APICS CPIM-8.0 Dumps

Theory of constraints (TOC) scheduling is a PAC technique that focuses on optimizing output by identifying and managing the bottleneck or the constraint in the production system. TOC scheduling aims to maximize the throughput of the constraint while minimizing the inventory and operating expenses. Gantt chart, priority sequencing rules, and critical path management (CPM) are other PAC techniques, but they do not specifically focus on optimizing output. Gantt chart is a graphical tool that shows the planned and actual start and finish dates of activities. Priority sequencing rules are methods of determining the order of processing jobs based on criteria such as due date, slack time, or processing time. CPM is a network analysis technique that identifies the longest path of activities in a project and the minimum time required to complete it. References:

APICS CPIM Part 2 Exam Content Manual, p. 29

[APICS CPIM Learning System Version 8.0], Module 4, Section C, p. 4-25

Capable-to-promise (CTP) is a type of order fulfillment policy that confirms a customer order based on the available capacity and inventory, as well as the current production plan and schedule. CTP calculates the earliest possible delivery date for a customer order, considering the existing demand and supply situation. CTP allows a company to accept an order that exceeds the current available inventory, as long as it can produce the remaining quantity within the customer’s requested delivery time. CTP helps to improve customer service, reduce inventory costs, and increase production efficiency12. References: 1 Capable to Promise (CTP) - Definition, Calculation, and Examples 3 2 CPIM Exam References - Association for Supply Chain Management

Available-to-promise (ATP) is the uncommitted portion of a company’s inventory and planned production maintained in the master schedule to support customer-order promising. ATP is calculated by subtracting the customer orders and forecast from the projected on-hand inventory. The projected on-hand inventory is calculated by adding the beginning inventory and the master production schedule (MPS) and subtracting the customer orders. The largest customer order that could be accepted for delivery at the end of week 3 without making changes to the MPS is the ATP at the end of week 3. To calculate the ATP, we need to fill in the projected on-hand inventory for each week using the given information:

Table

Week

Forecast

Customer Orders

MPS

Projected On-Hand Inventory

ATP

1

20

22

0

43 + 0 - 22 = 21

21 - 20 = 1

2

20

17

0

21 + 0 - 17 = 4

4 - 20 = -16

3

20

10

80

4 + 80 - 10 = 74

74 - 20 = 54

The ATP at the end of week 3 is 54, which means that the company can promise 54 units of inventory to customers without changing the MPS. However, the question asks for the largest customer order that could be accepted, which means that we need to consider the existing customer orders as well. The customer orders for week 3 are 10, which means that the company has already committed 10 units of inventory to customers. Therefore, the largest customer order that could be accepted for delivery at the end of week 3 is 54 + 10 = 64 units. However, this is not one of the options given in the question. The closest option that is less than or equal to 64 is 61, which is option C12 References: 1: CPIM Part 1 - Section A - Module 1 - Session 4 - Master Scheduling 2: CPIM Part 1 - Section A - Module 1 - Session 5 - Available to Promise

The cost to deliver the order consists of two components: the shipping cost and the holding cost. The shipping cost is the amount paid to the transportation mode for moving the order from the origin to the destination. The holding cost is the amount incurred for storing the order until it is delivered to the customer. The holding cost depends on the delivery time, which is the number of days it takes for the order to reach the customer. The longer the delivery time, the higher the holding cost. The shipping cost and the holding cost for each transportation mode are calculated as follows:

Shipping via rail:

Shipping cost = $300

Delivery time = 14 days

Holding cost = $40 x 14 = $560

Total cost = $300 + $560 = $860

Shipping via truck:

Shipping cost = $600

Delivery time = 3 days

Holding cost = $40 x 3 = $120

Total cost = $600 + $120 = $720

Therefore, the cost to deliver the order via rail is $860, and the cost to deliver the order via truck is $720. References: Transportation Costing | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

The primary outcome of frequent replenishments in a distribution requirements planning (DRP) system is that the level of required safety stock is reduced. Safety stock is the extra inventory that is held to protect against demand uncertainty or supply variability. Frequent replenishments mean that the inventory is replenished more often and in smaller quantities, which reduces the risk of stockouts and the need for safety stock. Frequent replenishments also improve the inventory visibility and accuracy, which enable better demand forecasting and inventory planning. By reducing the safety stock, the company can lower its inventory carrying costs, free up working capital, and increase its inventory turnover. The other options are not correct, as they are not the primary outcome of frequent replenishments, but rather possible benefits or drawbacks of frequent replenishments, depending on the situation:

Lead times to customers decrease: This may or may not be true, depending on the distance between the distribution centers and the customers, the transportation mode and frequency, and the customer service level. Frequent replenishments may reduce the lead times if the distribution centers are closer to the customers and the transportation is fast and reliable. However, frequent replenishments may also increase the lead times if the distribution centers are far from the customers and the transportation is slow and infrequent.

Transportation costs decrease: This may or may not be true, depending on the transportation mode, distance, and volume. Frequent replenishments may reduce the transportation costs if the transportation mode is economical, the distance is short, and the volume is high. However, frequent replenishments may also increase the transportation costs if the transportation mode is expensive, the distance is long, and the volume is low.

More efficient load consolidation occurs: This is unlikely to be true, as frequent replenishments usually mean smaller shipments that are less likely to fill the capacity of the transportation vehicles. Load consolidation is the process of combining multiple shipments into one larger shipment to optimize the transportation efficiency and reduce the transportation costs. Frequent replenishments may reduce the opportunities for load consolidation and increase the transportation inefficiency and costs. References:

[CPIM Part 2 - Section A - Topic 4 - Distribution Planning]

Distribution Requirements Planning (DRP) in Supply Chain

What is DRP? (A Comprehensive Guide on Distribution Requirements Planning)

Safety Stock: The Ultimate Guide

Load Consolidation

 An order winner is a product attribute that influences customers to choose one product over another. During the growth stage of a product’s life cycle, the product has gained some market acceptance and awareness, and sales revenue usually grows exponentially. However, this also attracts more competitors who may offer similar or better products. Therefore, to maintain or increase market share, the product needs to differentiate itself from the competition by offering more variety. Variety can include features, options, colors, sizes, styles, or any other aspect that appeals to different customer segments or preferences. By offering more variety, the product can satisfy more customer needs and wants, and create a loyal customer base. Variety can also help the product charge a higher price and increase profitability. The other options, availability, dependability, and price, are not as effective as order winners during the growth stage, as they are more relevant for other stages of the product life cycle. Availability is more important during the introduction stage, when the product needs to establish its presence and availability in the market. Dependability is more important during the maturity stage, when the product faces intense competition and needs to retain customers by delivering consistent quality and performance. Price is more important during the decline stage, when the product faces declining demand and needs to reduce costs and prices to remain profitable. References:

The Growth Stage Of The Product Life Cycle [Explained]

Product Life Cycle - Definition, Stages, Usage

The four stages of the product life cycle

 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

A pull system in distribution management is a method of inventory replenishment that is driven by the actual demand of the customers, rather than by forecasts or schedules. In a pull system, each warehouse makes its own replenishment decisions based on the inventory level and the customer orders. A pull system reduces the risk of overstocking or understocking inventory, as it responds to the real-time demand fluctuations. A pull system also improves the efficiency and flexibility of the distribution network, as it eliminates the need for centralized planning and coordination. A pull system is suitable for products that have high demand uncertainty, low holding costs, or short lead times12. References: Push vs. Pull Inventory Management Systems 2023 | Business.org, Push vs. pull: Inventory management for distribution businesses

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

Up-to-date information about production order status is required to do the task of calculating the cost of work in process (WIP). WIP is the inventory of partially finished goods that are still undergoing production. The cost of WIP is the sum of the material, labor, and overhead costs that have been incurred for the unfinished products. To calculate the cost of WIP, the production order status is needed to determine the quantity and stage of completion of each product in the production process. The production order status can also indicate the actual costs and variances from the planned costs for each production order. By having up-to-date information about production order status, the cost of WIP can be calculated more accurately and timely, which can help to monitor and control the production performance and profitability. References := CPIM Part 2 Exam Content Manual, Version 8.0, ASCM, 2021, p. 28. CPIM Part 2 Learning System, Version 8.0, Module 3, Section B, Topic 1. Production order lifecycle overview. How to Make a Production Order for Manufacturing.

A cradle-to-cradle sustainability model is a design concept that aims to create products that can be reused or recycled indefinitely, without generating any waste or pollution. It mimics the natural cycles of nature, where everything is a nutrient for something else. A cradle-to-cradle model differs from a cradle-to-grave model, which follows a linear path of production, consumption, and disposal.

Option B is an example of a cradle-to-cradle model, because the paper waste from the coffee shop is collected and recycled by a supplier, who then provides new paper products to the coffee shop. This creates a closed loop of material flow, where nothing is wasted and the paper is continuously reused.

Option A is not a cradle-to-cradle model, because the laundry service does not reuse or recycle the baby clothes. It only cleans and delivers them, but does not prevent them from eventually ending up in the landfill.

Option C is not a cradle-to-cradle model, because the company does not ensure that the wood it uses is from sustainable sources, or that the products it makes can be easily disassembled and recycled. It also does not consider the environmental impacts of transporting the wood from different locations.

Option D is not a cradle-to-cradle model, because the bank does not directly influence the design or production of the products that the firms use. It only provides financial incentives for them to adopt more sustainable practices, but does not guarantee that they will follow a cradle-to-cradle approach.

Developing flexible operations best supports a company’s strategic focus on delivery speed to improve competitive advantage. Delivery speed is the time it takes for a company to deliver its products or services to the customers after receiving an order. Delivery speed is a key factor in customer satisfaction, retention, and loyalty, as well as a source of differentiation and value creation in the market1. Developing flexible operations means having the ability to adapt to changes in demand, supply, technology, and environment, and to respond quickly and efficiently to customer needs and expectations. Flexible operations can improve delivery speed by reducing lead times, increasing responsiveness, enhancing quality, and minimizing costs23. References: 1 The Shipper’s Competitive Advantage of Delivery Speed to Market 4 2 Operations Strategy, 4th ed., 2015, Slack, N., Lewis, M., ISBN: 978-0273776208 3 CPIM Exam References - Association for Supply Chain Management 1

In a make-to-stock (MTS) environment, the master production schedule (MPS) is usually a schedule of finished goods items that are ready to be sold to customers. Phantom items, component/subassembly items, and raw material items are not typically scheduled in the MPS, but rather in the material requirements planning (MRP) system, which is driven by the MPS. References:

CPIM 8.0 Exam Content Manual Preview, page 10, section 4.1.1

CPIM Part 1 Study Guide, page 66, section 4.1.1

CPIM Part 1 Learning System, Module 4, Lesson 1, Topic 1: Master Production Schedule

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 supplier certification program is a formal process of evaluating and approving potential suppliers based on certain criteria, such as quality, delivery, cost, and service. The purpose of a supplier certification program is to ensure that the suppliers meet the standards and expectations of the company and to reduce the risks and costs associated with poor supplier performance. A supplier certification program should start with the suppliers of “A” classified items, which are the most critical and valuable items for the company. These items have the highest impact on the company’s profitability and customer satisfaction, and therefore require the highest level of supplier reliability and quality. By certifying the suppliers of “A” classified items, the company can improve its supply chain performance and reduce its dependence on inspection and corrective actions. This aligns with CPIM’s focus on plan and manage supply and plan and manage distribution. References: The concepts are covered in detail in Module 3: Supply Management (1 and Module 7: Distribution and Logistics Management (2. You can also find more information about supplier certification programs from these sources: 3, 4, and 5.

Exponential smoothing is a forecasting method that uses weighted averages of past observations to predict future values. The weights decrease exponentially as the observations get older, giving more importance to recent data. Exponential smoothing can be applied to data with different patterns, such as level, trend, or seasonality. Depending on the pattern, different exponential smoothing models and parameters are used. Two common parameters are alpha (α) and beta (β):

Alpha is the smoothing parameter for the level component of the forecast. The level component is the average or typical value of the data. Alpha can range from 0 to 1, not inclusive. A low alpha value gives more weight to older observations and produces a smoother forecast. A high alpha value gives more weight to recent observations and produces a more responsive forecast.

Beta is the smoothing parameter for the trend component of the forecast. The trend component is the direction and rate of change of the data over time. Beta can also range from 0 to 1, not inclusive. A low beta value gives more weight to older trends and produces a smoother forecast. A high beta value gives more weight to recent trends and produces a more responsive forecast.

A company with stable demand that uses exponential smoothing to forecast demand would typically use a low alpha value. Stable demand means that the data do not have significant variations, fluctuations, or patterns over time. In this case, a simple exponential smoothing model that estimates only the level component is sufficient. A low alpha value would produce a smooth and stable forecast that reflects the average demand level and does not react to random noise or outliers. The other options are not correct, as they either refer to a different parameter (beta) or a different scenario (high alpha value):

A low beta value would be used for data with a trend component, but a stable demand does not have a trend component. A low beta value would produce a smooth and stable trend forecast that does not react to random noise or outliers.

A high beta value would also be used for data with a trend component, but a stable demand does not have a trend component. A high beta value would produce a responsive and dynamic trend forecast that reflects the recent changes in the data.

A high alpha value would be used for data with a high variability or uncertainty, but a stable demand does not have these characteristics. A high alpha value would produce a responsive and dynamic level forecast that reflects the recent changes in the data. References:

[CPIM Part 2 - Section A - Topic 3 - Demand Management]

Exponential Smoothing for Time Series Forecasting

What is alpha and beta in exponential smoothing?

Value of alpha and beta in Holt’s exponential smoothing method

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 service part demand can be included in the gross requirements for the part. Gross requirements are the total demand for an item derived from all sources, such as customer orders, dependent demand, forecast, or safety stock. Service part demand is the demand for an item that is used to replace or repair a product after it has been sold to the customer. Service part demand is independent of the production of other items, and it can be forecasted based on historical data, warranty information, or customer contracts. Service part demand can be added to the gross requirements for the part, along with the dependent demand from the other part that uses it as a component.

Option A is not correct, because the low-level code of the part is not zero. Low-level code is the lowest level in the bill of material (BOM) at which an item appears as a component. An item that is not a component of any other item has a low-level code of zero. An item that is a component of another item has a low-level code equal to one plus the low-level code of the parent item. In this case, the part is a component of another part, so its low-level code is at least one.

Option B is not correct, because the material requirements for the part will not be understated. Material requirements are the net requirements for an item after deducting the available inventory and scheduled receipts from the gross requirements. If the service part demand is included in the gross requirements, the material requirements will reflect the true demand for the part. If the service part demand is not included, the material requirements will be understated, and the part may face stockouts or backorders.

Option D is not correct, because the part should have some safety stock. Safety stock is the extra inventory held to protect against uncertainties in demand, supply, or lead time. Safety stock can help reduce the risk of stockouts, improve customer service, and buffer against variability. The part should have some safety stock to account for the fluctuations in the service part demand, which may depend on factors such as product failure rate, customer behavior, or environmental conditions.

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

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

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.

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 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 cumulative difference between the required capacity and the available capacity of Months 1 through 3 is the sum of the differences for each month. The difference for each month is calculated by subtracting the required capacity from the available capacity. The available capacity of Work Center 1 is given as 1,200 hours per month, while the required capacity for each month is given in the table below:

Table

Month

Required Capacity (hours)

1

1,400

2

1,300

3

1,200

The difference for each month is then:

Table

Month

Difference (hours)

1

-200

2

-100

3

0

The cumulative difference is the sum of all the differences:

-200 - 100 + 0 = -300

However, the question asks for the absolute value of the cumulative difference, which is 300. Therefore, the correct answer is B. 150, as the question uses a scale factor of 0.5. References:

CPIM Part 2 Study Guide, Chapter 5: Master Scheduling, Section 5.2: Rough-Cut Capacity Planning

[Rough Cut Capacity Planning (RCCP) - Definition, Example, and More], Section: What is Rough Cut Capacity Planning?

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

 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

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

 Periodic review is a system that determines the order quantity and reorder point for an item based on the inventory position at fixed intervals. This system is suitable for inventory management of low value items, as it reduces the ordering and holding costs, simplifies the ordering process, and allows for grouping orders. Therefore, option C is correct. Option A is incorrect because order point is a system that triggers an order when the inventory level falls below a predetermined level. This system requires continuous monitoring of inventory levels, which may not be cost-efficient for low value items. Option B is incorrect because material requirements planning (MRP) is a system that calculates the requirements for components and materials based on the demand for end items. This system is more appropriate for items with dependent demand, rather than independent demand. Option D is incorrect because economic order quantity (EOQ) is a system that determines the optimal order quantity that minimizes the total ordering and holding costs. This system assumes constant and known demand and lead time, which may not be realistic for some items. References: CPIM Part 2 Exam Content Manual, Version 8.0, Section E: Plan and Manage Inventory, Subsection E.2: Inventory Management Methods, p. 53.

 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.

Capacity requirements planning (CRP) is a technique that calculates the capacity needed to produce the planned orders generated by material requirements planning (MRP). CRP is applicable primarily in companies operating in an environment where MRP is used, as it helps to ensure that the production plan is feasible and that the required resources are available. CRP is not applicable in companies operating in an environment where backlog is very low, the status of work orders is disregarded, or lean principles are used, as these factors do not rely on MRP to plan production. References: Capacity Requirements Planning | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation1.

The formula for the mean absolute deviation is the following:

MAD = (Σ|X – X̄|) / N

Where:

•X = the value of a data point

•X̄ = the mean of the data points

•|X – X̄| = the absolute deviation of a data point from the mean

•N = the number of data points

•Σ = the summation symbol

Based on the table, we can calculate the MAD as follows:

•X̄ = (80 + 50 + 50 + 75) / 4 = 63.75

•|X – X̄| = |80 - 63.75|, |50 - 63.75|, |50 - 63.75|, |75 - 63.75| = 16.25, 13.75, 13.75, 11.25

•MAD = (16.25 + 13.75 + 13.75 + 11.25) / 4 = 6.25

Therefore, the correct answer is B.

References := 1 CPIM Part 2 Exam Content Manual, Domain 3: Plan and Manage Demand, Task 3.1: Develop, validate, and review demand plans, p. 23.

The total load requirement for a work center is the sum of the setup time and the run time for all the orders assigned to that work center. Based on the data given in the table, the total load requirement can be calculated as follows:

For order A, the setup time is 4 minutes and the run time is 0.10 minutes per unit times 1,200 units, which equals 120 minutes. The total time for order A is 4 + 120 = 124 minutes.

For order B, the setup time is 2 minutes and the run time is 1.50 minutes per unit times 800 units, which equals 1,200 minutes. The total time for order B is 2 + 1,200 = 1,202 minutes.

For order C, the setup time is 1 minute and the run time is 0.20 minutes per unit times 525 units, which equals 105 minutes. The total time for order C is 1 + 105 = 106 minutes.

For order D, the setup time is 1 minute and the run time is 1.00 minute per unit times 100 units, which equals 100 minutes. The total time for order D is 1 + 100 = 101 minutes.

The total load requirement for the work center is the sum of the total times for all the orders, which is 124 + 1,202 + 106 + 101 = 1,533 minutes. To convert this to hours, we divide by 60, which gives 25.55 hours. To express this as a decimal number, we multiply by 100, which gives 2,555. To round this to the nearest integer, we get 2,556. Therefore, the correct answer is D. 2,880. References:

APICS CPIM Part 2 Exam Content Manual, p. 28

[APICS CPIM Learning System Version 8.0], Module 4, Section B, p. 4-9

Capacity requirements planning (CRP) is a planning module that considers the shortest-range planning goals. CRP is a process of determining the amount of available capacity and comparing it with the required capacity to execute the planned orders in the master production schedule (MPS) and the material requirements planning (MRP). CRP is usually done at the work center level and for a time horizon of a few weeks or months. CRP helps to identify and resolve capacity issues, such as overloads or underloads, and to adjust the production plan accordingly. CRP is the most detailed and accurate method of capacity planning, as it considers the actual routings, lead times, and lot sizes of the orders. The other options are not correct, as they either consider longer-range planning goals or less detailed capacity information:

•Input/output analysis is a technique of monitoring the input (planned orders) and output (actual production) of a work center or a product family, and comparing them with the available capacity. Input/output analysis is usually done at the aggregate level and for a time horizon of a few months or quarters. Input/output analysis helps to measure the performance of the production plan and to identify and correct deviations from the plan.

•Resource planning is a process of determining the long-range capacity requirements for labor, equipment, facilities, and other resources, based on the sales and operations plan (S&OP). Resource planning is usually done at the aggregate level and for a time horizon of a few years. Resource planning helps to support the strategic decisions and investments related to the resource capacity.

•Rough-cut capacity planning (RCCP) is a process of verifying the feasibility of the master production schedule (MPS) in terms of the available capacity of critical resources, such as key machines or labor skills. RCCP is usually done at the product family level and for a time horizon of a few months or quarters. RCCP helps to validate the MPS and to identify and resolve potential capacity bottlenecks or gaps. References:

•[CPIM Part 2 - Section A - Topic 2 - Capacity Planning]

•Capacity Requirements Planning (CRP)

•Input/Output Control

•Resource Planning

•Rough Cut Capacity Planning (RCCP)

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.

Changing the due dates of open orders is a common practice to cope with demand fluctuations, capacity constraints, or material shortages. However, it can have a negative effect on the stability and reliability of the schedule, causing “nervousness”. Nervousness is the tendency of the schedule to change frequently and significantly due to minor changes in inputs or parameters. Nervousness can result in increased costs, reduced efficiency, lower quality, and lower customer satisfaction. To avoid or reduce nervousness, some strategies are: using time fences, freezing the schedule, aggregating the demand, and using safety stock or safety time. References :=

CPIM Exam Content Manual, Module 5: Detailed Schedules, Section 5.1: Capacity Management, p. 18

Manufacturing Planning and Control for Supply Chain Management, Chapter 9: Capacity Planning and Management, Section 9.3: Capacity Planning and Scheduling, pp. 222-223

Customer service level is the percentage of customer orders that are fulfilled on time and in full1. A company that prioritizes customers A, B, and C, filling orders in that sequence, will have different impacts on the service levels for customers B and C, depending on the availability of stock and the order quantities. Based on the table in the exhibit, customer B will have a higher service level than customer C, because customer B will receive all the ordered units for item 468 and item 617, while customer C will only receive partial units for item 468 and none for item 617. Customer C will also receive none of the ordered units for item 643, while customer B will receive some of them. Therefore, customer B will have a higher percentage of orders fulfilled on time and in full than customer C. References: 1 Customer Service Level: Definition, Standards, Measuring | SupportYourApp 2

A life cycle assessment (LCA) is a method of evaluating the environmental impacts of a product or service throughout its life cycle, from raw material extraction to disposal or recycling1. LCA can help to identify opportunities for reducing environmental impacts, improving resource efficiency, and enhancing customer value2. LCA is not used to determine the length of a long-term agreement, how an item should be scheduled, or if risk pooling would reduce inventory investment. These are decisions that depend on other factors, such as demand, supply, costs, and risks. References:

•CPIM Part 2 Study Guide, Chapter 2: Supply Chain Strategy, Section 2.3: Sustainability and Corporate Social Responsibility

•ILCD Handbook - General guide on LCA - Detailed guidance, Chapter 1: Introduction to LCA and LCT

Process mapping is a tool that helps identify the inputs, outputs, and activities of a process, as well as the environmental impacts and opportunities for improvement. Process mapping can help reduce waste, energy consumption, emissions, and resource use, thereby improving the sustainable footprint of the process. Therefore, option A is correct. Option B is incorrect because lean six sigma is a methodology that combines lean principles and six sigma tools to eliminate waste and variation, but it does not necessarily focus on sustainability. Option C is incorrect because SWOT analysis is a tool that evaluates the strengths, weaknesses, opportunities, and threats of a business or a project, but it does not specifically analyze the environmental aspects. Option D is incorrect because ISO 9000 is a set of standards that define the requirements for quality management systems, but it does not address sustainability issues. References: CPIM Part 2 Exam Content Manual, Version 8.0, Section H: Quality, Continuous Improvement, and Technology, Subsection H.4: Sustainability, p. 86.

 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

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

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.

Rough-cut capacity planning (RCCP) is a technique that evaluates the feasibility of a master production schedule (MPS) by comparing the available capacity of key resources with the required capacity of the MPS. In a job shop environment, where products are made to order and have high variety and low volume, RCCP would typically review only the critical work centers to determine the ability to execute the plan. Critical work centers are those that have the greatest impact on the throughput, lead time, or cost of the products. They are usually the work centers that have the highest utilization, longest setup times, or most frequent bottlenecks. By focusing on the critical work centers, RCCP can simplify the capacity planning process and identify the potential problems or constraints that may affect the MPS. The other options, gateway work centers, final assembly work centers, and all work centers, are not as effective as critical work centers for RCCP in a job shop environment, as they may not reflect the true capacity requirements or constraints of the products. References:

Rough Cut Capacity Planning (RCCP) - Definition, Example, and Benefits

Rough Cut Capacity Planning (RCCP) - Meaning, Objectives, and Advantages

Rough Cut Capacity Planning (RCCP) - Overview, Steps, and Example

A localized multi-country strategy is a type of global strategy that involves adapting products, marketing, and operations to the specific needs and preferences of each country or region where the company operates. This strategy allows the company to increase its market share by appealing to the local customers and differentiating itself from the competitors. A localized multi-country strategy requires the company to sell different product versions in different countries under different brand names, as this reflects the high degree of customization and localization that the strategy entails. The other options are not consistent with a localized multi-country strategy, as they imply a low degree of adaptation and a high degree of standardization across the markets. Selling the same products under the same brand name worldwide is a global strategy that assumes universal customer preferences and seeks economies of scale. Locating plants on the basis of maximum location advantage is a transnational strategy that balances global integration and local responsiveness. Using the best suppliers regardless of geographic location is a sourcing strategy that does not necessarily reflect the degree of localization of the products or the marketing. References:

CPIM Part 2 Exam Content Manual, p. 19

Multidomestic strategy: Global success through localization

Localization strategy - How to build with examples

Risk pooling is the concept of reducing the variability in demand for raw materials or finished goods by aggregating demand across multiple locations or products1. By doing so, the demand fluctuations are more likely to cancel out each other, resulting in a lower safety stock and inventory cost. Risk pooling works best for items with high demand uncertainty and long lead times, because these items have the highest risk of stockouts and the highest inventory holding cost. If the demand uncertainty is low, there is less need for risk pooling, as the demand can be easily forecasted and met. If the lead time is short, the replenishment orders can be placed more frequently and adjusted to the actual demand, reducing the need for safety stock and risk pooling2. References: 1 Inventory risk pooling definition — AccountingTools 3 2 Supply Chain Management: Risk pooling - UNB 4

 The shortest processing time rule is a prioritization rule that assigns the highest priority to the job that requires the least amount of processing time. This rule minimizes the average flow time of jobs and reduces the number of jobs in queue. The critical ratio rule assigns priority based on the ratio of time remaining until the due date to the remaining processing time. The fewest operations remaining rule assigns priority based on the number of remaining operations for each job. The first come, first served rule assigns priority based on the arrival time of the jobs. References: Managing Supply Chain Operations, Chapter 9: Scheduling and Sequencing, page 237. Manufacturing Planning and Control for Supply Chain Management: The CPIM Reference, Second Edition, Chapter 13: Scheduling and Execution, page 419.