CPIM-8.0 Exam Dumps - APICS CPIM Questions and Answers

Excess capacity is the amount of capacity that is available beyond the normal or expected demand. Safety stock is the inventory that is held to protect against uncertainties in demand, supply, or lead time. Excess capacity can be a good substitute for safety stock when the cost of excess capacity is less than the cost of an additional unit of safety stock in the same period. This means that the opportunity cost of having idle resources is lower than the carrying cost of holding extra inventory. In this case, excess capacity can be used to produce more units in response to demand fluctuations, rather than relying on safety stock to meet customer orders. 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]

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

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)

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

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

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

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.