Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Chati ya Kudhibiti Inayozingatia Hatari× | Udhibiti wa Mchakato wa Kitakwimu× | |
|---|---|---|
| Nyanja | Muundo wa Majaribio | Muundo wa Majaribio |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1956 (economic design); refined through 1980s–2000s | 1924–1931 |
| Mwanzilishi≠ | A. J. Duncan (economic design, 1956); T. J. Lorenzen & L. C. Vance (unified economic model, 1986) | Walter A. Shewhart |
| Aina≠ | Quantitative process monitoring method | Process monitoring and quality control method |
| Chanzo asilia≠ | Lorenzen, T. J., & Vance, L. C. (1986). The economic design of control charts: A unified approach. Technometrics, 28(1), 3–10. DOI ↗ | Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762 |
| Majina mbadala | economic control chart, risk-integrated SPC, cost-based control chart, economic design of control charts | SPC, statistical quality control, process control charting, Shewhart control |
| Zinazohusiana | 6 | 6 |
| Muhtasari≠ | A risk-based control chart extends the classical Shewhart control chart by explicitly incorporating the costs and probabilities of two error types — false alarms (Type I) and missed shifts (Type II) — along with sampling costs, into the design of chart parameters. Rather than using arbitrary 3-sigma limits, the method selects sample size, sampling interval, and control limits to minimise the total expected cost or risk of operating the monitoring scheme. | Statistical Process Control (SPC) is a data-driven quality method that uses statistical techniques — primarily control charts — to monitor a manufacturing or service process over time. By distinguishing natural process variation (common cause) from unusual, actionable variation (special cause), SPC enables practitioners to maintain processes in a stable, predictable state and to detect problems early, before defective output reaches customers. |
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