TY - GEN
T1 - Road map to the statistical process control
AU - Requeijo, José Gomes
AU - Puga-Leal, Rogério
AU - Matos, Ana Sofia
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
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
ER -