Road map to the statistical process control

José Gomes Requeijo; Rogério Puga-Leal; Ana Sofia Matos

doi:10.1007/978-3-642-55122-2_82

Road map to the statistical process control

José Gomes Requeijo, Rogério Puga-Leal, Ana Sofia Matos

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Since 1920s, when Walter Shewhart first introduced the foundations for control charts, that several developments regarding new implementations of the statistical process control (SPC) have been presented in order to suit different situations that can be found in several processes. It is noted, among others, the Short Run SPC, data non-normality, the presence of auto-correlation in process data, detection of small and moderate shifts in process parameters and the simultaneous control of various quality characteristics. This great diversity of situations is crucial for academic researchers and quality managers in making decisions regarding the choice of the best technique to implement the statistical processes control. For answering this diversity of situations in production systems, this paper presents a road map that allows the decision maker choosing the best technique for implementation. Various techniques are shown, such as the traditional Shewhart control charts, cumulative sums (CUSUM) charts, exponential weighted moving average (EWMA) charts, dimensionless Z/W and Q charts, residuals/forecast errors charts to processes with a significant autocorrelation and multivariate control charts.

Original language	English
Title of host publication	Proceedings of the 8th International Conference on Management Science and Engineering Management - Focused on Computing and Engineering Management
Publisher	Springer-Verlag
Pages	949-957
Number of pages	9
Volume	281
ISBN (Electronic)	9783642551215
DOIs	https://doi.org/10.1007/978-3-642-55122-2_82
Publication status	Published - 2014
Event	8th International Conference on Management Science and Engineering Management, ICMSEM 2014 - Lisboa, Lisbon, Portugal Duration: 25 Jul 2014 → 27 Jul 2014 Conference number: 8th http://www.icmsem.org/past/201501/8.html

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	281
ISSN (Print)	21945357

Conference

Conference	8th International Conference on Management Science and Engineering Management, ICMSEM 2014
Abbreviated title	ICMSEM 2014
Country/Territory	Portugal
City	Lisbon
Period	25/07/14 → 27/07/14
Internet address	http://www.icmsem.org/past/201501/8.html

Keywords

Auto-correlation
Process capability
Short runs
Statistical process control (SPC)

Access to Document

10.1007/978-3-642-55122-2_82

Cite this

Requeijo, J. G., Puga-Leal, R., & Matos, A. S. (2014). Road map to the statistical process control. In Proceedings of the 8th International Conference on Management Science and Engineering Management - Focused on Computing and Engineering Management (Vol. 281, pp. 949-957). (Advances in Intelligent Systems and Computing; Vol. 281). Springer-Verlag. https://doi.org/10.1007/978-3-642-55122-2_82

@inproceedings{32e986d9048246d69357572253426bfc,

title = "Road map to the statistical process control",

abstract = "Since 1920s, when Walter Shewhart first introduced the foundations for control charts, that several developments regarding new implementations of the statistical process control (SPC) have been presented in order to suit different situations that can be found in several processes. It is noted, among others, the Short Run SPC, data non-normality, the presence of auto-correlation in process data, detection of small and moderate shifts in process parameters and the simultaneous control of various quality characteristics. This great diversity of situations is crucial for academic researchers and quality managers in making decisions regarding the choice of the best technique to implement the statistical processes control. For answering this diversity of situations in production systems, this paper presents a road map that allows the decision maker choosing the best technique for implementation. Various techniques are shown, such as the traditional Shewhart control charts, cumulative sums (CUSUM) charts, exponential weighted moving average (EWMA) charts, dimensionless Z/W and Q charts, residuals/forecast errors charts to processes with a significant autocorrelation and multivariate control charts.",

keywords = "Auto-correlation, Process capability, Short runs, Statistical process control (SPC)",

author = "Requeijo, {Jos{\'e} Gomes} and Rog{\'e}rio Puga-Leal and Matos, {Ana Sofia}",

year = "2014",

doi = "10.1007/978-3-642-55122-2_82",

language = "English",

volume = "281",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer-Verlag",

pages = "949--957",

booktitle = "Proceedings of the 8th International Conference on Management Science and Engineering Management - Focused on Computing and Engineering Management",

note = "8th International Conference on Management Science and Engineering Management, ICMSEM 2014, ICMSEM 2014 ; Conference date: 25-07-2014 Through 27-07-2014",

url = "http://www.icmsem.org/past/201501/8.html",

}

Requeijo, JG, Puga-Leal, R & Matos, AS 2014, Road map to the statistical process control. in Proceedings of the 8th International Conference on Management Science and Engineering Management - Focused on Computing and Engineering Management. vol. 281, Advances in Intelligent Systems and Computing, vol. 281, Springer-Verlag, pp. 949-957, 8th International Conference on Management Science and Engineering Management, ICMSEM 2014, Lisbon, Portugal, 25/07/14. https://doi.org/10.1007/978-3-642-55122-2_82

Road map to the statistical process control. / Requeijo, José Gomes; Puga-Leal, Rogério ; Matos, Ana Sofia.

Proceedings of the 8th International Conference on Management Science and Engineering Management - Focused on Computing and Engineering Management. Vol. 281 Springer-Verlag, 2014. p. 949-957 (Advances in Intelligent Systems and Computing; Vol. 281).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Road map to the statistical process control

AU - Requeijo, José Gomes

AU - Puga-Leal, Rogério

AU - Matos, Ana Sofia

N1 - Conference code: 8th

PY - 2014

Y1 - 2014

N2 - Since 1920s, when Walter Shewhart first introduced the foundations for control charts, that several developments regarding new implementations of the statistical process control (SPC) have been presented in order to suit different situations that can be found in several processes. It is noted, among others, the Short Run SPC, data non-normality, the presence of auto-correlation in process data, detection of small and moderate shifts in process parameters and the simultaneous control of various quality characteristics. This great diversity of situations is crucial for academic researchers and quality managers in making decisions regarding the choice of the best technique to implement the statistical processes control. For answering this diversity of situations in production systems, this paper presents a road map that allows the decision maker choosing the best technique for implementation. Various techniques are shown, such as the traditional Shewhart control charts, cumulative sums (CUSUM) charts, exponential weighted moving average (EWMA) charts, dimensionless Z/W and Q charts, residuals/forecast errors charts to processes with a significant autocorrelation and multivariate control charts.

AB - Since 1920s, when Walter Shewhart first introduced the foundations for control charts, that several developments regarding new implementations of the statistical process control (SPC) have been presented in order to suit different situations that can be found in several processes. It is noted, among others, the Short Run SPC, data non-normality, the presence of auto-correlation in process data, detection of small and moderate shifts in process parameters and the simultaneous control of various quality characteristics. This great diversity of situations is crucial for academic researchers and quality managers in making decisions regarding the choice of the best technique to implement the statistical processes control. For answering this diversity of situations in production systems, this paper presents a road map that allows the decision maker choosing the best technique for implementation. Various techniques are shown, such as the traditional Shewhart control charts, cumulative sums (CUSUM) charts, exponential weighted moving average (EWMA) charts, dimensionless Z/W and Q charts, residuals/forecast errors charts to processes with a significant autocorrelation and multivariate control charts.

KW - Auto-correlation

KW - Process capability

KW - Short runs

KW - Statistical process control (SPC)

UR - http://www.scopus.com/inward/record.url?scp=84919360076&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-55122-2_82

DO - 10.1007/978-3-642-55122-2_82

M3 - Conference contribution

AN - SCOPUS:84919360076

VL - 281

T3 - Advances in Intelligent Systems and Computing

SP - 949

EP - 957

BT - Proceedings of the 8th International Conference on Management Science and Engineering Management - Focused on Computing and Engineering Management

PB - Springer-Verlag

T2 - 8th International Conference on Management Science and Engineering Management, ICMSEM 2014

Y2 - 25 July 2014 through 27 July 2014

ER -

Requeijo JG, Puga-Leal R , Matos AS. Road map to the statistical process control. In Proceedings of the 8th International Conference on Management Science and Engineering Management - Focused on Computing and Engineering Management. Vol. 281. Springer-Verlag. 2014. p. 949-957. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-642-55122-2_82

Road map to the statistical process control

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this