Sign In |Help & Support
ALL SECTORS
  • ALL SECTORS
  • GB(National Standard)
  • CB(Shipping)
  • CECS(Engineering Construction)
  • CJ(Urban Construction)
  • CY(News and Publication)
  • DB(Provincial Standard)
  • DL(Electricity & Power)
  • DZ(Geology & Mineralogy)
  • FZ(Spinning & Textile)
  • GA(Public Security)
  • HB(Aviation)
  • HG(Chemical Industry)
  • HJ(Environmental Protection)
  • JB(Machinery)
  • JC(Building Materials)
  • JG(Building & Construction)
  • JJ(Metering)
  • JT(Highway & Transportation)
  • LY(Forestry)
  • MT(Coal)
  • NB(Energy)
  • NY(Agriculture)
  • QB(Light Industry)
  • QC(Automobile & Vehicle)
  • QJ(Aerospace)
  • SH(Petrochemical)
  • SJ(Electronics)
  • SL(Water Resources)
  • SN(Commodity Inspection)
  • SY(Oil & Gas)
  • TB(Railway & Train)
  • YB(Ferrous Metallurgy)
  • YC(Tobacco)
  • YD(Telecommunication)
  • YY(Medical Device)
Database: 365,228(8 Aug 2026)
cumulative sum control charts gb/t cumulative sum charts cumulative sum charts introduction core concepts conventional control charts cumulative sum lng density calculation models scopethe lng density calculation model² export leather shoes pasture seed socket roller
GB/T 17989.4-2020 in English

GB/T 17989.4-2020 in English

VALID

Control charts—Part 4: Cumulative sum charts

  • Issued on:2020-03-06
  • Implemented on:2020-10-01
  • File Format:PDF
  • Delivery:Via email within 5 business days
Price(USD): $820.00
$796.00
Standard No: GB/T 17989.4-2020
Document status: VALID
Title in English: Control charts—Part 4: Cumulative sum charts
Title in Chinese: 控制图 第4部分:累积和控制图
Language: English
File Format: Electronic (PDF)
Delivery: Via email within 5 business days
Issued on: 2020-03-06
Implemented on: 2020-10-01
Superseding: GB/Z 4887-2006 Cumulative Sum charts - Guidance on quality control and data analysis using CUSUM techniques
ICS Classification: 03.120.30-Application of statistical methods
Chinese Classification: A41-Mathematics
Professional Classification: GB-National Standard
Related Keywords: cumulative sum control charts gb/t
cumulative sum charts
cumulative sum charts introduction core concepts
conventional control charts
cumulative sum
Related Topics: product
accumulation
cumulative effect
cumulative effect
Forecast accumulation
Forecast accumulation
GBT17989.4
GB/T 17989.4-2020
Control Charts
mapping

《GB/T 17989.4-2020控制图 第4部分:累积和控制图》由TC21(全国统计方法应用标准化技术委员会)归口,主管部门为国家标准化管理委员会。


Introduction

Core Concepts of Cumulative Sum Control Charts

GB/T 17989.4-2020, as the fourth part of the control chart series standard, focuses on the application of cumulative sum (CUSUM) technology in process monitoring. Compared with conventional control charts, cumulative sum charts are more sensitive to small process deviations by accumulating deviations from target values.


Comparison of standard frameworks

Comparison dimensions Conventional control charts Cumulative and control charts
Detection sensitivity Suitable for detecting large shifts (>2σ) Good at capturing small shifts of 0.5-1.5σ
Data visualization Independent analysis between points Intuitive display of process trends through slope changes
Response speed Average chain length (L0≈370) Customizable L0 up to 1000+ (CS1 solution)

Motor production case analysis

Chapter 6 of the standard takes motor voltage monitoring as an example to demonstrate the process of constructing a cumulative sum chart:

  1. Assume the target value T=10V, calculate the deviation of each observation value (Xi-T)
  2. Accumulate the deviation to obtain the CUSUM sequence
  3. Identify 4 change points through slope analysis (sample No. 10/18/31)

Compared with conventional control charts, the cumulative sum chart detects voltage fluctuations of 7.5V~12.6V earlier, verifying its sensitivity to small offsets.


V-type template design specifications

Chapter 8 of the standard details 5 template types:

  • Truncated V-type: Basic template, h=5σe, f=0.5
  • Semi-parabola: Optimize large offset detection
  • Fast Initial Response (FIR): Set a non-zero initial value to accelerate the alarm

Template parameter calculation formula:

H = hσe F = fσe

Special processing of discrete data

For count data (such as the number of defects), the standard recommends:

  • Use Poisson approximation when Tp<0.1 (Example in Appendix B)
  • When Tm>20, normal approximation is used
  • H and K parameters need to be calculated separately for binomial data

Sample only — not a preview of GB/T 17989.4-2020
Page: 1 / 0
100%

Loading PDF document...

Error loading PDF. Please make sure the file is valid and try again.

We also recommend

  • GB/T 6378.3-2024 in English

    GB/T 6378.3-2024 in English

    Sampling procedures for inspection by variables—Part 3: Double sampling schemes indexed by acceptance quality limit (AQL) for lot-by-lot inspection

    2024-09-29
  • GB/T 40681.2-2023 in English

    GB/T 40681.2-2023 in English

    Statistical methods in monitoring process capability and performance—Part 2: Process capability and performance of time-dependent process models

    2023-11-27
  • GB/T 22553-2023 in English

    GB/T 22553-2023 in English

    Guidance for the use of repeatability, reproducibility and trueness estimates in measurement uncertainty evaluation

    2023-11-27
  • GB/T 16307-2026 in English

    GB/T 16307-2026 in English

    Sequential sampling plans for inspection by variables for percent nonconforming (known standard deviation)

    2026-01-28
  • GB/T 10092-2009 in English

    GB/T 10092-2009 in English

    Statistical interpretation of data - Multiple comparison for test results

    2009-10-15
  • GB/T 8051-2008 in English

    GB/T 8051-2008 in English

    Sequential sampling plans for inspection by attributes

    2008-07-28
  • GB/T 27407-2010 in English

    GB/T 27407-2010 in English

    Quality control in laboratories applying statistical quality assurance and control charting techniques to evaluate analytical measurement system performance

    2011-01-14
  • GB/T 26823-2011 in English

    GB/T 26823-2011 in English

    Acceptance sampling procedures by attributes - Accept-zero sampling system based on credit principle for controlling outgoing quality

    2011-07-29