APICS CPIM CPIM-8.0 New Questions

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.

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

A push system is a production system that operates based on forecasts and schedules, rather than actual customer demand. A push system pushes products to the market regardless of the current demand, and often results in excess inventory and waste. A push system does not consider the capacity constraints of the work centers, and therefore may send work orders to them even if they are not able to process them. This can create bottlenecks, delays, and inefficiencies in the production process12.

The other options are not correct because:

•B. Work centers are scheduled using finite capacity planning. This is not a characteristic of a push system, but rather a pull system. Finite capacity planning is a method of scheduling that takes into account the actual capacity of the work centers, and only releases work orders when there is enough capacity to process them. This reduces the risk of overloading the work centers and improves the flow of production3.

•C. Work centers operate using decentralized control. This is not a characteristic of a push system, but rather a pull system. Decentralized control is a method of management that gives more autonomy and decision-making power to the work centers, and allows them to adjust their production according to the actual demand and capacity. This increases the flexibility and responsiveness of the production system4.

•D. Work centers signal previous work centers when they are ready for more work. This is not a characteristic of a push system, but rather a pull system. This is a common practice in a pull system that uses kanban cards as visual signals to trigger the production or replenishment of a product. The work centers only request more work when they have enough capacity and demand for it, and avoid overproduction and waste5.

References := 1 Push System vs. Pull System: Adopting A Hybrid Approach To MRP1 2 Push Systems vs. Pull System: Definitions and Differences4 3 Finite Capacity Planning - an overview | ScienceDirect Topics 4 Centralized vs. Decentralized Manufacturing | IndustryWeek 5 Kanban - an overview | ScienceDirect Topics

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