CPIM-8.0 APICS Certified in Planning and Inventory Management (CPIM 8.0) Free Practice Exam Questions (2025 Updated)

 Prevention is a risk control strategy that involves avoiding or eliminating the sources of risk. By deciding not to pursue a business opportunity in a foreign market due to political instability and currency fluctuations, the company prevented the potential losses or disruptions that could arise from these factors. Mitigation is a risk control strategy that involves reducing the impact or likelihood of risk. Recovery is a risk control strategy that involves restoring normal operations after a risk event occurs. Wait and see is a risk control strategy that involves monitoring the risk situation and taking action only when necessary. References:

CPIM Part 2 Learning System, Module 1: Supply Chain Strategy, Section 1.5: Risk Management

CPIM Part 2 Learning System, Module 4: Execution and Control of Operations, Section 4.3: Risk Management

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.

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.

References:

•Cradle-to-Cradle for Sustainable Development: From Ecodesign to Circular Economy

•Cradle to Cradle – Sustainability Guide

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 timeperiod 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

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

 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.

The total landed cost is the sum of all the costs associated with buying a quantity larger than immediately needed, including the cost of the product, the custom fees, the freight, and the warehouse rent. Based on the table, the total landed cost can be calculated as follows:

Landed cost = material cost + custom fees + freight + warehouse rent Landed cost = $500 + $125 + $700 + $200 Landed cost = $1,525

Therefore, the correct answer is D. $1,525. The other options are not correct, as they either omit some of the costs or use incorrect values. The total landed cost reflects the direct costs only to move the product from the factory floor to the customer. It is an important supply chain KPI in inventory management, as it helps to determine the optimal order quantity, pricing, and profitability of the products12. References:

What is Landed Cost? | Calculation and Tips to Improve - ORBA Cloud CFO

What is Landed Cost & Why is it Important | Finale Inventory

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

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, notinclusive. 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

Moving average forecasting methods are best when demand shows high random variation, as they help to smooth out the noise and capture the underlying level of demand. Moving average methods use the average of the most recent observations as the forecast for the next period. They assign equal weights to all observations in the average, and drop the oldest observation when a new one becomes available. Moving average methods are not suitable for demand patterns that show a clear trend, consistent seasonality, or a cyclical pattern, as they cannot capture these components of demand. For these patterns, more sophisticated methods such as exponential smoothing or regression are needed. References: Forecasting with moving averages, APICS CPIM 8 Planning and Inventory Management | ASCM

Time series decomposition is a method that breaks down a time series of historical demand data into its components: trend, seasonality, cyclical, and random. It is appropriate for forecasting the demand for a product family when there is a significant trend and seasonality in the demand history, as it can isolate and estimate these components and project them into the future. Time series decomposition can also handle cyclical and random variations in demand, and it can be applied to different time intervals (such as monthly, quarterly, or yearly). The other methods are not suitable for this scenario. Econometric models are complex mathematical models that use regression analysis to relate demand to various explanatory variables, such as price, income, or advertising. They are not designed to capture trend and seasonality in demand. Computer simulation is a technique that uses a computer program to mimic the behavior of a real system under different scenarios and assumptions. It is not a forecasting method per se, but rather a tool for testing and evaluating different forecasting methods or policies. Weighted moving average is a simple method that uses the average of the most recent observations as the forecast for the next period, with more weight given to the recent observations than the older ones. It is not able to capture trend and seasonality in demand, as it assumes that demand is stable and does not change over time. References: Time Series Decomposition | APICS Dictionary Term of the Day, APICS CPIM 8 Planning and Inventory Management | ASCM

Given the bill of material (BOM) information, we can calculate the weekly gross requirement of component F by considering the independent requirements of Component A and B. For Component A, there is no direct requirement for Component F. For Component B, which has an independent requirement of 20 pcs per week, each requires 4 pcs of Component F according to its BOM. So, thetotal weekly gross requirement for Component F due to Component B is 204 = 80 pcs. Additionally, each piece of Component A requires 2 pieces of Component C according to its BOM and has an independent requirement of 10 pcs per week; hence requiring a total of 20 pieces of component C per week. Each piece of component C in turn requires 4 pieces of component F according to its BOM; hence requiring a total weekly gross requirement for component F due to component A is: 204 =80 pcs. Adding both gives us a total weekly gross requirement for component F as:80+80=160pcs. References:

•CPIM Part 1 Learning System, Module 4: Inventory Management, Section 4.2: Inventory Management Policies and Objectives

•CPIM Part 2 Learning System, Module 1: Supply Chain Strategy, Section 1.3: Capacity Management

 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.

A reduction in purchased lot sizes means ordering smaller quantities of materials more frequently. This reduces the average inventory level and the carrying cost of inventory. However, it also increases the frequency of orders and the ordering cost. The reorder point (ROP) is the level of inventory that triggers a new order, and it depends on the demand rate, the lead time, and the safety stock. The ROP is not affected by the lot size, unless the demand or the lead time changes. The setup time is the time required to prepare a machine or a process for production, and it is not related to the purchased lot size. References: EXAM CONTENT MANUAL PREVIEW, page 14, section 6.1.2. Manufacturing Planning and Control for Supply Chain Management: The CPIM Reference, Second Edition, page 433, section 12.4.

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

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

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.

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

Maintenance, repair, and operating (MRO) supply systems are essential for ensuring the availability and reliability of equipment and infrastructure used in production processes. MRO supplies include items such as spare parts, tools, lubricants, cleaning materials, and safety equipment. The primary consideration in MRO supply systems typically is stockout costs, which are the costs incurred when an item is not available when needed. Stockouts can cause production delays, equipment breakdowns, customer dissatisfaction, and lost sales opportunities. Therefore, it is important to maintain adequate inventory levels of MRO supplies to avoid stockouts and ensure uninterrupted operations. Order quantity, carrying costs, and shelf life are also important factors in MRO supply systems, but they are not the primary consideration. Order quantity is the amount of MRO supplies ordered at a time, which affects the ordering costs and the inventory levels. Carrying costs are the costs of holding MRO supplies in inventory, which include storage, handling, insurance, and obsolescence costs. Shelf life is the period of time that MRO supplies can be stored before they expire or deteriorate, which affects the inventory turnover and the waste disposal costs. These factors need to be balanced with the stockout costs to optimize the MRO supply systems. References:

CPIM Part 2 Study Guide, Chapter 6: Inventory Management, Section 6.3: Inventory Management for Independent Demand Items

What is maintenance, repair and operations | IBM, Section: Why should you care about MRO?

Maintenance, Repair, and Operations/Overhaul (MRO) - A Complete Guide, Section: Understanding MRO