2013
WORD COUNT : 1,657
By submitting this piece of assessment the group confirms that all the work is thoroughly and adequately acknowledge and referenced, and has been completed in accordance with the Pooling help to reduce the variability of data collection, however pooling of customers adds variability to the system and no efficiency will be gained (Vanberkel et al., 2010). Furthermore, it helps to reduce the average queue time in system for the products; it is optimal to schedule the shortest job first and to give priority to short jobs (Downey, n.d.). Thus, it can reduce inventory holding period and costs. This method used in the model is called FIFO (first-in first-out).
3.2 Comparison between initial model and pooled model
1- There are dramatic changes after pooling warehouses, the queuing time dropped from 34 hours to 15 hours while queue size decreased from16 units to 15 units. As a result the average time in system declined from 110 hours to 88 hours, thus it can lead to better customer service, saving storage costs and save time as well.
2- After pooling the drivers, it has influenced the waiting times of the vehicles to increase slightly from 2% to 2.4%. While driver’s utilisation has improved significantly to rise from 91% to 93%, therefore drivers after pooling can respond quickly and flexibly to customers.
Usefulness of Simulation Model in Business Context
4.1 Simulation and decision making
The simulation model can help the real-world companies to provide efficient
