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Six_Sigma

ICYB · Question #87

Which statement best describes a process that is 搃n statistical control?

The correct answer is B. It shows only common cause variation. A process "in statistical control" means its variation is predictable and stems entirely from common causes - the natural, inherent variability built into the system - with no unexpected special cause variation (spikes, shifts, or patterns caused by assignable events). This is th

Control

Question

Which statement best describes a process that is 搃n statistical control?

Options

  • AIt operates efficiently with no waste
  • BIt shows only common cause variation
  • CIt consistently meets customer specifications
  • DIt has a high sigma level

How the community answered

(30 responses)
  • A
    7% (2)
  • B
    87% (26)
  • C
    3% (1)
  • D
    3% (1)

Explanation

A process "in statistical control" means its variation is predictable and stems entirely from common causes - the natural, inherent variability built into the system - with no unexpected special cause variation (spikes, shifts, or patterns caused by assignable events). This is the precise definition from statistical process control (SPC) theory, making B correct.

  • A is wrong because efficiency and waste elimination are concepts from lean manufacturing; a process can be in statistical control yet still be wasteful or inefficient.
  • C is wrong because statistical control is about predictability of variation, not about meeting specs - a process can be perfectly stable yet centered far outside specification limits.
  • D is wrong because sigma level (e.g., Six Sigma) measures how well the process fits within spec limits relative to its spread, which is a capability concept, not a control concept.

Memory tip: Think "control = calm and consistent causes." If the only variation you see is the calm, everyday noise the process always produces, you're in statistical control - regardless of whether the output is good or bad.

Topics

#statistical control#common cause variation#control charts#process stability

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