CPIM-8.0 Exam Dumps - Certified in Planning and Inventory Management (CPIM 8.0)

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

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

An assignable cause of variation is a source of variation that is intermittent, not predictable, and identifiable. It is also called a special cause of variation. An assignable cause of variation affects the process performance in an unexpected and non-random way, and it can be eliminated or controlled by finding and correcting the specific cause1. An example of an assignable cause of variation in process performance is incorrect setup of a machine by the operator. This means that the operator did not follow the standard procedure or specification for setting up the machine, which may result in defective or nonconforming products or materials. This cause of variation can be identified and corrected by checking the setup instructions, training the operator, or implementing a setup verification system23. References: 1 Assignable Cause - isixsigma.com 4 2 Process Capability Analysis - an overview | ScienceDirect Topics 5 3 CPIM Exam References - Association for Supply Chain Management 1

A production cell is a group of machines or workstations that are arranged in a way that allows for continuous flow of materials and products. The main objective of designing a production cell is to reduce waste, improve quality, and increase productivity. One of the most important considerations for designing a production cell is the flow of materials into the cell and sequencing of operations to minimize total cycle time. Total cycle time is the time it takes for a product to go through all the steps in the cell, from the first operation to the last. By minimizing total cycle time, the production cell can achieve higher throughput, lower inventory, and faster delivery123 References: 1: CPIM Part 2 - Section C - Module 1 - Session 1 - Lean Manufacturing 2: CPIM Part 2 - Section C - Module 1 - Session 2 - Lean Manufacturing Tools 3: CPIM Part 2 - Section C - Module 1 - Session 3 - Lean Manufacturing Implementation

 The labor efficiency variance is the difference between the standard labor hours allowed for the actual output and the actual labor hours used, multiplied by the standard labor rate. In this case, the standard labor hours allowed for 100 pieces are 0.5 * 100 = 50 hours. The actual labor hours used are 48 hours. The standard labor rate is $10 per hour. Therefore, the labor efficiency variance = (50 - 48) * $10 = $20 favorable. This means that the actual labor hours used were less than the standard labor hours allowed, which indicates a higher labor efficiency12 References: 1: CPIM Part 2 - Section B - Module 2 - Session 2 - Variance Analysis 2: CPIM Part 2 - Section B - Module 2 - Session 3 - Variance Analysis Example

 Forecast error is the difference between the actual demand and the forecasted demand for a given period. Forecast error can be caused by various factors, such as changes in customer preferences, market conditions, competitor actions, or random variation. Forecast error can be measured using different methods, such as mean absolute deviation (MAD), mean absolute percentage error (MAPE), or tracking signal. Forecast error typically triggers forecast revision when it is continually increasing, which indicates that the forecast model is not capturing the underlying demand pattern or trend. A continually increasing forecast error can lead to poor customer service, excess or obsolete inventory, or lost sales opportunities. Therefore, it is important to monitor the forecast error and revise the forecast when necessary to improve the forecast accuracy and reliability. Forecast error does not trigger forecast revision when it is used in computing the tracking signal, associated with the introduction stage of the product life cycle, or caused by random variation. These are not valid reasons for revising the forecast, as they do not indicate a systematic or persistent deviation from the actual demand. References:

• CPIM Part 1 Study Guide, Chapter 4: Demand Management, Section 4.2: Forecasting Techniques and Performance Measurement
• CPIM Part 2 Study Guide, Chapter 3: Demand Management, Section 3.1: Demand Planning
• A Critical Look at Measuring and Calculating Forecast Bias, Section: What Is Forecast Bias?
• How Can Forecast Error be Calculated?, Section: Introduction

Increasing finished goods inventory investment will improve service levels by reducing the probability of stockouts. However, the relationship between inventory and service level is not linear, but rather asymptotic. This means that as inventory increases, service level increases at a decreasing rate, approaching a maximum value. Therefore, option C is correct. Option A is incorrect because service level will not remain the same when inventory changes. Option B is incorrect because service level will not increase in direct proportion to inventory. Option D is incorrect because service level will not increase at an increasing rate as inventory increases. References: CPIM Part 2 Exam Content Manual, Version 8.0, Section A: Demand Management, Subsection A.3: Demand Management and Customer Service, p. 10.

Global outsourcing and shared suppliers serving an industry are drivers of loss of intellectual property risk, which is the risk of losing proprietary information or technology to competitors or other parties. This risk can arise from inadequate protection of data, contracts, patents, or trade secrets, or from intentional or unintentional disclosure by suppliers or employees. Loss of intellectual property can result in reduced competitive advantage, lower market share, or legal disputes. References := CPIM Part 2 Exam Content Manual, Version 8.0, ASCM, 2021, p. 11. CPIM Part 2 Learning System, Version 8.0, Module 1, Section A, Topic 4.