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