APICS Updated CPIM-Part-2 Exam Questions and Answers by tahlia

Mean time between failures (MTBF) is the predicted elapsed time between inherent failures of a mechanical or electronic system during normal system operation1. MTBF can be calculated as the arithmetic mean (average) time between failures of a system1. MTBF is a useful measure of reliability, because it indicates how long a system is likely to work before failing. The higher the MTBF, the more reliable the system2. Reliability is the probability that a system will perform its intended function without failure for a specified period of time under specified conditions3.

The other statements about MTBF are false. MTBF is not used for non-repairable products, but for repairable systems. For non-repairable products, mean time to failure (MTTF) is used instead4. MTTF is the expected time to failure for a non-repairable system1. An increase in MTBF is not proportional to an increase in quality, because quality is not only determined by reliability, but also by other factors such as performance, functionality, durability, and customer satisfaction5. MTBF is not the same as operating life or service life, because operating life or service life is the total time that a system can operate before it reaches the end of its useful life, while MTBF is the average time between failures during the operating life6.

The horizon for forecasts that are input to the sales and operations planning (S&OP) process should be long enough that required resources can be properly planned. The S&OP process is a cross-functional process that aligns the demand and supply plans of an organization. The S&OP process consists of several steps, such as data gathering, demand planning, supply planning, pre-S&OP meeting, executive S&OP meeting, and S&OP implementation. The output of the S&OP process is the production plan, which is a statement of the resources needed to meet the aggregate demand plan over a medium-term horizon. The production plan can be stated in different units of measure depending on the type of manufacturing environment, such as hours, units, tons, or dollars. The horizon for forecasts that are input to the S&OP process should be long enough that required resources can be properly planned, meaning that the organization can anticipate and allocate the necessary capacity, materials, labor, equipment, and facilities to meet the expected demand. The horizon for forecasts should also match the lead time for acquiring or changing the resources, as well as the planning cycle for updating the production plan.

References: CPIM Exam Content Manual Version 7.0, Domain 4: Plan and Manage Supply, Section 4.1: Develop Supply Plans, Subsection 4.1.2: Describe how to develop a production plan (page 36).

The sales and operations planning (S&OP) process is a cross-functional process that aligns the demand and supply plans of an organization. The S&OP process consists of several steps, such as data gathering, demand planning, supply planning, pre-S&OP meeting, executive S&OP meeting, and S&OP implementation. Once the S&OP process has been completed, the executive S&OP meeting approves the final production plan, which is the output of the supply planning step. The production plan is a statement of the resources needed to meet the aggregate demand plan over a medium-term horizon. The functional responsibility of operations is to meet the revised production plan by developing and executing the master production schedule (MPS) and the detailed schedules. The MPS is a statement of the specific end items to be produced in each time period of the short-term horizon. The detailed schedules are the statements of the specific materials, resources, and activities needed to execute the MPS. References: CPIM Exam Content Manual Version 7.0, Domain 4: Plan and Manage Supply, Section 4.1: Develop Supply Plans, Subsection 4.1.2: Describe how to develop a production plan (page 36).

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.

References := Bullwhip Effect: Meaning, Example, Impact - Investopedia, Bullwhip Effect - What Is It, Causes, Supply Chain, Examples, Bullwhip Effect: Example, Causes, and Impact on Supply Chain