Operations Management / Discrete Event Modeling A neighborhood supermarket in No

Question

Operations Management / Discrete Event Modeling A neighborhood supermarket in Norfolk is open daily from 10 am to 10 pm. On average, 20 customers arrive per hour. An arriving customer first needs to take a shopping cart. If no shopping cart is available, the customer has to wait until a shopping cart becomes available. There are currently 25 shopping carts in the supermarket. The supermarket has 3 areas: (1) the dairy area, (2) the meat area, and (3) the fruit and vegetables area These areas are visited in that order by all customers. 60 % of customers go to the dairy area, 70 % of customers go to the meat area, and 100% of customers go the fruit and vegetables area. In each area, a customer will typically buy between 2 to 15 items and it takes about 45 seconds to pick each item After picking all the items in their shopping cart, the customers go to the cashier area. There are 6 cashiers open at all times. All customers wait in a single queue and are directed to the next available cashier. It generally takes 105 seconds to checkout, yet it may be as fast a 30 second or as long as 3 minutes. The business owner is seeking advice to decide on whether to adjust the number of her shopping carts as well as the number of cashiers. In order to help make this decision, please answer the following questions: List the entities, resources, and processes. (1pt) Build a model in the Arena software and simulate the model for 30 replications. (5pts) What's on average the total time spent by a customer in the supermarket? (1pt) What's the maximum time spent waiting for a shopping cart? (1pt) What's the average time waiting at the cashier? (1pt) What's the average number of people waiting for a cashier? (1pt) Bonus Question (3 extra points): What is the minimum number of shopping carts and cashiers such that total waiting in the supermarket is always less than 1 minute. 1. 2. 3. 4. 5. 6. 7. 8.

Explanation / Answer

Abstract:

The supply chain of Freescale Semiconductor from fabrication through final test and delivery was modeled and analyzed using discrete event simulation in Arena. Freescale starts products in manufacturing based on a make-to-order and make-to-stock master production schedule. Since customer lead time is often less than the supply chain cycle time, Freescale maintains strategic safety stock throughout the supply chain and as finished goods inventory. Manufacturing entry rate is determined by the amount of product in WIP and inventory. Our analysis concentrates on the relationship between on-time delivery in the major supply chain segments and on-time delivery to the customer in an environment of significant inventory and WIP level changes. The goal is to predict the effect of internal on-time delivery, inventory and WIP changes on the customer order fulfillment service level. In our analysis, we evaluate supply chain production and inventory control policies and the impact of lead time reductions

Freescale Semiconductor, Inc. is a global semiconductor company focused on providing embedded processing and connectivity products to large, high-growth markets. The company provides products to the automotive, networking and wireless communications industries. Freescale offers families of embedded processors, which provide the basic intelligence for electronic devices and can be programmed to address specific applications or functions, as well as a broad portfolio of complementary devices that provide connectivity between products, across networks and to real-world signals, such as sound, vibration and pressure. Through its embedded processors and complementary products, Freescale is able to offer customers platform-level products. On October 6, 2003, Freescale was created when Motorola announced its intention to separate its semiconductor operations into a separate company. In late 2004, it was spun off and Motorola ceased to be a controlling stockholder.

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