Statistical Process Control (SPC) Flashcards
6 cards from real Certified Six Sigma Black Belt Exam practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Statistical Process Control (SPC) flashcards as text
The primary purpose of a control chart in Statistical Process Control (SPC) is to:
Answer: Graphically distinguish between common cause and special cause variation.
Control charts are specifically designed to monitor a process over time and identify when unexpected or 'special cause' variation occurs, which is distinct from the natural, inherent 'common cause' variation. While SPC contributes to meeting specifications and improving capability, the chart's fundamental purpose is to differentiate between these two types of variation.
A Black Belt is monitoring a process using an X-bar chart. For the last nine consecutive subgroups, the plotted averages have all fallen below the centerline. What is the most likely interpretation of this pattern?
Answer: A special cause has influenced the process, causing a sustained shift in the mean.
A run of eight or more consecutive points on one side of the centerline is a standard rule for identifying a non-random pattern, which indicates the presence of a special cause of variation. This pattern signifies a sustained shift in the process average that requires investigation.
A quality manager wants to monitor the number of nonconformities (e.g., scratches, dents, paint blemishes) on the surface of refrigerators. Each refrigerator is considered one unit. The number of refrigerators inspected each hour is constant. Which of the following control charts is most appropriate for this application?
Answer: c-chart
A c-chart is used for attribute data to monitor the total count of defects or nonconformities per unit (or a constant area of opportunity). Since the data represents the count of defects on one unit (a refrigerator) and the sample size (one unit) is constant, the c-chart is the correct choice.
Which of the following statements best describes the relationship between control limits and specification limits?
Answer: Control limits are calculated from process data, while specification limits are determined by customer requirements.
Control limits are derived from the actual performance of the process (the 'voice of the process') and indicate its natural variation. Specification limits are set by the customer or engineering and define what is acceptable for the product (the 'voice of the customer'). A process can be in control (stable) but not capable of meeting customer specifications, and vice versa.
A process is described as being 'in statistical control' but not 'capable'. What does this mean?
Answer: The process has too much common cause variation, preventing it from meeting customer specifications.
A process 'in statistical control' is stable and predictable, meaning it is only subject to common cause variation. However, if it is not 'capable', the predictable spread of its natural variation is wider than the customer's specification limits allow. Therefore, even when running as expected, it consistently produces non-conforming products.
In SPC, which of the following is an example of a special cause of variation?
Answer: A machine operator who is not properly trained for a specific task.
A special cause of variation is an assignable, non-random event that is not an inherent part of the process. An untrained operator introduces an unpredictable and correctable source of error, which fits the definition of a special cause. The other options describe sources of natural, expected, and random variation, which are considered common causes.