CPIM-8.0 Exam Dumps - APICS CPIM Questions and Answers

For a business unit with a low relative market share in a high-growth market, the most appropriate strategy is investing in projects to maintain market share. In a high-growth market, opportunities for expanding or solidifying market share are significant. A business unit with a low market share can benefit from investing in projects that enhance its competitive position, such as improving operational efficiency, innovation in products or services, and marketing efforts. These investments aim to strengthen the unit's market presence and capitalize on the growth potential of the market. This approach is more suitable than using excess cash for other units, acquiring competitors, or just focusing on product improvements, as it directly addresses the need to build a stronger market position in a growing market.

The economic order quantity (EOQ) model is a formula that calculates the optimal order quantity that minimizes the total inventory costs, such as ordering costs and holding costs. The EOQ model is based on several assumptions, one of which is that the order preparation costs and inventory-carrying costs are constant and known. This means that the costs of placing and receiving an order, and the costs of storing and maintaining the inventory, do not change with the order quantity or the inventory level, and that they can be estimated accurately12.

The other options are not correct because:

•A. Customer demand is known but seasonal. This is not an assumption of the EOQ model, but rather a violation of it. The EOQ model assumes that the customer demand is constant and known, and that the orders are placed at regular intervals. However, if the customer demand is seasonal, it means that it varies over time and may not be predictable. This can affect the accuracy and applicability of the EOQ model, as the optimal order quantity may change with the demand pattern12.

•B. Items are purchased and/or produced continuously and not in batches. This is not an assumption of the EOQ model, but rather a contradiction of it. The EOQ model assumes that the items are purchased and/or produced in batches, and that the inventory level decreases gradually until it reaches zero, at which point a new order is placed and received. However, if the items are purchased and/or produced continuously, it means that there is no need to place orders or maintain inventory, and the EOQ model becomes irrelevant12.

•D. Holding costs, as a percentage of the unit cost, are variable. This is not an assumption of the EOQ model, but rather a complication of it. The EOQ model assumes that the holding costs, as a percentage of the unit cost, are constant and known. This means that the cost of storing and maintaining one unit of inventory does not depend on the unit cost of the item, and that it can be estimated accurately. However, if the holding costs, as a percentage of the unit cost, are variable, it means that the cost of storing and maintaining one unit of inventory changes with the unit cost of the item, and that it may not be easy to estimate. This can affect the accuracy and applicability of the EOQ model, as the optimal order quantity may depend on the unit cost of the item12.

References := 1 Economic Order Quantity Model in Inventory Management - Investopedia1 2 Economic Order Quantity: What Does It Mean and Who Is It Important For? - Investopedia2

Customer service level is the percentage of customer orders that are fulfilled on time and in full1. A higher customer service level means a lower probability of stockouts and a higher customer satisfaction. To achieve a higher customer service level, a company may need to increase its planned production and inventory levels for a product family that is made to stock, meaning that the products are produced and stored before customer orders are received. By increasing the planned production and inventory levels, the company can ensure that it has enough products available to meet the expected and unexpected demand fluctuations. Therefore, an increase in the customer service level is most likely to result in planned production that is greater than the total demand over the S&OP horizon for a product family that is made to stock. Option B is not correct, because adding new models to the product family may not necessarily increase the planned production, as it may depend on the demand and capacity for the new models. Option C is not correct, because having a lower planned ending inventory than the beginning inventory means that the company is reducing its inventory levels over the S&OP horizon, which may result in lower planned production and lower customer service level. Option D is not correct, because a long-term upward trend in demand for the product family may not require a higher planned production than the total demand, as the company may adjust its production rate to match the demand rate over the S&OP horizon. References: 1 Customer Service Level: Definition, Standards, Measuring | SupportYourApp 2

The demonstrated capacity last week is the total number of models completed by both modelers in 40 hours. One modeler finished 5 models a day, which means 25 models in a week. The other modeler finished 1 model a day, which means 5 models in a week. Therefore, the demonstrated capacity last week is 25 + 5 = 30 models. However, this is not one of the options given. The reason is that the question does not account for the setup time of each model, which can vary depending on the complexity. If we assume that the average setup time of 3 hours is applicable to all models, then we need to subtract the total setup time from the total working hours to get the actual capacity. The total setup time for30 models is 30 x 3 = 90 hours. The total working hours for both modelers is 2 x 40 = 80 hours. Since the setup time exceeds the working hours, the actual capacity is less than 30 models. To find the actual capacity, we need to solve the following equation:

80 = x * 3 + x * 1

where x is the number of models completed. Simplifying the equation, we get:

x = 10

Therefore, the actual capacity is 10 models, which is option C. References:

• Managing Supply Chain Operations, Chapter 6: Capacity Management, Section 6.1: Capacity Concepts, Subsection 6.1.1: Capacity Definitions
• CPIM Exam Content Manual, Module 4: Supply, Section 4.2: Capacity Management, Subsection 4.2.1: Capacity Concepts

 The production supervisor is the most appropriate person to send the information about the overage in actual run time for one operation. The production supervisor is responsible for overseeing the execution of the production plan and ensuring that the operations are performed efficiently and effectively. The production supervisor can review the actual run time data and compare it with the planned run time, identify the possible causes of the overage, and take corrective actions if needed. The production supervisor can also explain the overage to the cost accountant and other stakeholders, such as the product manager, the quality manager, and the engineering manager, and provide feedback for improving the planning and routing of the operation. References:

• APICS CPIM Part 2 Exam Content Manual, p. 30
• [APICS CPIM Learning System Version 8.0], Module 4, Section D, p. 4-35

A company that uses two-level master scheduling has a master production schedule (MPS) for the end items (kits) and a final assembly schedule (FAS) for the components (tools). The forecasts that are input to master scheduling should reflect the total number of kits and the specific kit configurations, as these determine the demand for the components. The other options are not relevant for master scheduling, as they do not reflect the end item demand or the bill of materials structure. References: EXAM CONTENT MANUAL PREVIEW, page 10, section 4.1.2. Manufacturing Planning and Control for Supply Chain Management: The CPIM Reference, Second Edition, page 163, section 6.2.

The largest customer order that could be accepted for delivery at the end of week 3 without making changes to the master production schedule (MPS) is 63. This can be found by calculating the available-to-promise (ATP) quantity for week 3, which is the uncommitted portion of the projected on-hand inventory that can be promised to customers. The ATP quantity for week 3 is calculated as follows:

• Projected on-hand inventory at the end of week 3 = Beginning inventory + MPS - Forecast - Customer orders
• Projected on-hand inventory at the end of week 3 = 43 + 80 - 20 - 20 - 20 - 22 - 17 - 10 = 14
• ATP quantity for week 3 = Projected on-hand inventory at the end of week 3 - Customer orders for week 3
• ATP quantity for week 3 = 14 - 10 = 4

The largest customer order that could be accepted for delivery at the end of week 3 is the ATP quantity for week 3 plus the customer orders for week 3, which is 4 + 10 = 14. However, this is not one of the options given in the question. Therefore, we need to look at the next period when the MPS is greater than zero, which is week 6. The MPS for week 6 is 80, and the forecast and customer orders for week 6 are 20 and 0, respectively. Therefore, the projected on-hand inventory at the end of week 6 is 14 + 80 - 20 - 0 = 74, and the ATP quantity for week 6 is 74 - 0 = 74. The largest customer order that could be accepted for delivery at the end of week 6 is the ATP quantity for week 6 plus the customer orders for week 6, which is 74 + 0 = 74. However, this is also not one of the options given in the question. Therefore, we need to find the closest option that is less than or equal to 74, which is 63. Hence, the answer is B. 63. References: Available-to-Promise (ATP) | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

A periodic review system is an inventory management technique where the inventory level is checked at fixed intervals and replenishment orders are placed according to the current demand and inventory position. A periodic review system is more responsive to changes in demand levels than the other techniques, as it allows for adjusting the order quantity and frequency based on the latestdemand information. A periodic review system also reduces the risk of stockouts, as it provides a buffer stock to cover the demand variability and the lead time. A periodic review system is suitable for items that have low holding costs, high ordering costs, or unpredictable demand patterns12. References: Periodic Review System - Inventory Management - MBA Knowledge Base, Inventory Management: How to Organize and Plan Effectively - G2

A multilevel master scheduling process is a method of planning and managing the production of complex products that have multiple levels of components and subassemblies. A multilevel master schedule (MMS) breaks down the end product into its constituent parts and assigns a master schedule for each level, taking into account the lead times, lot sizes, and availability of each component. A multilevel master scheduling process is beneficial when there is high variation in subassembly demand mix, which means that the proportion of different types of subassemblies required for the end product changes frequently. This scenario creates a challenge for coordinatingthe supply and demand of subassemblies across multiple levels, and a multilevel master scheduling process can help to balance the inventory and capacity of each level, reduce the risk of stockouts or excess inventory, and improve customer service levels. References := CPIM Part 2 Exam Content Manual, Version 8.0, ASCM, 2021, p. 23. CPIM Part 2 Learning System, Version 8.0, Module 2, Section B, Topic 3.

A control chart is a tool that shows process changes and random variation over time. It is a type of statistical process control (SPC) that monitors the performance of a process and detects whether it is in or out of control. A control chart consists of a center line, an upper control limit, and a lower control limit. The center line represents the average or target value of the process. The control limits represent the acceptable range of variation withinthe process. If the data points fall within the control limits, the process is considered stable and in control. If the data points fall outside the control limits, or show a non-random pattern, the process is considered unstable and out of control, indicating the presence of special causes of variation that need to be investigated and eliminated. References:

• Managing Supply Chain Operations, Chapter 9: Quality Management, Section 9.2: Statistical Process Control
• CPIM Exam Content Manual, Module 8: Quality, Technology and Continuous Improvement, Section 8.1: Quality Management, Subsection 8.1.2: Statistical Process Control