I was asked to provide a distribution pattern that minimizes shipping costs and provides adequate availability and demand. I used transportation modeling to solve this problem. Transportation modeling is “an interactive procedure that finds the least costly means of moving products from a series of sources to a series of destinations” (Heizer & Render, 2011).
This tool is used to determine the best distribution pattern for multiple locations. It is best for this problem because it allows for us to determine how many products can be held at each location to give Shuzworld the lowest shipping costs. The original setup had an optimal shipping cost of $13,600. It had 1300 pairs housed at the Shanghai warehouse. Shuzworld H had 300 pairs in Warehouse 1, 200 pairs in Warehouse 2, and 1800 pairs at Warehouse 3.
Shuzworld F had 2200 pairs housed at 1 warehouse. The recommended plan lowered the optimal cost to $13,400. The Shanghai plant will house 1500 shoes in Warehouse 2, with an additional 1300 shoes held in case of increased demand. Shuzworld H will hold 300 shoes in Warehouse 1, 1800 shoes in Warehouse 3, and an additional 200 shoes will be held for increased demand. Shuzworld F will have 2200 shoes held in Warehouse 1. This will allow all of the warehouses to hold enough products to meet current demand, with additional products in short shipping distance. This cuts down on shipping costs as well as time waiting on the production of more shoes. As the market demand increases, additional shoes can be delivered from the holding warehouse.
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Price elasticity of demand (PED) is the responsiveness of quantity demanded in relation to the price. Normally as price increases for an elastic good the quantity demanded will fall. This is affected by how many close substitutes there are for the good and if the good is a luxury good (jewelry) or a necessary good (food). If the price of a certain type of cheese increases, less will be demanded ...
The next task is to find the most reliable machine set up for the computer-driven shoe machine process. “Reliability is the probability that a machine will function properly for a specified time” (Heizer & Render, 2011).
In order to provide reliability, it is critical to provide backup systems for all computers. When operating computers fail, production can be slowed, or stopped altogether. The initial system had an overall reliability of 76%. There was no backups for any of the machines. Machine 1 had a reliability of 84%, Machine 2’s reliability was 91%, and Machine 3 had a reliability of 99%. The first possible setup, and ultimately the recommended setup, was to backup Machine 1. This led to an overall reliability of 84%. Backing up Machine 2 only gave a reliability of 82%. Backing up Machine 3 only gave a reliability of 76%. Therefore the recommendation is to backup Machine 1 and increase the reliability to 88%.
The next task is to provide the optimum number of shoelaces to order, using appropriate cost balancing. The economic order quantity (EOQ) is the order amount that allows for an optimum level of materials at the lowest cost possible. There is a demand ofr 300,000 shoelaces per year. The setup cost is $125 per order. There is a $.10 holding cost per unit. The optimal order quantity recommended is 27,386.13 shoelaces per order, with a maximum inventory of 27,386.13. This means that we will order just the amount of shoelaces needed to fulfill current production orders. The average inventory is 13,693.06 shoelaces. There will be approximately 10.95 orders per year. The annual setup cost is $1,369.31, and the annual holding cost is $1,369.31. This makes the total cost per year $2, 738.61. This decision tool allows us to calculate the correct amount needed per order to ensure that we are lowering operating and holding costs, while keeping production properly stocked.
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Our Time Machine. G. Wells once wrote a novel called The Time Machine, it was published in 1895. This exciting little adventure featured a device that had power over time. Who knew that in 2001 we too would have such a device? One invention that has made it evident that we have reached the twenty first century is named Tivo. With this, one has the ability to pause, fast forward, and essentially ...
The last task was to determine if Shuzworld would benefit from a one-cashier or two-cashier waiting line system. There is typically an average of 6 customers being serviced at any given time. There is typically a customer being services every 5 minutes, so the service rate is 12 customers per hour. One server is typically busy 0.5 of the time. There is usually 0.5 customers in the queue at any given time. There is 1 customer in the system at one time. This means that a customer spends 0.08 hours (5 minutes) in the store waiting to be serviced. A customer spends 0.17 hours (10 minutes) in the store making their complete purchase. This is too much time for a customer to wait and be serviced. This long wait time may dissuade sales, as customers do not want to wait to be helped or pay for their purchases.
Using a two-cashier system is a more efficient option of Shuzworld. The average server utilization is 0.25, meaning that 75% of the time, there is a server available to help customers. There is 0.03 customers in the queue at any given time, with 0.53 customers being served at one time. This means that the customer spends 0.01 hours (.33 minutes) waiting to be served, and 0.09 hours (5.33 minutes) in the store completing their purchase. This system allows the customers to get into the store, pick out their items, and pay in less than 6 minutes. This will definitely encourage future business with the company. Customers want to have the least amount of time spent in a store, and waiting for service may cause some to leave without making a purchase. This analysis tool allowed us to determine which system would provide the best times for the customers of Shuzworld.
References
Heizer, J., & Render, B. (2011).
Operations Management (10 ed.).
Prentice Hall.
