APICS CPIM-Part-2 Practice Test - Questions Answers, Page 8

Providing a realistic basis for setting internal performance targets can be accomplished through benchmarking. Benchmarking is a process of comparing one's own performance, processes, or practices with those of other organizations that are recognized as leaders or best in class in a specific area. Benchmarking can help identify gaps, strengths, weaknesses, opportunities, and threats in one's own performance, as well as learn from the experiences and successes of others. Benchmarking can also help set realistic, achievable, and challenging goals and targets for improvement, based on external standards or benchmarks. Benchmarking can be done internally (within the same organization), externally (with other organizations in the same industry or sector), or functionally (with other organizations that perform similar functions or processes).

Beta testing is not a way of providing a realistic basis for setting internal performance targets. Beta testing is a stage of product development where a sample of potential users or customers test a product or service before it is released to the general public. Beta testing can help identify and fix any bugs, errors, or issues in the product or service, as well as collect feedback and suggestions for improvement. Beta testing can also help evaluate the usability, functionality, and quality of the product or service, as well as measure customer satisfaction and loyalty. Beta testing is not related to setting internal performance targets, as it is focused on the product or service, not the organization.

Breakthrough innovation is not a way of providing a realistic basis for setting internal performance targets. Breakthrough innovation is a type of innovation that creates significant value for customers and markets by introducing new products, services, or business models that are radically different from existing ones. Breakthrough innovation can help create competitive advantage, disrupt existing markets, or create new markets. Breakthrough innovation is not related to setting internal performance targets, as it is focused on the outcome, not the process.

Best practices are not a way of providing a realistic basis for setting internal performance targets. Best practices are methods or techniques that have been proven to be effective and efficient in achieving desired results or outcomes. Best practices can be derived from one's own experience, research, or benchmarking. Best practices can help improve performance, quality, or productivity by adopting proven solutions or standards. Best practices are not related to setting internal performance targets, as they are focused on the implementation, not the measurement.

The priority rule that is most consistent with the objective of meeting due dates is slack time per operation. Slack time per operation is a priority rule that assigns a priority index to each job based on the ratio of the remaining slack time to the remaining number of operations. Slack time is the difference between the due date and the expected completion time of a job. A lower ratio means a higher priority, as it indicates that the job has less slack time per operation and is more likely to be late. Slack time per operation is a dynamic priority rule, as it updates the priority index after each operation is completed. Slack time per operation can help minimize the number of tardy jobs and the average tardiness of jobs, as it gives preference to the jobs that are closer to their due dates and have more operations left.

First-come-first-served (FCFS) is not a priority rule that is consistent with the objective of meeting due dates. FCFS is a priority rule that processes jobs in the order of their arrival or release times. FCFS is a simple and fair rule, but it ignores the processing times and due dates of jobs. FCFS can result in poor due date performance, as it can delay urgent or short jobs behind long or non-urgent jobs.

Shortest processing time (SPT) is not a priority rule that is consistent with the objective of meeting due dates. SPT is a priority rule that processes jobs in ascending order of their processing times. SPT is an effective rule for minimizing the average flow time and work-in-process inventory of jobs, as it clears out small jobs quickly and reduces congestion in the system. However, SPT does not consider the due dates of jobs, and it can make long or urgent jobs late.

Fewest operations remaining is not a priority rule that is consistent with the objective of meeting due dates. Fewest operations remaining is a priority rule that processes jobs in ascending order of their remaining number of operations. Fewest operations remaining is a rule that can reduce the variability and complexity of jobs, as it tends to complete jobs faster and reduce their flow times. However, fewest operations remaining does not take into account the slack times or due dates of jobs, and it can make urgent or short jobs late.

When a certified supplier's delivery performance declines, a company should respond initially by communicating with the supplier to investigate the source of the problem. A certified supplier is a supplier that has met certain quality, delivery, and service standards and has been approved by the company to supply goods or services without inspection or testing. A certified supplier is expected to maintain a high level of performance and reliability, as well as to report any issues or deviations that may affect the delivery process. However, sometimes a certified supplier may experience a decline in delivery performance, which can cause delays, disruptions, or dissatisfaction for the company and its customers.

The best way to deal with a decline in delivery performance from a certified supplier is to communicate with the supplier and find out the root cause of the problem. Communication is essential for maintaining a good relationship with the supplier and for resolving any issues or conflicts that may arise. Communication can help the company and the supplier to understand each other's expectations, needs, and challenges, as well as to identify and implement corrective actions or preventive measures. Communication can also help to restore trust and confidence between the parties and to prevent further deterioration of performance.

Tightening performance criteria for the supplier is not an appropriate initial response when a certified supplier's delivery performance declines. Tightening performance criteria means imposing stricter standards or requirements on the supplier, such as reducing lead times, increasing penalties, or demanding more frequent reports. Tightening performance criteria may seem like a way of holding the supplier accountable and motivating them to improve their performance, but it can also have negative consequences. Tightening performance criteria can create more pressure and stress for the supplier, which can affect their quality, productivity, or morale. It can also damage the relationship with the supplier, as it may signal a lack of trust, respect, or cooperation from the company.

Establishing a temporary buffer of finished goods inventory at the supplier is not an effective initial response when a certified supplier's delivery performance declines. Establishing a temporary buffer of finished goods inventory means storing extra units of products at the supplier's location to compensate for any delays or shortages in delivery. Establishing a temporary buffer of finished goods inventory may seem like a way of ensuring availability and continuity of supply, but it can also have drawbacks. Establishing a temporary buffer of finished goods inventory can increase inventory costs, such as holding costs, transportation costs, or obsolescence costs. It can also reduce inventory visibility and control, as it may be difficult to track or manage the inventory at the supplier's location. Moreover, establishing a temporary buffer of finished goods inventory does not address the root cause of the decline in delivery performance, but rather masks or postpones it.

Increasing the standard lead time of the component to allow for supplier delays is not a suitable initial response when a certified supplier's delivery performance declines. Increasing the standard lead time of the component means extending the time between placing an order and receiving it from the supplier. Increasing the standard lead time of the component may seem like a way of adjusting to the decline in delivery performance and avoiding late deliveries, but it can also have disadvantages. Increasing the standard lead time of the component can reduce customer satisfaction and loyalty, as it may result in longer waiting times or missed deadlines for the customers. It can also reduce operational efficiency and flexibility, as it may limit the ability to respond to changes in demand or supply. Furthermore, increasing the standard lead time of the component does not solve the problem of the decline in delivery performance, but rather accepts or tolerates it.

A company's process technology and equipment should be characterized by product-independent processes and flexible automation if its competitive business strategy is based on offering customized products or features and a rapid response to market shifts. Product-independent processes are processes that can produce a variety of products or features without requiring major changes or adjustments in the production system. Flexible automation is a type of automation that can adapt to different product specifications or volumes by using programmable or reconfigurable machines, robots, or software. Product-independent processes and flexible automation can enable a company to offer customized products or features and a rapid response to market shifts by allowing it to:

Produce small batches or single units of products or features that meet specific customer needs or preferences.

Switch quickly and easily between different products or features without losing time or efficiency.

Incorporate new technologies, materials, or designs into the production system without disrupting the existing operations.

Respond to changes in demand or supply by adjusting the production capacity or output accordingly.

Continuous flow processes and a high degree of fixed automation are not suitable for a company's process technology and equipment if its competitive business strategy is based on offering customized products or features and a rapid response to market shifts. Continuous flow processes are processes that produce products or features in a continuous and uninterrupted manner, without any breaks or buffers between the stages. Fixed automation is a type of automation that uses specialized machines or equipment that are designed to perform a specific task or operation. Continuous flow processes and fixed automation can enable a company to achieve high efficiency, productivity, and quality, but they also have some limitations, such as:

They are suitable for producing large volumes of standardized products or features that have stable and predictable demand.

They are difficult and costly to modify or change when there is a need to produce different products or features or to incorporate new technologies, materials, or designs.

They are inflexible and rigid when there are variations or fluctuations in demand or supply, as they cannot adjust the production capacity or output easily.

Product-independent processes with parallel production lines are not appropriate for a company's process technology and equipment if its competitive business strategy is based on offering customized products or features and a rapid response to market shifts. Product-independent processes with parallel production lines are processes that use multiple identical machines or equipment that can produce the same product or feature simultaneously. Product-independent processes with parallel production lines can enable a company to increase its production capacity and output, but they also have some drawbacks, such as:

They are suitable for producing high volumes of standardized products or features that have high and constant demand.

They are inefficient and wasteful when there is a need to produce different products or features or to incorporate new technologies, materials, or designs, as they require duplication of resources and equipment.

They are redundant and unnecessary when there are variations or fluctuations in demand or supply, as they create excess inventory or idle capacity.

Product-dependent processes and automation based on product volume are not optimal for a company's process technology and equipment if its competitive business strategy is based on offering customized products or features and a rapid response to market shifts. Product-dependent processes are processes that can produce only one type of product or feature, or that require significant changes or adjustments in the production system to produce different products or features. Automation based on product volume is a type of automation that uses different machines or equipment depending on the volume of production required for each product or feature. Product-dependent processes and automation based on product volume can enable a company to optimize its production costs and quality, but they also have some disadvantages, such as:

They are suitable for producing low volumes of specialized products or features that have low variability and uncertainty in demand.

They are complex and time-consuming when there is a need to produce different products or features or to incorporate new technologies, materials, or designs, as they require frequent changes or setups in the production system.

They are unresponsive and slow when there are variations or fluctuations in demand or supply, as they cannot adapt the production capacity or output quickly.

The measurement that indicates there may be bias in the forecast model is the tracking signal. The tracking signal is a ratio of the cumulative forecast error to the mean absolute deviation (MAD). The cumulative forecast error is the sum of the differences between the forecasted and actual values over a period of time. The MAD is the average of the absolute values of the forecast errors. The tracking signal can help detect and measure the bias of a forecast model by comparing the magnitude and direction of the forecast errors. A positive tracking signal indicates that the forecast model is consistently over-forecasting, while a negative tracking signal indicates that the forecast model is consistently under-forecasting. A zero tracking signal indicates that there is no bias in the forecast model. A rule of thumb is that if the tracking signal exceeds a certain threshold, such as 4, then there is a significant bias in the forecast model that needs to be corrected.

The other measurements do not indicate bias in the forecast model, but rather other aspects of the forecast accuracy or variability. The MAD is a measure of the average error or deviation of the forecast model from the actual values. The MAD does not indicate bias, as it does not consider the direction or sign of the errors. A low MAD indicates a high accuracy of the forecast model, while a high MAD indicates a low accuracy of the forecast model.

The standard deviation is a measure of the dispersion or variation of the forecast errors around their mean. The standard deviation does not indicate bias, as it does not consider the direction or sign of the errors. A low standard deviation indicates a low variability or uncertainty of the forecast model, while a high standard deviation indicates a high variability or uncertainty of the forecast model.

The variance is a measure of the squared deviation or dispersion of the forecast errors around their mean. The variance does not indicate bias, as it does not consider the direction or sign of the errors. The variance is related to the standard deviation, as it is equal to the square of the standard deviation. A low variance indicates a low variability or uncertainty of the forecast model, while a high variance indicates a high variability or uncertainty of the forecast model.

The results from responding to uncertainty in the supply chain by exaggerating lead times and increasing lot sizes is called the bullwhip effect. The bullwhip effect is a phenomenon that occurs when small changes in demand at the downstream end of the supply chain (such as retailers or customers) cause larger and larger fluctuations in demand at the upstream end of the supply chain (such as wholesalers, distributors, or manufacturers). The bullwhip effect can create inefficiencies, waste, and costs in the supply chain, as well as reduce customer satisfaction and profitability.

One of the causes of the bullwhip effect is the response to uncertainty in the supply chain by exaggerating lead times and increasing lot sizes. Lead time is the time between placing an order and receiving it from a supplier. Lot size is the quantity of units ordered or produced at a time. When there is uncertainty or variability in demand or supply, such as due to seasonality, promotions, disruptions, or forecasting errors, some supply chain members may try to cope by exaggerating lead times and increasing lot sizes. For example, a retailer may increase its safety stock or reorder point to avoid stockouts or delays, or a manufacturer may produce more than needed to take advantage of economies of scale or discounts. However, these actions can have unintended consequences, as they can distort the demand information and amplify the demand variability along the supply chain. This can result in excess inventory, low inventory turnover, high holding costs, poor service levels, lost sales, obsolete products, or capacity issues.

To prevent or reduce the bullwhip effect caused by responding to uncertainty in the supply chain by exaggerating lead times and increasing lot sizes, some possible solutions are:

Improving communication and collaboration among supply chain members to share accurate and timely demand information and forecasts.

Reducing lead times and lot sizes by using lean production techniques, just-in-time inventory systems, or quick response methods.

Implementing vendor-managed inventory (VMI) systems, where suppliers are responsible for managing and replenishing the inventory of their customers based on their actual consumption data.

Adopting advanced technologies, such as radio-frequency identification (RFID), artificial intelligence (AI), or blockchain, to enhance visibility, traceability, and coordination in the supply chain.

The capacity requirements plan is used primarily to balance capacity and load at work centers. A work center is a location where one or more resources perform a specific operation or a group of operations. Capacity is the amount of time or output that a work center can offer for production activities. Load is the amount of time or output that a work center is required to produce based on the planned production schedule. Balancing capacity and load means matching the available capacity with the required load, so that there is no excess or shortage of capacity at any work center.

The capacity requirements plan is a report that shows the projected load and capacity of each work center over a planning horizon. It is derived from the master production schedule (MPS), which specifies the quantity and timing of finished goods to be produced, and the bill of materials (BOM), which specifies the components and materials needed for each finished good. The capacity requirements plan also uses the routing file, which specifies the sequence of operations and work centers required for each finished good, and the work center file, which specifies the capacity and availability of each work center. The capacity requirements plan can help to identify any gaps or surpluses in capacity at each work center and to take corrective actions, such as revising the MPS, rescheduling operations, adding or reducing resources, or outsourcing production.

The other options are not the primary uses of the capacity requirements plan. Calculating the level of available capacity is an input to the capacity requirements plan, not an output. The level of available capacity is determined by the work center file, which contains information such as shifts, hours, efficiency, utilization, and maintenance of each work center. Determining the overall product load profile is not a use of the capacity requirements plan, as it does not consider the product mix or demand variability. The overall product load profile is a general estimate of the total production volume or demand over a period of time. Determining the priority of orders is not a use of the capacity requirements plan, as it does not consider the due dates or urgency of orders. The priority of orders is determined by using priority rules or dispatching methods, such as first-come-first-served (FCFS), shortest processing time (SPT), earliest due date (EDD), or critical ratio (CR).

Mixed-model scheduling is a production technique that allows for the simultaneous production of different products or features on the same production line or system. Mixed-model scheduling can help reduce lead times, inventory levels, setup times, and material shortages by increasing the flexibility and responsiveness of the production process. One of the benefits of mixed-model scheduling is improved demand response, which means the ability to meet customer demand without delay or stockout. Improved demand response can enhance customer satisfaction and loyalty, as well as reduce the need for safety stock or buffer inventory. By using mixed-model scheduling, a company can produce products or features according to the actual or forecasted customer demand, rather than producing large batches of standardized products or features. This can help avoid overproduction or underproduction, which can result in excess inventory or lost sales. Mixed-model scheduling can also help adjust the production output quickly and easily when there are changes or fluctuations in demand, by using flexible automation, lean production techniques, or quick response methods.

The other options are not benefits of mixed-model scheduling. Increased inventory is not a benefit of mixed-model scheduling, but rather a drawback. Increased inventory can increase inventory costs, such as holding costs, transportation costs, or obsolescence costs. It can also reduce inventory visibility and control, as well as increase the risk of quality issues or spoilage. Mixed-model scheduling can help reduce inventory by producing products or features in small batches or single units that match customer demand. Fewer setups are not a benefit of mixed-model scheduling, but rather a requirement. Fewer setups mean less time and resources spent on changing or adjusting the production system to produce different products or features. Fewer setups can increase the efficiency and productivity of the production process, as well as reduce the setup costs and waste. Mixed-model scheduling requires fewer setups to enable the simultaneous production of different products or features on the same production line or system. Fewer material shortages are not a benefit of mixed-model scheduling, but rather an outcome. Fewer material shortages mean less disruption or delay in the production process due to the lack of materials or components needed for production. Fewer material shortages can improve the quality and reliability of the production process, as well as reduce the material costs and waste. Mixed-model scheduling can result in fewer material shortages by reducing the lead times and inventory levels of materials or components, as well as by improving the communication and coordination with suppliers.

The information about the consistent overage in actual run time for one operation should be sent first to the engineering manager to evaluate the run time for the routing. A routing is a document that specifies the sequence of operations and work centers required to produce a product or feature. A run time is the amount of time needed to perform an operation or a task at a work center. An overage in actual run time means that the actual time spent on an operation or a task is more than the planned or standard time. This can result in lower efficiency, productivity, or quality, as well as higher costs, waste, or delays.

The engineering manager is responsible for designing and maintaining the routing and the run time for each operation or task. The engineering manager can evaluate the run time for the routing by comparing the actual and planned times, identifying the causes of the overage, and taking corrective actions. For example, the engineering manager may:

Review the accuracy and validity of the planned or standard time, and update it if necessary.

Analyze the performance and capability of the machines, equipment, or labor involved in the operation or task, and improve them if needed.

Investigate the presence of any errors, defects, rework, or variability in the operation or task, and eliminate them if possible.

Implement lean production techniques, such as value stream mapping, waste reduction, or continuous improvement, to optimize the operation or task.

The other options are not appropriate for sending the information about the consistent overage in actual run time for one operation first. The product manager is not responsible for designing or maintaining the routing or the run time for each operation or task. The product manager is responsible for managing and marketing the product or feature, such as defining its specifications, features, price, or promotion. Increasing the selling price of the product is not a solution for addressing the overage in actual run time, as it may reduce customer demand or satisfaction, as well as increase competition. The quality manager is not responsible for designing or maintaining the routing or the run time for each operation or task. The quality manager is responsible for ensuring and improving the quality of the product or feature, such as setting quality standards, implementing quality control methods, or conducting quality audits. Adding a new quality measurement to the operation is not a solution for addressing the overage in actual run time, as it may increase complexity or cost without improving efficiency or productivity. The production supervisor is not responsible for designing or maintaining the routing or the run time for each operation or task. The production supervisor is responsible for overseeing and coordinating the production activities at a work center, such as scheduling operations, assigning resources, monitoring performance, or resolving issues. Reviewing and explaining the overage in actual run time is not a solution for addressing it, as it does not identify or eliminate its causes.