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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 economic order quantity (EOQ) model is a formula that calculates the optimal order quantity that minimizes the total inventory costs, such as ordering costs and holding costs. The EOQ model is based on several assumptions, one of which is that the order preparation costs and inventory-carrying costs are constant and known. This means that the costs of placing and receiving an order, and the costs of storing and maintaining the inventory, do not change with the order quantity or the inventory level, and that they can be estimated accurately12.

The other options are not correct because:

•A. Customer demand is known but seasonal. This is not an assumption of the EOQ model, but rather a violation of it. The EOQ model assumes that the customer demand is constant and known, and that the orders are placed at regular intervals. However, if the customer demand is seasonal, it means that it varies over time and may not be predictable. This can affect the accuracy and applicability of the EOQ model, as the optimal order quantity may change with the demand pattern12.

•B. Items are purchased and/or produced continuously and not in batches. This is not an assumption of the EOQ model, but rather a contradiction of it. The EOQ model assumes that the items are purchased and/or produced in batches, and that the inventory level decreases gradually until it reaches zero, at which point a new order is placed and received. However, if the items are purchased and/or produced continuously, it means that there is no need to place orders or maintain inventory, and the EOQ model becomes irrelevant12.

•D. Holding costs, as a percentage of the unit cost, are variable. This is not an assumption of the EOQ model, but rather a complication of it. The EOQ model assumes that the holding costs, as a percentage of the unit cost, are constant and known. This means that the cost of storing and maintaining one unit of inventory does not depend on the unit cost of the item, and that it can be estimated accurately. However, if the holding costs, as a percentage of the unit cost, are variable, it means that the cost of storing and maintaining one unit of inventory changes with the unit cost of the item, and that it may not be easy to estimate. This can affect the accuracy and applicability of the EOQ model, as the optimal order quantity may depend on the unit cost of the item12.

References := 1 Economic Order Quantity Model in Inventory Management - Investopedia1 2 Economic Order Quantity: What Does It Mean and Who Is It Important For? - Investopedia2

Level production planning is a strategy that maintains a constant output rate, production rate, or workforce level over the planning horizon. It is suitable for products with stable demand or seasonal demand that can be smoothed by using inventory or backorders. Level production planning can help reduce labor costs, hiring and firing costs, and overtime costs. However, it may also result in high inventory costs or customer dissatisfaction due to long lead times or stockouts. To overcome these drawbacks, the company can investigate subcontracting to meet the extra demand during the peak season. Subcontracting is the process of outsourcing some or all of the production to another firm. It can help the company increase its capacity, flexibility, and responsiveness without investing in additional facilities or equipment. Subcontracting can also reduce the risk of obsolescence or spoilage of seasonal products.

Option B is not appropriate, because chase production planning is a strategy that adjusts the production rate to match the demand rate over the planning horizon. It is suitable for products with highly variable or uncertain demand that cannot be smoothed by using inventory or backorders. Chase production planning can help minimize inventory costs and avoid overproduction or underproduction. However, it may also result in high labor costs, hiring and firing costs, and overtime costs. Moreover, it may limit the company’s ability to capture the market share and satisfy the customer demand during the high demand season.

Option C is not appropriate, because hybrid production planning is a strategy that combines the features of level production planning and chase production planning. It is suitable for products with moderate variability or uncertainty in demand that can be partially smoothed by using inventory or backorders. Hybrid production planning can help balance the trade-offs between inventory costs and labor costs. However, it may also increase the complexity and difficulty of coordinating the production and demand plans. Moreover, it may not address the company’s financial constraints or capacity limitations.

Option D is not appropriate, because reducing the size of the customer base during the high demand season is a risky and counterproductive move. It may result in losing loyal customers, damaging the company’s reputation, and forfeiting potential profits. It may also create an opportunity for competitors to gain market share and customer loyalty.

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

Safety stock is the extra inventory that a company keeps to prevent stockouts or shortages due to uncertainties in demand, supply, or lead time. Safety stock acts as a buffer to protect the company from losing sales or disrupting operations. One of the factors that is used to determine safety stock is the forecast error distribution, which is the measure of how much the actual demand deviates from the forecasted demand. Forecast error distribution can be calculated by using statistical methods, such as standard deviation or mean absolute deviation, to find the average and the variability of the forecast errors. The higher the forecast error distribution, the more safety stock is needed to cover the potential demand fluctuations. Forecast error distribution is one of the components of the safety stock formula, which is:

Safety stock = Z x ∑LT x D

Where:

Z refers to the service level factor, which is the desired probability of not having a stockout.

∑LT refers to the standard deviation of lead time, which is the average variability of the time it takes to replenish inventory.

D is the average demand per unit of time.

References := CPIM Part 2 Exam Content Manual, Version 8.0, ASCM, 2021, p. 24. CPIM Part 2 Learning System, Version 8.0, Module 2, Section C, Topic 3. How To Calculate Safety Stock (With Examples and FAQs). What is Safety Stock? (Definition, Formulas, Best Practices).

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