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scholarly journals X86_64 Memory Type Tests.

2022 ◽  
Author(s):  
Azalea Raad ◽  
Luc Maranget ◽  
Viktor Vafeiadis
Keyword(s):  
Memory Type

On the location‐based memory type control charts under modified successive sampling scheme

2021 ◽  
Author(s):  
Mehvish Hyder ◽  
Tahir Mahmood ◽  
Muhammad Moeen Butt ◽  
Syed Muhammad Muslim Raza ◽  
Nasir Abbas
Keyword(s):  
Control Charts ◽  
Sampling Scheme ◽  
Successive Sampling ◽  
Memory Type

scholarly journals Distribution-Free CUSUM-Type Control Charts for Monitoring Industrial Processes: An Overview

2021 ◽  
Vol 6 (4) ◽  
pp. 975-1008
Author(s):  
Ioannis S. Triantafyllou ◽  
Mangey Ram
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Crucial Role ◽  
Control Charts ◽  
Industrial Processes ◽  
Cumulative Sum ◽  
Statistical Process ◽  
Distribution Free ◽  
Practical Applications ◽  
Memory Type

In the present paper we provide an up-to-date overview of nonparametric Cumulative Sum (CUSUM) monitoring schemes. Due to their nonparametric nature, such memory-type schemes are proved to be very useful for monitoring industrial processes, where the output does not match to a particular distributional model. Several fundamental contributions on the topic are mentioned, while recent advances are also presented in some detail. In addition, some practical applications of the nonparametric CUSUM-type control charts are highlighted, in order to emphasize their crucial role in the contemporary online Statistical Process Control.

Progressive NO 2 Sensors with Rapid Alarm and Persistent Memory‐Type Responses for Wide‐Range Sensing Using Antimony Triselenide Nanoflakes

2021 ◽  
pp. 2102439
Author(s):  
Young Been Kim ◽  
Sung Hyeon Jung ◽  
Dong Su Kim ◽  
Nishad G. Deshpande ◽  
Hee Won Suh ◽  
...  
Keyword(s):  
Range Sensing ◽  
Wide Range ◽  
Persistent Memory ◽  
Memory Type

Memory type ratio and product estimators under ranked-based sampling schemes

2021 ◽  
pp. 1-23
Author(s):  
Irfan Aslam ◽  
Muhammad Noor-ul-Amin ◽  
Muhammad Hanif ◽  
Paryas Sharma
Keyword(s):  
Sampling Schemes ◽  
Memory Type

scholarly journals Nonparametric EWMA-Type Control Charts for Monitoring Industrial Processes: An Overview

2021 ◽  
Vol 6 (3) ◽  
pp. 708-751
Author(s):  
Ioannis S. Triantafyllou ◽  
Mangey Ram
Keyword(s):  
Probability Distribution ◽  
Statistical Process Control ◽  
Crucial Role ◽  
Control Charts ◽  
Moving Average ◽  
Industrial Processes ◽  
Statistical Process ◽  
Practical Applications ◽  
Memory Type ◽  
Weighted Moving Average

In the present paper we provide an up-to-date overview of nonparametric Exponentially Weighted Moving Average (EWMA) control charts. Due to their nonparametric nature, such memory-type schemes are proved to be very useful for monitoring industrial processes, where the output cannot match to a particular probability distribution. Several fundamental contributions on the topic are mentioned, while recent advances are also presented in some detail. In addition, some practical applications of the nonparametric EWMA-type control charts are highlighted, in order to emphasize their crucial role in the contemporary online statistical process control.

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