EBBD EMAIL – for Internal Use Only
From: Danny Wilco <[email protected]>
Subject: Re: Deliveries clogging the loading dock area
OK, here’s what I want to know: how often do we have more than 5 trucks, more than 6 trucks, and more than 7 trucks. What is the highest number of trucks we may have in the system with a 95% probability? And then, assuming the arrival rate of the deliveries does not change, what does the unload rate need to be so that we can service up to five trucks 95% of the time? In other words if we want a 95% probability of 5 or fewer trucks in the system at any one time, what does the unloading (service) rate need to be? Then, consider that we have two unloading teams, each able to unload trucks at the same rate. What does the unloading rate need to be for each team in order to ensure (100%) 5 or fewer trucks in the system at any time? I know we don’t have room for two unloading teams at this time, but there is a possibility we might make room in the future.
Analyze this situation and determine what we need to know and give me report. At this point in time, I am looking only for the problem to be quantified and the unload rate determined for the current situation (single server) and possible two servers.
Let me know if you have any questions.
~DW, VP LogOps.
If you have mastered the examples and exercises provided in the Background from the Queuing PowerPoint, you are ready to tackle the EBBD problem.
The current situation is a Single Server situation. Enter the arrival rate and service rate to calculate the pertinent queuing system state data. Find out the probabilities of 5 or more trucks in the system, then 6, then 7. Then use trial and error to find the greatest number of trucks or less that can be in the system with 95% (or as close to 95%).
For the Multi-server problem you will need to use a similar process.
Record the results of your calculations and save the Excel file.
Then write your report.
Upload the Report to Case 4. Upload the Excel file with the solution to Additional Files in Module 4.
The report should thoroughly address these aspects in depth and breadth:
Queuing Theory. (n.d.). Reference for Business. Retrieved from: http://www.referenceforbusiness.com/encyclopedia/Pro-Res/Queuing-Theory.html
Lynch, C. (2010). Top ten logistics challenges for 2011 (and beyond). DC Velocity. Retrieved from http://www.dcvelocity.com/articles/2010121310_logistics_challenges_in_2011/