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Category: 130 (Process analysis & improvements)
Categories
: 130 (Process analysis & improvements)
Title
Cat:App
Page
Big data? Statistical process control can help!
130
:
Y
QCAS
/
67
/
3-4
/
181
Comparing two measurement systems using the probability of agreement web app
130
:
Y
QCAS
/
65
/
5-6
/
343
Some perspectives on nonparametric statistical process control
130
:
Y
QCAS
/
64
/
5-6
/
371
Bridging the gap between theory and practice in basic statistical process monitoring
130
:
Y
QCAS
/
64
/
1-2
/
41
A class of process capability indices for asymmetric tolerances
130
:
Y
QCAS
/
63
/
5-6
/
377
Monitoring multivariate process variability when sub-group size is small
130
:
Y
QCAS
/
63
/
5-6
/
381
Process yield for simple linear profiles
130
:
Y
QCAS
/
60
/
1-2
/
29
A Bayesian approach for interpreting mean shifts in multivariate quality control
130
:
Y
QCAS
/
58
/
5-6
/
455
Variability reduction: A statistical engineering approach to engage operations teams in process improvement
130
:
Y
QCAS
/
58
/
4
/
307
A LASSO-based diagnostic framework for multivariate statistical process control
130
:
Y
QCAS
/
58
/
1-2
/
33
On the expected parts per million nonconforming levels obtained from estimated process capability indices
130
:
Y
QCAS
/
56
/
5-6
/
435
Rethinking Statistics for Quality Control
130
:
Y
QCAS
/
56
/
1-2
/
25
Optimization designs and performance comparison of two CUSUM schemes for monitoring process shifts in mean and variance
130
:
Y
QCAS
/
55
/
3
/
189
Shipping operations quality assurance for fiberglass reinforced plastics manufacturersFiller
130
:
M
QCAS
/
55
/
1-2
/
21
Statistical process monitoring of nonlinear profiles using wavelets
130
:
Y
QCAS
/
54
/
3
/
189
Estimation of process parameters to determine the optimum diagnosis interval for control of defective items
130
:
Y
QCAS
/
54
/
1-2
/
25
Bright idea: Using SPC could help prevent the next blackout
130
:
Y
QCAS
/
54
/
1-2
/
27
Statistical monitoring of a sealing process by means of multivariate accelerometer data
130
:
M
QCAS
/
53
/
6
/
555
Understanding behavioral sources of process variation following enterprise system deployment
130
:
Y
QCAS
/
53
/
6
/
557
A statistical process control approach to selecting a warm-up period for a discrete-event simulation
130
:
Y
QCAS
/
52
/
5
/
487
Use SPC for everyday work processes
130
:
Y
QCAS
/
52
/
2
/
159
CUSUM method in predicting regime shifts and its performance in different stock markets allowing for transaction fees
130
:
A
QCAS
/
52
/
1
/
33
Modelling of unexpected shift in SPC
130
:
Y
QCAS
/
51
/
2
/
145
A Bayesian approach for assessing process precision based on multiple samples
130
:
Y
QCAS
/
50
/
6
/
619
Process investment and loss functions: Models and analysis
130
:
M
QCAS
/
50
/
2
/
121
A statistical process control framework for the characterization of variation in batch profiles
130
:
Y
QCAS
/
49
/
5
/
515
Learning curves and p-charts for a preliminary estimation of asymptotic performances of a manufacturing process
130
:
M
QCAS
/
47
/
6
/
611
Applying Hotelling’s T2 statistic to batch processes
130
:
Y
QCAS
/
47
/
4
/
373
Adaptive quality-control strategy for progressive reduction of the amount of inspection required
130
:
Y
QCAS
/
47
/
2
/
131
Estimation of the change point of a normal process mean in SPC applications
130
:
Y
QCAS
/
46
/
4
/
383
Joint monitoring of PID-controlled processes
130
:
Y
QCAS
/
45
/
6
/
619
Process tolerance limits
130
:
Y
QCAS
/
45
/
6
/
625
An SPC case study on stabilizing syringe lengths
130
:
Y
QCAS
/
45
/
5
/
509
An approach to controlling process variability for short production runs
130
:
Y
QCAS
/
45
/
3
/
259