APICS CPIM-Part-2 Practice Test - Questions Answers, Page 4

A3 method is a tool that can be used in a root cause corrective action process to determine the problem of a machine that is suddenly having excessive downtime.A3 method is a structured problem-solving approach that follows the Plan-Do-Check-Act (PDCA) cycle and uses a single sheet of paper (A3 size) to document the problem, analysis, countermeasures, and results1.A3 method can help identify the root cause of a problem by using tools such as the 5 Whys or the fishbone diagram, and then develop and implement effective corrective actions to prevent recurrence2.A3 method can also help communicate the problem and the solution to stakeholders, as well as monitor and evaluate the outcomes3.

The steps of the A3 method are4:

Step 1: Define the problem and its impact. Describe the current situation, the gap between the actual and the desired state, and the scope and magnitude of the problem.

Step 2: Identify the root cause of the problem. Use tools such as the 5 Whys or the fishbone diagram to analyze the factors that contribute to the problem and drill down to its root cause.

Step 3: Propose countermeasures to address the root cause. Generate possible solutions that can eliminate or reduce the root cause, and evaluate their feasibility, effectiveness, and costs.

Step 4: Implement countermeasures. Select the best solution and plan how to execute it. Define the roles, responsibilities, resources, timeline, and expected outcomes of the implementation.

Step 5: Check results and process. Measure and compare the results before and after the implementation, and verify if the problem has been solved or improved. Also check if the process has been followed correctly and document any deviations or issues.

Step 6: Standardize successful processes or identify unresolved issues. If the results are satisfactory, standardize the new process and ensure that it is sustained. If not, identify the remaining or new issues and repeat the A3 method.

Therefore, A3 method is a tool that can be used in a root cause corrective action process to determine the problem of a machine that is suddenly having excessive downtime.

Pareto analysis is a technique that a group can use to prioritize problems.Pareto analysis is based on the Pareto principle, also known as the 80/20 rule, which states that 80% of the effects come from 20% of the causes1.Pareto analysis can help a group identify and focus on the most significant problems that account for the majority of the negative outcomes, and allocate their resources and efforts accordingly2.

The steps of Pareto analysis are3:

Step 1: Define the problem and its scope. Clarify what the problem is, why it is important, and what are the desired outcomes.

Step 2: Identify the causes of the problem. Brainstorm and list all the possible factors that contribute to the problem, such as people, processes, equipment, materials, environment, etc.

Step 3: Collect data on the causes. Gather quantitative or qualitative data on how often or how much each cause affects the problem, such as frequency, severity, cost, time, etc.

Step 4: Analyze the data using a Pareto chart. A Pareto chart is a type of bar chart that shows the frequency or impact of each cause in descending order, along with a cumulative line that shows the percentage of the total effect. A Pareto chart can help visualize which causes are more significant than others, and where the 80/20 split occurs.

Step 5: Prioritize the causes and take action. Based on the Pareto chart, select the most critical causes that need to be addressed first, and develop and implement solutions to eliminate or reduce them. Monitor and evaluate the results and repeat the process if necessary.

Therefore, Pareto analysis is a technique that a group can use to prioritize problems by identifying and focusing on the most significant causes that account for the majority of the negative outcomes.

One of the trade-offs that should be evaluated when determining where to place inventory in a multi-echelon supply chain network is the transportation cost and delivery time.A multi-echelon supply chain network is a system of interconnected stages or echelons that perform different functions, such as production, distribution, and retailing, to deliver products or services to the end customers1.Inventory placement is the decision of how much and where to hold inventory in the supply chain network to balance the costs and service levels2.

Transportation cost is the expense of moving products or materials from one echelon to another in the supply chain network.Transportation cost depends on factors such as distance, mode, volume, weight, fuel, and tariffs3. Delivery time is the duration of moving products or materials from one echelon to another in the supply chain network.Delivery time depends on factors such as speed, reliability, frequency, and congestion3.

There is a trade-off between transportation cost and delivery time when determining where to place inventory in a multi-echelon supply chain network.Generally, holding more inventory closer to the customers can reduce the delivery time and increase the service level, but it can also increase the transportation cost and the inventory holding cost4.On the other hand, holding less inventory farther from the customers can reduce the transportation cost and the inventory holding cost, but it can also increase the delivery time and decrease the service level4. Therefore, finding the optimal inventory placement requires balancing the transportation cost and delivery time trade-off.

Some of the methods or tools that can help evaluate the transportation cost and delivery time trade-off are:

Network optimization: a technique that uses mathematical models to optimize the design and configuration of a supply chain network by minimizing the total costs (including transportation and inventory costs) while satisfying the service level requirements.

Multi-echelon inventory optimization: a technique that uses mathematical models to optimize the allocation and sizing of safety stocks across multiple echelons of a supply chain network by minimizing the total costs (including transportation and inventory costs) while satisfying the service level requirements.

Simulation: a technique that uses computer software to mimic the behavior and performance of a supply chain network under different scenarios and assumptions. Simulation can help evaluate the impact of different inventory placement strategies on the transportation cost and delivery time.

Therefore, transportation cost and delivery time is one of the trade-offs that should be evaluated when determining where to place inventory in a multi-echelon supply chain network.

A bill of resources is a tool that is used to evaluate the impact that a production plan has on capacity.A bill of resources is a document that lists the required resources, such as machines, labor, materials, and space, for each product or service in the production plan1.A bill of resources can help estimate the total capacity requirements for the production plan, as well as the capacity utilization and availability for each resource2.A bill of resources can also help identify potential capacity gaps, bottlenecks, or excesses, and evaluate alternative production plans or resource allocations3.

A bill of resources can be created by using the following steps4:

Step 1: Identify the products or services in the production plan and their quantities and timings.

Step 2: Identify the resources needed for each product or service and their quantities and timings. This can be done by using tools such as product routings, process maps, or work breakdown structures.

Step 3: Aggregate the resource requirements for each product or service and for the entire production plan. This can be done by using tools such as spreadsheets, tables, or charts.

Step 4: Compare the resource requirements with the resource capacities and availability. This can be done by using tools such as capacity planning matrices, load profiles, or resource histograms.

Step 5: Analyze the results and make adjustments or recommendations. This can be done by using tools such as what-if analysis, simulation, or optimization.

Therefore, a bill of resources is a tool that is used to evaluate the impact that a production plan has on capacity.

Establishment of goals and baselines prior to entering the plan-do-check-act (PDCA) cycle allows improvement teams to determine whether an effective change was made in the process.Goals are the desired outcomes or targets that the improvement teams want to achieve by implementing changes in the process1.Baselines are the current or initial performance levels of the process before implementing any changes2. By establishing goals and baselines, improvement teams can have a clear direction and a reference point for their improvement efforts.

In the PDCA cycle, improvement teams follow four steps: plan, do, check, and act. In the plan step, they define the problem, analyze the root cause, and propose countermeasures. In the do step, they test the countermeasures on a small scale. In the check step, they measure and evaluate the results of the test and compare them with the goals and baselines.In the act step, they standardize and sustain the successful countermeasures or revise and repeat the cycle if needed3.

By comparing the results with the goals and baselines in the check step, improvement teams can determine whether an effective change was made in the process.An effective change is one that improves the performance of the process and meets or exceeds the goals set by the improvement teams4. If the results show that an effective change was made, improvement teams can move to the act step and implement the change on a larger scale.If not, improvement teams can go back to the plan step and identify new or revised countermeasures5.

Therefore, establishment of goals and baselines prior to entering the PDCA cycle allows improvement teams to determine whether an effective change was made in the process.

Manufacturing flexibility can be measured by using changeover time.Changeover time is the time it takes to go from the last good part of one product run to the first good part of the next product run1.Manufacturing flexibility is the ability of a system to handle a range of products or variants with fast setups2.By using changeover time as a measure of manufacturing flexibility, we can assess how quickly and efficiently a system can switch from one product to another, and how well it can respond to changes in customer demand, product mix, quality standards, and delivery schedules3.

Some of the benefits of reducing changeover time and increasing manufacturing flexibility are4:

Lower manufacturing costs: More value-added capacity can be unlocked because the equipment is idle for less time.

Higher customer satisfaction: Customers can get their products faster and with more variety.

Greater competitive advantage: The system can adapt to market changes and offer more customized products or services.

Improved quality and productivity: The system can avoid defects, waste, and errors that may occur during long or complex changeovers.

Some of the methods or tools that can help reduce changeover time and increase manufacturing flexibility are5:

Single-minute exchange of die (SMED): A technique that aims to reduce changeover time to less than 10 minutes by converting internal setup activities (those that can only be done when the machine is stopped) to external setup activities (those that can be done while the machine is running), and streamlining both types of activities.

Total productive maintenance (TPM): A technique that involves maintaining and improving the equipment performance and reliability by involving all employees in preventive maintenance, autonomous maintenance, focused improvement, and quality management.

Quick response manufacturing (QRM): A technique that focuses on reducing lead times throughout the entire organization by applying the principles of time-based competition, cellular manufacturing, system dynamics, and enterprise-wide application.

Therefore, changeover time is a measure that can be used to evaluate the manufacturing flexibility of a system.

Exponential smoothing is a forecasting technique that uses a weighted average of past and present data to predict future values. It is suitable for time series data that have a stable or slowly changing trend and no significant seasonal variations. Exponential smoothing assigns more weight to the most recent data, giving it a higher influence on the forecast. This makes it more responsive to changes in demand patterns than other techniques, such as moving average or time series decomposition, which use fixed weights or historical data. The Delphi method is a qualitative technique that involves a panel of experts who provide their opinions and feedback on a topic through multiple rounds of surveys. It is not based on historical data or mathematical formulas, but rather on human judgment and consensus. Therefore, it is not appropriate for developing a forecast.Reference: CPIM Part 2 Exam Content Manual, Version 7.0, Domain 3: Plan and Manage Demand, Section A: Demand Management, Subsection 2: Forecasting Techniques and Methods, p. 14-15.