Decision Analysis

Shuzworld currently has three production plants and three central warehouses for one of their major lines of women's shoes. The three production plants (Shanghai, Shuzworld H, and Shuzworld F) are producing at normal capacity to meet current demand.

Shuzworld is currently producing 1,300 units at their Shanghai factory. They would like to increase production at Shanghai to 2,800 units.

As per the excel spreadsheet, this solution shows the most cost effective distribution for one month. The optimal monthly cost is $13,400. In order to achieve this cost, the Shanghai factory should send 1,500 units to Warehouse 2. The Shuzworld H factory should send 300 units to Warehouse 1 and 1,800 units to Warehouse 3. The Shuzworld F factory should send all 2,200 units to Warehouse 1. Several units will also need to be sent to a "dummy" destination. The Shanghai factory will send 1,300 units and Shuzworld H will send 200 units to a "dummy" factory. This occurs because the increase to 2,800 units creates more supply than there is demand. A "dummy" destination is created to equal out the supply and demand, but these units are never shipped. Since they are never shipped, they have no cost associated to them.

We want to increase our production in the Shanghai factory to 2,800 units. This is in anticipation of increasing demand. We do not currently have that increased demand, so the "dummy" destination will not hurt them us at this time. This projection will give us time to determine our next course of action, so we can meet demand in the future. We may have to allocate another warehouse for these 1,500 monthly units of women's shoes in the future.

I chose the transportation model because it is a form of linear programming that helps us to find the lowest cost solutions to shipping problems throughout the companywide shipping system. This tool will help us to analyze the costs to transport products from various shipping points to the various destinations and provide a model that will minimize overall transportation costs (Heizer, & Render, 2010).

Each machine performs at a different function in the process of making shoes. It takes all three machines to work properly to produce the casual deck shoes. The reliability of each machine is exclusive to that individual machine and has no bearing on the reliability of the other machines.

The past reliability figures are:

MACHINE RELIABITY

NUMBER 1 .84

NUMBER 2 .91

NUMBER 3 .99

Bases on the equation Rs=R1*R2*R3 the total reliability of the process is 75.7%.

Based on the information provided, we have a couple of options to increase the overall reliability of the deck shoe production. First we can replace machine number 1 with a higher reliability rate.

Secondly, we can utilize redundancy to increase reliability of the process. Redundancy is the process where the least reliable machine is backed up with additional identical components. It is my recommendation to back up machine number 1. By having a backup component for machine no production time would be lost if the machine broke down. Using redundancy for machine number 1 would raise the reliability rate of machine one form .81 to .97. Machine number two would still have reliability rate of .91 and machine three would still have a reliability rate of .99. Backing up machine 2 and 3 will have no significant increase in reliability. There will be no effect on the total reliability either. This is why I only chose to back up machine 1. The total reliability of the process would also increase from 75.7% to 87.8%.

To ensure the machines remain working properly and efficiently, it is vital to have a system of preventive maintenance in place. This will involve routine machine inspections, servicing and repair. If done correctly, preventive measures can prevent machine failure. Part of preventive maintenance is proper training and installation this will increase the life of the machine.

The company management wanted to know the reliability of their current system and what it could do to increase reliability through the addition of another machine therefore we selected the reliability general network tool because this tool will calculate the product failure rate, which is the basic unit of measure for reliability. This tool calculated the current reliability of the process and the increase in reliability of the process after we inputted the redundant #1 machine into the equation.

Also, in order to determine the system reliability