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APICS CPIM-8.0 Exam
Certified in Planning and Inventory Management (CPIM 8.0) (Page 5 )

Updated On: 1-Feb-2026
Page 5 of 31
PDF with 150 Questions

In which of the following situations would you use an X-bar chart?

  1. Track the number of defects that are found in each unit.
  2. Measure the difference between the largest and the smallest in a sample.
  3. Determine the average value of a group of units.
  4. Estimate a subgroup variation.

Answer(s): C

Explanation:

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.


Reference:

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



Which of the following statements best characterizes enterprise resources planning (ERP) systems?

  1. They track activity from customer order through payment.
  2. They are expensive but easy to implement.
  3. They provide real-time planning and scheduling, decision support, available-to-promise (ATP), and capable-to-promise (CTP) capabilities.
  4. They are used for strategic reporting requirements.

Answer(s): C

Explanation:

Enterprise resource planning (ERP) systems are software platforms that help organizations manage and integrate the essential parts of their businesses, such as finance, supply chain, operations, human resources, and more. ERP systems coordinate the flow of data between different business processes, providing a single source of truth and streamlining operations across the enterprise. ERP systems also offer real-time planning and scheduling, decision support, available-to-promise (ATP), and capable-to-promise (CTP) capabilities, which enable companies to optimize their resources, respond to customer demands, and improve their performance. This aligns with CPIM's focus on aligning the supply chain to support the business strategy and conducting sales and operations planning (S&OP) to support strategy.


Reference:

The concepts are covered in detail in Module 1:
Business Planning and Strategy (1 and Module 2: Demand Management (2. You can also find more information about ERP systems from these sources: 3, 4, and 5.



Management should support investments in new process technologies that:

  1. require minimal changes in existing systems, procedures, and skills.
  2. have been recommended by technical experts and equipment suppliers.
  3. provide significant cost-reduction opportunities for the company's current products.
  4. provide long-term competitive advantage with acceptable financial risk.

Answer(s): D

Explanation:

Management should support investments in new process technologies that align with the strategic objectives of the organization and provide a sustainable competitive advantage in the market. New process technologies may involve changes in existing systems, procedures, and skills, but these changes should be justified by the potential benefits and risks of the investment. Therefore, option D is correct. Option A is incorrect because requiring minimal changes in existing systems, procedures, and skills is not a sufficient criterion for investing in new process technologies. Option B is incorrect because relying on the recommendations of technical experts and equipment suppliers may not reflect the best interests of the organization or its customers. Option C is incorrect because providing significant cost-reduction opportunities for the company's current products may not be enough to justify the investment in new process technologies, especially if the products have a short life cycle or low demand.


Reference:

CPIM Part 2 Exam Content Manual, Version 8.0, Section H: Quality, Continuous Improvement, and Technology, Subsection H.3: Technology, p. 85.



If fixed costs are §200,000 and 20,000 units are produced, a unit's fixed cost is §10. This is an example of:

  1. variable costing.
  2. activity-based costing (ABC).
  3. absorption costing.
  4. overhead costing.

Answer(s): C

Explanation:

Absorption costing is a method of allocating all manufacturing costs to the units produced. It includes both fixed and variable costs in the calculation of the unit cost. In this example, the fixed cost per unit is §10, which is obtained by dividing the total fixed cost of §200,000 by the number of units produced (20,000). This fixed cost per unit is then added to the variable cost per unit to get the total unit cost under absorption costing. Variable costing, on the other hand, only assigns variable costs to the units produced and treats fixed costs as period costs. Activity-based costing (ABC) is a method of allocating overhead costs to products or services based on the activities they consume. Overhead costing is a general term that refers to any method of assigning overhead costs to products or services.


Reference:

CPIM Part 2 Learning System, Module 2: Demand Management, Section 2.4: Costing Methods and Cost Behavior
CPIM Part 2 Learning System, Module 3: Supply, Section 3.5: Cost Management



A company with stable demand that uses exponential smoothing to forecast demand would typically use a:

  1. low alpha value.
  2. low beta value.
  3. high beta value.
  4. high alpha value.

Answer(s): A

Explanation:

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 () and beta ():
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.


Reference:

[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



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