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Statistical Process Control Charts

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Abstractions about monitoring process stability using control charts, including attribute-based charts such as the c-chart and np-chart, continuous and adaptive monitoring statistics like the EWMA chart and Shewhart individuals control chart, and the underlying variation concepts they rely on such as natural process variation and the Reynolds operator.

7 abstractions in this family — domain-specific abstractions that sit near one another in structural-signature space (k-means over structural-signature embeddings). Each is shown with its short description.

  • C-chart — Monitor the count of nonconformities in constant-size inspection units against Poisson-based center and control limits.
  • Delay-gradient congestion control — Regulate a network sender using the direction and magnitude of recent round-trip-delay change as congestion feedback, rather than relying only on packet loss or a fixed absolute-delay threshold.
  • EWMA chart — Monitor a time-ordered process by plotting a recursively updated exponentially weighted statistic against model-based control limits, retaining geometrically decreasing memory to improve sensitivity to sustained small shifts.
  • Natural Process Variation — The common-cause fluctuation produced by a stable process's recurring causal system, estimated from time-ordered data so routine behavior can be separated from assignable special-cause signals and tampering.
  • Np-chart — Monitor a fixed-size sequence of samples by plotting each sample's count of nonconforming units against binomial center and control limits, separating common-cause fluctuation from special-cause signals.
  • Reynolds operator — Project objects onto their invariant part by averaging over a symmetry group or averaging regime, with linearity, idempotence, and compatibility rules governing the result.
  • Shewhart individuals control chart — A paired individuals and moving-range control chart for monitoring a process one observation at a time when rational subgroups are unavailable or inappropriate.