CPIM-8.0 Practice Exam Questions with Answers Certified in Planning and Inventory Management (CPIM 8.0) Certification

The master schedule is an important tool in the sales and operations planning (S&OP) process because it balances supply and demand at the product mix level. The master schedule is a detailed plan that specifies the quantity and timing of each end item or product family to be produced. It is derived from the aggregate production plan, which is the output of the S&OP process. The master schedule helps to translate the aggregate plan into specific product requirements and to allocate the available capacity to meet the demand. The master schedule also provides input to the material requirements planning (MRP) and capacity requirements planning (CRP) systems, which further refine the production plan at the component and resource levels. The other statements are not true about the master schedule. The master schedule does not represent the forecast before changes are made in S&OP, as the forecast is an input to the S&OP process, not an output. The master schedule does not represent the forecast with less detail, as the master schedule is more detailed than the forecast, which is usually expressed in aggregate terms. The master schedule does not balance supply and demand at the sales volume level, as the sales volume level is the level of the aggregate production plan, not the master schedule. References: Master Schedule | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

Price negotiation is most appropriate when purchasing commodities. Commodities are products or materials that are standardized, widely available, and have low differentiation. Examples of commodities include metals, grains, oil, gas, etc. Price negotiation is a process of bargaining with the supplier to obtain the best possible price for the purchase. Price negotiation is suitable for commodities because they have high price volatility, meaning that their prices fluctuate frequently and unpredictably due to changes in supply and demand, market conditions, and other factors. Price negotiation can help the buyer to take advantage of the price fluctuations and secure a lower price or a better contract term with the supplier. Price negotiation can also help the buyer to reduce the total cost of ownership, which includes not only the purchase price but also the costs of transportation, storage, quality, and risk12. References: 1 How to negotiate price: negotiation tips for salespeople 3 2 CPIM Exam References - Association for Supply Chain Management 1

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

 Backflushing is a method of inventory accounting that deducts the materials used in production from the inventory record after the completion of a product or batch. This introduces a temporary variance between the actual inventory balance and the inventory record, which should be reconciled periodically. Inventory write-off, cycle count, and kanban do not cause such a variance. References: [CPIM Part 1 Study Guide], Chapter 5: Inventory Management, Section 5.3: Inventory Record Accuracy, p. 5-15.

The sales and operations plan (S&OP) is the most appropriate level to adjust when a major new customer is received from sales. The S&OP is a cross-functional process that aligns the demand and supply plans with the business strategy and financial goals. It also provides the basis for the master production schedule (MPS), which is a more detailed and disaggregated plan for specific products or families. Adjusting the production volume or the forecast would not be sufficient to account for the impact of the new customer on the overall business objectives and resources. References:

•APICS CPIM Part 2 Exam Content Manual, p. 11

•[APICS CPIM Learning System Version 8.0], Module 1, Section A, p. 1-15

The discrete available-to-promise (ATP) method is a calculation based on the available-to-promise figure in the master schedule. For the first period, the ATP is the sum of the beginning inventory plus the MPS quantity minus backlog for all periods until the item is master scheduled again. For other periods, the quantity that is available for an item is based on the quantity available within an individual purchase. Therefore, the master production receipt quantity is committed to requests only for shipment before the next MPS receipt12. References:

•1: APICS CPIM Part 2 Exam Content Manual, Version 8.0, p. 29

•2: NetSuite Applications Suite - Available to Promise Methods3

Sharing of demand data with a supplier is an example of collaboration between suppliers and operations which would give more lead time visibility. This is because it allows the supplier to plan and adjust their production and delivery schedules according to the customer’s needs, reducing the risk of stockouts or excess inventory. It also enables the supplier to provide feedback and suggestions to improve the demand planning process and the accuracy of the forecasts. Sharing of demand data is a key component of supplier relationship management (SRM) and collaborative planning, forecasting, and replenishment (CPFR). References :=

CPIM Exam Content Manual, Module 4: Supply, Section 4.2: Supplier Relationship Management, p. 15

Essentials of Supply Chain Management, Chapter 6: Demand Planning and Forecasting, Section 6.4: Collaborative Planning, Forecasting, and Replenishment, pp. 101-103

Demonstrated capacity is the actual output achieved by a resource or a system over a period of time, such as a day, a week, or a month. It is determined from actual results, such as production records, time studies, or historical data. Demonstrated capacity reflects the past performance, not the future load, of a resource or a system. It may be lower or higher than the rated capacity, which is the theoretical or design capacity of a resource or a system. Demonstrated capacity considers utilization and efficiency factors, such as machine availability, operator skills, product mix, quality issues, or maintenance schedules, that affect the actual output. References:

Managing Supply Chain Operations, Chapter 5: Capacity Planning and Management, Section 5.2: Capacity Planning Decisions, page 132-133.

Manufacturing Planning and Control for Supply Chain Management: The CPIM Reference, Second Edition, Chapter 6: Capacity Management, Section 6.2: Capacity Planning, page 156-157.

CPIM 8.0 Exam Content Manual Preview, Module 5: Plan and Manage Supply, Section 5.1: Plan and Manage Capacity, page 9.

Mixed-model scheduling is a technique that allows multiple products to be produced on the same assembly line without changeovers, and then sequences those products in a way that smoothes the demand for upstream components12. In this case, the company is using mixed-model scheduling to produce three different products (A, B, and C) on the same line, and then alternating them in a pattern that minimizes the variation in the workload and the inventory levels. The other options are not correct because:

•Matrix scheduling is a technique that assigns tasks to workers based on their skills and availability3.

•Synchronized scheduling is a technique that coordinates the production and delivery of materials and components to match the demand of the final assembly4.

•Line balancing is a technique that distributes the workload evenly among the workers or machines on a production line5. References := 1 Create Mixed Model Flow in 5 Steps | Industrial Equipment News 2 Mixed Model Scheduling - Mountain Home Academy 3 Matrix Scheduling - an overview | ScienceDirect Topics 4 Synchronized Scheduling - an overview | ScienceDirect Topics 5 Line Balancing - an overview | ScienceDirect Topics

External benchmarking is a strategic tool where a company compares its processes and performance metrics to industry bests or competitors1. Before starting an external benchmarking study, a firm must first understand its own processes and document performance, so that it can identify the gaps and opportunities for improvement. This is also a requirement for regulatory compliance2. Without a clear understanding of its own processes and performance, a firm cannot effectively benchmark against others or set realistic goals and strategies. References:

•What Is External Benchmarking? (with picture) - Smart Capital Mind

•5 Strategies for Effective ASC External Benchmarking - Becker’s ASC

 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

Safety factor is a multiplier that is applied to the standard deviation of demand to determine the safety stock level. Safety factor remains constant while maintaining the same customer service level, as it reflects the desired probability of not stocking out. The higher the safety factor, the higher the customer service level, and vice versa. The other factors do not remain constant while maintaining the same customer service level. Reorder point (ROP) is the inventory level that triggers a replenishment order. ROP increases with increasing forecast error, as more safety stock is needed to cover the demand uncertainty. Safety stock is the inventory that is carried to protect against forecast errors and demand fluctuations. Safety stock increases with increasing forecast error, as more buffer is needed to avoid stockouts. Inventory investment is the total value of the inventory that is held in the system. Inventory investment increases with increasing forecast error, as more inventory is required to maintain the same customer service level. References: Safety Factor | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

Check sheets are simple tools that allow data to be collected and recorded in an organized manner. Check sheets can be used to determine the frequency of a defect and the time period between occurrences by counting and categorizing the number of defects that occur over a specified time interval. Check sheets can also help to identify the causes and patterns of defects, and to monitor the effectiveness of improvement actions. The other statements are not true about check sheets. Check sheets do not provide a quick method to identify if possible defects exist, as they require data collection and analysis. Check sheets do not allow improvement teams to see if action items are being completed on time, as they are not designed to track the progress of tasks. Check sheets do not provide an indication of correlation between defects, as they do not measure the relationship between variables. References: Check Sheet | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

Inventory turnover is a ratio that measures how many times a company sells and replaces its inventory in a given period. It is calculated by dividing the cost of goods sold (COGS) by the average inventory value. A higher inventory turnover indicates a more efficient use of inventory, while a lower turnover implies excess inventory or poor sales1.

Based on the values reported in the table, we can calculate the inventory turnover as follows:

Inventory Turnover = COGS / Average Inventory Value = $260,000 / $150,000 = 1.73

Therefore, the correct answer is C.

References := 1 Inventory Turnover - How to Calculate Inventory Turns2

Mixed-model scheduling is a technique that produces different models of the same product family in the same production line or work center. One of the benefits of mixed-model scheduling is that it reduces the number of setups required, as the models share common components and processes. Fewer setups can lead to lower setup costs, higher productivity, and better utilization of resources. The other outcomes are not benefits of mixed-model scheduling. Increased inventory, improved demand response, and fewer material shortages are more related to other factors such as inventory policies, demand forecasting, and supply planning. References: Mixed Model Scheduling | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

The production plan is a high-level plan that defines the level of output to be produced for each product family or group in a given time period. It is based on the sales forecast, the aggregate production capacity, and the desired inventory levels. The production plan does not specify the quantities of each individual product to be produced, as this is done in the master production schedule. The production plan also does not include the sales forecast or the business plans for the company, as these are inputs to the production plan, not outputs12 References:

Introduction to Materials Management, 8th ed., 2017, Chapman, Stephen N., J. R. Tony Arnold, Ann K. Gatewood, and Lloyd M. Clive, ISBN: 978-0134156323, Chapter 11: Production Planning System

Manufacturing Planning and Control for Supply Chain Management, The CPIM Reference, 2nd ed., 2018, Jacobs, F. Robert, William L. Berry, D. Clay Whybark, and Thomas E. Vollmann, ISBN: 978-1260108385, Chapter 6: Production Planning Strategies

Concurrent engineering is a product design approach that involves the simultaneous and collaborative involvement of different functional areas, such as engineering, marketing, manufacturing, and suppliers, in the product development process. Concurrent engineering aims to reduce time to market, improve quality, lower costs, and enhance customer satisfaction by integrating and coordinating the inputs and feedback of all the stakeholders from the early stages of design. Concurrent engineering can also facilitate the standardization and modularization of product components, which can improve the flexibility and responsiveness of a global supply chain. References:

Managing Supply Chain Operations, Chapter 3: Product Design and Development, Section 3.2: Concurrent Engineering

CPIM Exam Content Manual, Module 1: Supply Chains and Strategy, Section 1.3: Product and Process Design, Subsection 1.3.1: Product and Process Design Concepts

In a rapidly changing business environment, a primary advantage of an effective customer relationship management (CRM) program is earlier identification of shifts in customer preferences. CRM is a strategy that focuses on building and maintaining long-term relationships with customers by understanding their needs, preferences, and behaviors. CRM enables organizations to anticipate and respond to changes in customer demand, improve customer satisfaction and loyalty, and increase profitability and competitiveness. CRM also helps organizations to segment and target customers based on their value and potential, and to customize products and services accordingly. CRM involves the use of various tools and techniques, such as data collection and analysis, communication channels, feedback mechanisms, and loyalty programs. References:

Managing Supply Chain Operations, Chapter 4: Customer Relationship Management, Section 4.1: Introduction to Customer Relationship Management

CPIM Exam Content Manual, Module 1: Supply Chains and Strategy, Section 1.2: Customer Relationship Management, Subsection 1.2.1: Customer Relationship Management Concepts

Third-party logistics (3PL) services are external providers that handle various supply chain functions for a firm, such as transportation, warehousing, inventory management, and order fulfillment. By outsourcing these functions to a 3PL, a firm can reduce its investment in fixed assets, such as trucks, trailers, warehouses, and equipment. This can improve the firm’s liquidity and return on assets ratios, as well as lower its depreciation and maintenance costs. However, using a 3PL does not necessarily affect the firm’s retained earnings, accounts receivable, or intangible assets, which are influenced by other factors, such as profitability, sales, and goodwill. References:

•Third-Party Logistics (3PL) Guide: Process, Resources, And Benefits

•3PLs, Explained: The Complete Guide to Third-Party Logistics

•Understanding 3PL: The Role of Third-Party Logistics in 2024

An effective approach to projecting requirements for materials with long lead times is to initiate a multilevel master schedule. A multilevel master schedule is a detailed plan that shows the quantities and timing of the end items and all of their components at each level of the bill of materials (BOM). By using a multilevel master schedule, a planner can determine the requirements for materials with long lead times and place orders in advance to avoid shortages or delays. A phantom bill of materials (BOM) is a temporary grouping of components that are used in the production of a parent item, but do not exist as a separate item in inventory. A phantom BOM is not an effective approach to projecting requirements for materials with long lead times, as it does not reflect the actual demand for the components. Increasing the level of safety stock is a way of mitigating the risk of uncertainty in demand or supply, but it is not an effective approach to projecting requirements for materials with long lead times, as it increases the inventory carrying costs and does not address the root cause of the problem. Decreasing the planning horizon is the opposite of an effective approach to projecting requirements for materials with long lead times, as it reduces the visibility and accuracy of the forecast and increases the likelihood of stockouts or excess inventory. References:

CPIM Part 2 Learning System, Module 1: Supply Chain Strategy, Section 1.4: Master Scheduling

CPIM Part 2 Learning System, Module 3: Supply, Section 3.2: Material Requirements Planning

The supply planning team is responsible for developing a supply plan that balances the demand plan with the available resources and capacities. The functional representatives on the supply planning team, such as production, procurement, engineering, and finance, need to ensure that their functional objectives are considered when developing the plans. For example, production needs to consider the impact of the supply plan on the production schedule, capacity utilization, and labor requirements. Procurement needs to consider the impact of the supply plan on the supplier relationships, lead times, and inventory levels. Engineering needs to consider the impact of the supply plan on the product design, quality, and innovation. Finance needs to consider the impact of the supply plan on the costs, revenues, and profitability. By ensuring that the functional objectives are considered, the supply planning team can create a feasible and optimal supply plan that aligns with the overall business strategy12. References: 1 S&OP: A Comprehensive Overview of Sales and Operations Planning 3 2 CPIM Exam References - Association for Supply Chain Management 1

The mean time between failures (MTBF) is the inverse of the failure rate. The failure rate is given as 0.00055 failures per hour, so the MTBF is 1/0.00055 = 1,818.2 hours. This means that the average time the machine operates without failing is 1,818.2 hours. References: MTBF Formula | How to Calculate Mean Time Between Failure? - EDUCBA, Mean time between failures - Wikipedia

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

A push system is a production system that relies on forecasts and schedules to plan the production and distribution of goods and services. A pull system is a production system that responds to actual customer demand and signals to trigger the production and distribution of goods and services. A transition from a push system to a pull system requires a change in the mindset and the processes of the organization, as well as the adoption of new tools and techniques to enable a demand-driven production system12.

One of the tools that is commonly used in a pull system is kanban, which is a visual signal that indicates the need for replenishment of materials or products. Kanban cards are attached to standardized containers that hold a fixed amount of inventory. When a container is empty, the kanban card is sent back to the upstream process as a signal to produce more. This way, the inventory level is controlled by the actual consumption of the downstream process, and the production is synchronized with the demand13.

One of the actions that hinders the transition from a push system to a pull system is using work orders as a backup. Work orders are documents that authorize the production of a certain quantity of a product or a service, based on a forecast or a schedule. Work orders are typical of a push system, as they are not triggered by the actual customer demand, but by the planned production. Using work orders as a backup means that the organization is not fully committed to the pull system, and still relies on the push system to ensure the availability of inventory. This can create confusion, inconsistency, and inefficiency in the production system, as well as increase the inventory holding costs and the risk of obsolescence1 .

Therefore, using work orders as a backup is the correct answer, as it is an action that hinders the transition from a push system to a pull system. The other options are actions that support the transition, as they are aligned with the principles and practices of a pull system.

A bill of resources is a tool that lists the capacity requirements for each work center or resource group based on the planned production quantities. It is used to evaluate the impact that a production plan has on capacity by comparing the available capacity with the required capacity. A bill of resources can also help identify capacity bottlenecks, excess capacity, and alternative resources. A demand time fence (DTF) is a tool that defines the period of time in which the master production schedule (MPS) is frozen and cannot be changed by customer orders. A product routing is a tool that defines the sequence of operations and work centers required to produce a product. A safety capacity is a tool that provides a buffer against demand and supply uncertainty by adding extra capacity to the planned capacity. These tools are not directly used to evaluate the impact that a production plan has on capacity, although they may affect the capacity planning process. References: Bill of Resources | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

One way to mitigate liability risk in the supply chain is to require traceability for components. Liability risk is the risk that a party may be held responsible for certain types of losses caused by its actions or products to third parties1. Traceability is the ability to track the origin, history, location, and movement of a product or a component through the supply chain2. Requiring traceability for components can help to mitigate liability risk in the supply chain by enabling the identification and verification of the quality, safety, and compliance of the components, as well as the detection and prevention of counterfeit, defective, or hazardous components. Traceability can also facilitate the recall, repair, or replacement of faulty components, and the allocation of responsibility and accountability among the supply chain partners in case of a liability claim34. References: 1 What is a Liability Risk? - Definition from Insuranceopedia 5 2 Traceability - Wikipedia 6 3 Supply Chain Liability in the Corporate Sustainability Due Diligence … 7 4 CPIM Exam References - Association for Supply Chain Management 8

 The time spent in queue by a specific manufacturing job is determined by the priority of the order. Priority is the relative importance or urgency of an order compared to other orders in the system. Priority can be assigned based on various criteria, such as due date, customer preference, profitability, or first-come-first-served. Priority determines the order in which jobs are processed at each workstation and affects the waiting time and flow time of each job. Higher priority jobs have shorter waiting times and lower priority jobs have longer waiting times. Priority can be used as a tool to manage the trade-offs between customer service, capacity utilization, and inventory levels. References:

Managing Supply Chain Operations, Chapter 7: Scheduling and Sequencing, Section 7.2: Priority Rules

CPIM Exam Content Manual, Module 6: Detailed Schedules, Section 6.2: Scheduling and Sequencing, Subsection 6.2.2: Priority Rules

The tracking signal is a measurement that indicates there may be bias in the forecast model. The tracking signal is the ratio of the cumulative forecast error to the mean absolute deviation (MAD). It measures how well the forecast is tracking the actual demand over time. A tracking signal of zero means that the forecast is perfectly accurate. A tracking signal within the range of -4 to +4 is considered acceptable. A tracking signal outside this range indicates that the forecast is consistently overestimating or underestimating the demand, which implies that there is bias in the forecast model. Bias is the tendency of a forecast to be consistently higher or lower than the actual demand. Bias can be caused by factors such as inaccurate data, inappropriate forecasting methods, or changes in demand patterns. References:

Managing Supply Chain Operations, Chapter 5: Demand Management and Forecasting, Section 5.2: Forecasting Methods, Subsection 5.2.3: Forecast Accuracy and Control

CPIM Exam Content Manual, Module 3: Demand, Section 3.2: Forecasting, Subsection 3.2.2: Forecasting Methods, Subsubsection 3.2.2.3: Forecast Accuracy and Control

Point-of-use storage is a stock location system that places inventory close to where it is needed or consumed in the production process. This reduces waste, handling, and transportation costs, and improves material flow and visibility. Point-of-use storage is a key element of a lean environment, where inventory is minimized and replenished frequently based on demand signals. References: EXAM CONTENT MANUAL PREVIEW, page 15, section 7.1.2. Manufacturing Planning and Control for Supply Chain Management: The CPIM Reference, Second Edition, page 462, section 13.3.

Substituting capital equipment in place of direct labor can be economically justified for scenario A, where volumes are forecasted to increase. This is because capital equipment can provide higher productivity, efficiency, and quality than direct labor, especially for large-scale and standardized production. Capital equipment can also reduce labor costs, such as wages, benefits, and training, and avoid labor shortages or turnover. However, capital equipment also involves high initial investment, maintenance, and depreciation costs, and may require more skilled workers to operate and monitor. Therefore, the substitution of capital equipment for direct labor should be based on a careful analysis of the trade-offs between the costs and benefits of both alternatives.

Option B is not correct, because material prices are forecasted to increase. This scenario does not directly affect the decision to substitute capital equipment for direct labor, as both alternatives use the same materials. However, increasing material prices may reduce the profitability of the production, and may require the company to find ways to reduce material usage, such as improving material yield, reducing scrap and rework, or sourcing from cheaper suppliers.

Option C is not correct, because implementing a pull system in production. This scenario does not favor the substitution of capital equipment for direct labor, as a pull system is based on the principle of producing only what is needed by the customer, when it is needed, and in the quantity needed. A pull system requires flexibility, responsiveness, and adaptability to the changing customer demand, which may be better achieved by direct labor than capital equipment. A pull system also aims to minimize inventory, waste, and overproduction, which may reduce the need for capital equipment.

Option D is not correct, because functional layouts are being utilized. This scenario does not support the substitution of capital equipment for direct labor, as functional layouts are based on grouping similar or related processes or machines together, regardless of the product flow. Functional layouts may result in long and complex material flows, high transportation and handling costs, high work-in-process inventory, and low visibility and coordination of the production. Functional layouts may also require more direct labor to move and monitor the materials and machines. Capital equipment may be more suitable for product layouts, where the processes or machines are arranged according to the sequence of operations for a specific product or family of products.

Finite loading is a capacity planning approach that takes into account the available capacity of the resources and does not allow overloading. It considers adjustments to plans based on planned capacity utilization, which means that it can change the start or end dates of the operations to avoid exceeding the capacity limits. This way, finite loading ensures that the production schedule is realistic and feasible. Other capacity planning approaches, such as infinite loading, do not consider adjustments to plans based on planned capacity utilization. Infinite loading ignores the capacity constraints and schedules the operations based on the due dates and the lead times, regardless of the resource availability. This may result in overloading the resources and causing delays or disruptions in the production process. Therefore, the fundamental difference between finite loading and other capacity planning approaches is that finite loading considers adjustments to plans based on planned capacity utilization, while other approaches do not. References:

CPIM Part 2 Exam Content Manual, p. 48

The Difference Between Finite Capacity Scheduling and Infinite Capacity Loading

FINITE LOADING

Plan-do-check-action (PDCA) is a technique that would best be used to return a process under control when it is outside its upper control limit (UCL). PDCA is a four-step cycle of continuous improvement that involves planning a change, implementing the change, checking the results, and acting on the findings. PDCA can help identify and eliminate the root causes of variation, improve the process performance, and prevent the recurrence of problems. PDCA is also known as the Deming cycle or the Shewhart cycle. References:

Managing Supply Chain Operations, Chapter 9: Quality Management, Section 9.3: Quality Improvement, Subsection 9.3.1: Plan-Do-Check-Act Cycle

CPIM Exam Content Manual, Module 8: Quality, Technology and Continuous Improvement, Section 8.2: Continuous Improvement, Subsection 8.2.1: Continuous Improvement Concepts, Subsubsection 8.2.1.1: Plan-Do-Check-Act Cycle

Plan-do-check-action (PDCA) is a technique that would best be used to return a process under control when it is outside its upper control limit (UCL). PDCA is a four-step cycle of continuous improvement that involves planning a change, implementing the change, checking the results, and acting on the findings. PDCA can help identify and eliminate the root causes of variation, improve the process performance, and prevent the recurrence of problems. PDCA is also known as the Deming cycle or the Shewhart cycle. References:

Managing Supply Chain Operations, Chapter 9: Quality Management, Section 9.3: Quality Improvement, Subsection 9.3.1: Plan-Do-Check-Act Cycle

CPIM Exam Content Manual, Module 8: Quality, Technology and Continuous Improvement, Section 8.2: Continuous Improvement, Subsection 8.2.1: Continuous Improvement Concepts, Subsubsection 8.2.1.1: Plan-Do-Check-Act Cycle

An X-bar chart is a type of control chart that is used to determine the average value of a group of units. It is also known as a mean chart. It plots the sample means of subgroups of units over time and compares them with the center line and the control limits. An X-bar chart is useful for monitoring the central tendency of a process and detecting any shifts or trends in the process mean. It is often used in conjunction with an R-chart, which measures the subgroup variation. References:

Managing Supply Chain Operations, Chapter 9: Quality Management, Section 9.2: Statistical Process Control, Subsection 9.2.1: Control Charts

CPIM Exam Content Manual, Module 8: Quality, Technology and Continuous Improvement, Section 8.1: Quality Management, Subsection 8.1.2: Statistical Process Control, Subsubsection 8.1.2.1: Control Charts

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.

Concurrent engineering is a method of designing and developing products in which the different stages run simultaneously, rather than consecutively. It decreases product development time and also the number of errors and rework. By involving all the relevant stakeholders, such as engineering, manufacturing, marketing, and purchasing, in the design process from the beginning, concurrent engineering reduces the need for product design changes later in the product life cycle. References:

•APICS CPIM Part 2 Exam Content Manual, p. 15

•[APICS CPIM Learning System Version 8.0], Module 2, Section B, p. 2-17

Transportation cost and delivery time are two of the trade-offs that should be evaluated when determining where to place inventory in a multi-echelon supply chain network. A multi-echelon supply chain network consists of multiple levels of distribution, such as factories, warehouses, distribution centers, and retailers. Placing inventory closer to the customers can reduce the delivery time and improve the service level, but it can also increase the transportation cost and the inventory holding cost. Placing inventory farther from the customers can reduce the transportation cost and the inventory holding cost, but it can also increase the delivery time and the risk of stockouts. Therefore, the optimal inventory placement depends on balancing these trade-offs and finding the lowest total cost for the desired service level. The other trade-offs are not directly related to inventory placement in a multi-echelon supply chain network. Production cost and lot size quantity are more related to inventory replenishment policies and economies of scale. Purchase cost and shrinkage rates are more related to inventory sourcing and quality control. Customer price and order quantity are more related to demand management and pricing strategies. References: Network Design and Safety Stock Placement for a Multi-Echelon Supply Chain, APICS CPIM 8 Planning and Inventory Management | ASCM