Abstract
In general, the quality of items produced in a manufacturing process is not necessarily uniform, and it has stochastic variability. Control charts are basic tools for detecting a change in process conditions using the quality data with stochastic variability. When the assignable change in process conditions is detected by the control charts, identifying the time point of state change and searching for assignable causes are important issues in process management. In this study, first we develop the state transition tracking method for depicting the state transition and showing the change points using successive observed data. Then, we discuss a new procedure for monitoring the process conditions using the state transtion tracking method with the control charts.
| Original language | English |
|---|---|
| Pages (from-to) | 240-248 |
| Number of pages | 9 |
| Journal | Journal of Japan Industrial Management Association |
| Volume | 66 |
| Issue number | 3 |
| Publication status | Published - 2015 |
Fingerprint
Keywords
- Change point
- Control charts
- Information criteiron
- Likelihood theory
- Process management
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering
- Applied Mathematics
- Management Science and Operations Research
- Strategy and Management
Cite this
Development and usage of process state transition tracking method for successive data. / Takemoto, Yasuhiko; Arizono, Ikuo.
In: Journal of Japan Industrial Management Association, Vol. 66, No. 3, 2015, p. 240-248.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Development and usage of process state transition tracking method for successive data
AU - Takemoto, Yasuhiko
AU - Arizono, Ikuo
PY - 2015
Y1 - 2015
N2 - In general, the quality of items produced in a manufacturing process is not necessarily uniform, and it has stochastic variability. Control charts are basic tools for detecting a change in process conditions using the quality data with stochastic variability. When the assignable change in process conditions is detected by the control charts, identifying the time point of state change and searching for assignable causes are important issues in process management. In this study, first we develop the state transition tracking method for depicting the state transition and showing the change points using successive observed data. Then, we discuss a new procedure for monitoring the process conditions using the state transtion tracking method with the control charts.
AB - In general, the quality of items produced in a manufacturing process is not necessarily uniform, and it has stochastic variability. Control charts are basic tools for detecting a change in process conditions using the quality data with stochastic variability. When the assignable change in process conditions is detected by the control charts, identifying the time point of state change and searching for assignable causes are important issues in process management. In this study, first we develop the state transition tracking method for depicting the state transition and showing the change points using successive observed data. Then, we discuss a new procedure for monitoring the process conditions using the state transtion tracking method with the control charts.
KW - Change point
KW - Control charts
KW - Information criteiron
KW - Likelihood theory
KW - Process management
UR - http://www.scopus.com/inward/record.url?scp=84946058360&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84946058360&partnerID=8YFLogxK
M3 - Article
VL - 66
SP - 240
EP - 248
JO - Journal of Japan Industrial Management Association
JF - Journal of Japan Industrial Management Association
SN - 0386-4812
IS - 3
ER -