Pass the APICS CPIM CPIM-Part-2 Questions and answers with ExamsMirror

The load on a work center is the total time required to complete all the work orders assigned to that work center. The load can be calculated by multiplying the quantity and the run time of each work order, and then adding them up. The formula is:

Load = (Q1 x R1) + (Q2 x R2) + … + (Qn x Rn)

Where Q is the quantity and R is the run time of each work order.

Using the data from the table, we can plug in the values and get:

Load = (10 x 8) + (15 x 9) + (12 x 7.5) + (20 x 10) + (8 x 6.5) = 80 + 135 + 90 + 200 + 52 = 557

Therefore, the load on this work center is 557 hours.

References: CPIM Exam Content Manual Version 7.0, Domain 6: Plan, Manage, and Execute Detailed Schedules, Section 6.3: Monitor Detailed Schedules, Subsection 6.3.2: Describe how to monitor input/output control (I/O) (page 60).

Risk pooling is a strategy to reduce the total safety stock by aggregating the inventory of multiple items or locations. Risk pooling works best for items with high demand uncertainty and long lead times, because these items have higher variability and require more safety stock. By pooling the inventory, the variability of the total demand is reduced, and the safety stock can be lowered without increasing the risk of stockouts. References: CPIM Part 2 Exam Content Manual, Domain 5: Plan and Manage Inventory, Section 5.3: Inventory Management Policies and Objectives, p. 28.

To find the cumulative difference between the required capacity and the available capacity of Months 1 through 37, we need to sum up the differences for each month. The difference for each month is calculated by subtracting the available capacity from the required capacity. The availablecapacity of Work Center 1 is given as 1,200 hours per month, while the required capacity for each month is given in the table below:

The difference for each month is then:

The cumulative difference is the sum of all the differences:

-200 -100 +0 +100 +200 +300 +400 + … +1,700 = 150

 A balanced scorecard is a performance measurement approach that involves linking financial and non-financial performance measures to organizational goals. According to the web search results, a balanced scorecard is a strategic planning and management system that organizations use to communicate what they are trying to accomplish, align the day-to-day work with strategy, prioritize projects, products, and services, and measure and monitor progress towards strategic targets1. A balanced scorecard focuses on four key perspectives: financial, customer, internal business process, and learning and growth2. Each perspective includes objectives, measures, targets, and initiatives that are aligned with the organization’s vision, mission, and strategy3. By using a balanced scorecard, organizations can balance the short-term and long-term objectives, the financial and non-financial outcomes, and the internal and external stakeholders.

Multiple sourcing is an outsourcing approach in which products or services are contracted to various suppliers needed to conduct the business instead of using traditional single sourcing1. One of the potential advantages of multiple sourcing is that it can lower the price of the products or services, as it creates competition among the suppliers and gives the buyer more bargaining power2. Another potential advantage of multiple sourcing is that it can reduce the risk of supply disruptions, as it diversifies the supply chain and makes the buyer less dependent on any single supplier3. If one supplier fails to deliver due to unforeseen circumstances, such as natural disasters, political instability, or quality issues, the buyer can switch to another supplier or use a combination of suppliers to meet the demand4. Therefore, multiple sourcing can provide lower price and reduced risk as potential advantages in the supplier selection process.

References: 1: Multi-Sourcing: Everything You Need To Know - SupplierGATEWAY 3 2: Dual sourcing: Advantages and disadvantages - Hermes Supply Chain Blog 4 3: The Case for Making Multiple Suppliers Part of Your Supply Chain Strategy 5 4: Using Multi-Sourcing to Diversify the Supply Chain 6

 The approved output of the distribution requirements planning (DRP) process is an input to the master production planning (MPS) process. The DRP process determines the quantity and timing of finished goods to be delivered to each distribution center or warehouse to meet customer demand1. The output of the DRP process is a distribution schedule that specifies the planned delivery dates and quantities of products2. The distribution schedule is then used as an input to the MPS process, which determines the quantity and timing of end items to be produced at each manufacturing facility3. The MPS process balances the demand from the distribution schedule with the available capacity and resources of the production system3. The output of the MPS process is a master production schedule that specifies the planned production dates and quantities of end items3.

References: CPIM Part 2 Exam Content Manual, Domain 4: Plan and Manage Supply, Section 4.1: Supply Management Concepts and Tools, p. 33-34.

A fishbone diagram, also known as a cause-and-effect diagram or an Ishikawa diagram, is a tool for identifying and analyzing the possible causes of a problem or an effect. It is often used in quality management to find the root causes of defects or errors. A fishbone diagram has a main branch that represents the problem or effect, and several sub-branches that represent the categories of causes, such as people, processes, equipment, materials, environment, etc. Each category can have further sub-branches that represent more specific causes. A fishbone diagram would help a service organization determine the source of a quality-of-service issue by allowing them to visualize and organize the potential factors that contribute to the problem and identify the most likely cause. References: CPIM Part 2 Exam Content Manual, Domain 8: Manage Quality, Continuous Improvement, and Technology, Section 8.1: Quality Management Concepts and Tools, p. 59-60.

Option overplanning is a technique used in an assemble-to-order (ATO) environment to address uncertainty in the product mix. An ATO environment is a production strategy where products are assembled from components or subassemblies after receiving customer orders1. Option overplanning is the practice of planning and stocking more components or subassemblies than the expected demand, based on historical data or forecasts2. The purpose of option overplanning is to increase the flexibility and responsiveness of the production system, by allowing the manufacturer to meet a variety of customer orders with different options or features. Option overplanning can help reduce the risk of stockouts, improve customer service, and capture new market opportunities.

Option overplanning is not used to verify appropriate inventory levels, schedule detailed production, or compensate for forecast bias. Verifying appropriate inventory levels is a function of inventory management, which involves monitoring and controlling the quantity and quality of materials and products in stock. Scheduling detailed production is a function of detailed scheduling, which involves allocating resources and setting priorities for specific tasks or orders in the production process. Compensating for forecast bias is a function of demand management, which involves adjusting the forecasts based on the difference between the actual and predicted demand.

References: Assemble-to-Order (ATO): Overview, Examples, Pros and Cons - Investopedia; Assemble-to-Order - Overview, How It Works, Advantages; [Assemble-to-Order (ATO) Definition | Operations & Supply Chain Dictionary]; [Assemble-to-Order (ATO) - MBA Skool-Study.Learn.Share.]; [InventoryManagement - Definition, Types, Objectives and Examples]; [Detailed Scheduling - an overview | ScienceDirect Topics]; [Forecast Bias - an overview | ScienceDirect Topics].

 Process improvement is a method of analyzing and enhancing the production methods and techniques to increase productivity and performance. Process improvement aims to reduce costs, waste, defects, and errors, as well as to improve quality, efficiency, and customer satisfaction. When considering process improvement, the first approach that should be considered is making better use of existing resources. This means that the production system should optimize the utilization andallocation of the available resources, such as materials, labor, machines, and space. This can be achieved by implementing various techniques, such as lean manufacturing, six sigma, kaizen, or 5S. Making better use of existing resources can help to improve the process without requiring additional investment or expenditure.

The other options are not the first approaches that should be considered as part of process improvement. Hiring more skilled people to perform the job is not the first approach, as it may increase the labor cost and require more training and supervision. Hiring more skilled people may not necessarily improve the process if the existing methods and techniques are inefficient or ineffective. Buying better and faster equipment is not the first approach, as it may involve a large capital outlay and a long payback period. Buying better and faster equipment may not necessarily improve the process if the existing resources are underutilized or misallocated. Applying stricter quality control is not the first approach, as it may increase the inspection and testing cost and time. Applying stricter quality control may not necessarily improve the process if the existing methods and techniques are prone to errors or defects. References: CPIM Exam Content Manual Version 7.0, Domain 8: Manage Quality, Continuous Improvement, and Technology, Section 8.2: Continuous Improvement Concepts, p. 46; Process Improvement; Process Improvement Definition.

Full pegging is a method of tracing the relationship between supply and demand in a manufacturing system. Full pegging shows the link between each demand and its corresponding supply, as well as the link between each demand and the highest-level order that triggered it. Full pegging helps to identify the impact of changes in demand or supply on the production plan, and to make adjustments accordingly. Full pegging is most beneficial in an assemble-to-order (ATO) environment, where products are customized by assembling standardized components or modules according to customer specifications. In an ATO environment, full pegging can show the connection between the finished products, the components or modules, and the customer orders. This can help to optimize the inventory level, reduce lead time, and improve customer service.

Full pegging is not very useful in the other production environments. Distribute-to-order is a production strategy that delivers finished products from inventory to customers based on their orders. There is no customization or assembly involved in this strategy, so full pegging is not needed. Make-to-order is a production strategy that produces customized products from raw materials or components after receiving customer orders. There is no standardization ormodularization involved in this strategy, so full pegging is not applicable. Make-to-stock is a production strategy that produces standardized products in advance of customer demand, and stores them in inventory until they are sold. There is no customization or assembly involved in this strategy, so full pegging is not relevant. References: CPIM Exam Content Manual Version 7.0, Domain 4: Plan and Manage Supply, Section 4.1: Supply Planning Concepts, p. 23; Full Pegging; Assemble to order.