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Abstract
Data privacy is a serious issue and therefore needs our attention. In this study, we propose masking through randomized response techniques (RRTs) to ensure the privacy and thus to avoid falsification. We assume that the process characteristic is of sensitive nature, and due to privacy issue, the actual measurements cannot be shared with the monitoring team. In such situations, the producer is very likely to falsify the measurements. Consequently, the usual control charting techniques will mislead about the process status. We discuss different data masking strategies to be used with Shewhart-type control charts. The usual Shewhart-type control chart appears to be a subchart of the proposed charts. Average run length (ARL) is used as a performance measure of the study proposals. We have evaluated the performance of the proposed charts for different shift sizes and under different intensities of masking. We have also carried out a comparative analysis for various models under varying sensitivity parameters. We have also compared the performance of the proposals with the traditional Shewhart chart. It is observed that the B-L control chart under the RRT model performs better for smaller shifts and for larger shift sizes, the G-B chart under an unrelated question model tperforms better. A real-life application of the study proposal is also considered where monitoring of thickness of paint on refrigerators is of interest.
Highlights
Control charting technique deals with the early detection of special cause variation in the process. e idea was proposed by Shewhart for monitoring production process and is widely applied in other fields such as health care, social sciences, and business decision-making
On the extension side of control charting techniques, motivated by the Shewhart (1939, p. 134) statement, “the only way one can experience any quality characteristic quantitatively is by means of an operation of measurement,” Linna and Woodall [10] addressed the issue of measurement error in a production process and quantified its impact on power of the Shewhart control chart for monitoring the characteristic under study
Different Types of Masking and Proposed Charts is section is devoted to construction of generalized control charting technique which takes a broad view that of Shewhart and result in a flexible way of monitoring the sensitive character. is mechanism exploits both the quantitative randomized response models and the techniques used for monitoring the process mean in statistical process control
Summary
Control charting technique deals with the early detection of special cause variation in the process. e idea was proposed by Shewhart for monitoring production process and is widely applied in other fields such as health care, social sciences, and business decision-making. 134) statement, “the only way one can experience any quality characteristic quantitatively is by means of an operation of measurement,” Linna and Woodall [10] addressed the issue of measurement error in a production process and quantified its impact on power of the Shewhart control chart for monitoring the characteristic under study. E aim of this paper is to address the issue of false reporting and data privacy in control charting techniques with the help of incorporating randomized responses. 3. Different Types of Masking and Proposed Charts is section is devoted to construction of generalized control charting technique which takes a broad view that of Shewhart and result in a flexible way of monitoring the sensitive character. Is mechanism exploits both the quantitative randomized response models and the techniques used for monitoring the process mean in statistical process control. It is nontrivial to show that mean and variance of Z are μZG pμX +(1 − p)μS, σ
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