In today's highly competitive industrial environment due to fast technology development, quality practitioners will to detect out-of-control situations and take actions whenever is necessary as soon as possible. Accordingly, new statistical procedures have been enhanced incessantly both to handle high yield processes along with looking for methods of minimizing all quality cost. CCC-r chart, th...

CCC-r chart extended approach of CCC charts, is a technique applied when nonconforming items are rarely observed. However, it is usually assumed that the inspection process is perfect in the implementation control charts imperfect inspections may have a significant impact on the performance of the control chart and setting the control limits. This paper first investigates the ...

The application of protective gel, which is a subprocess of the electronic assembly of the exhaust gas recircula‐ tion sensor, is a highly capable process with the fraction of nonconforming units as low as 200 ppm. Every unit is inspected immediately after gel application. The conven‐ tional Shewhart chart is of no use here, and the ap‐ proach based on the Bernoulli process is therefore conside...

Decision procedures for monitoring industrial processes can be based on application of control charts. The commonly used p-chart and np-chart are unsatisfactory for monitoring high-quality processes with a low fraction nonconforming. To overcome this difficulty, one may develop models based on the number of items inspected until r (P 1) nonconforming items are observed. The cumulative count con...

CCC-r control chart is a monitoring technique for high yield processes. It is based on the analysis of the number of inspected items until observing a specific number of defective items.  One of the assumptions in implementing CCC-r chart that has a significant effect on the design of the control chart is that the inspection is perfect. However, in reality, due to the multiple reasons, the...

In high quality industrial processes, the control chart is design based on cumulative count of conforming (CCC) items is very useful. In this paper, the performance of CCC-r chart with variable sampling intervals (CCC-rVSI chart) in the presence ofinspectionerrors isinvestigated. The efficiency of CCC-rVSI chart is compared with CCC-r chart with fixed sampling interval (CC...

In high-yields process monitoring, the Geometric distribution is particularly useful to control the cumulative counts of conforming (CCC) items. However, in some instances the number of defects on a nonconforming observation is also of important application and must be monitored. For the latter case, the use of the generalized Poisson distribution and hence simultaneously implementation of two ...

Cumulative Count of Conforming (CCC) charts are utilized for monitoring the quality characteristics in high-quality processes. Executive cost of control charts is a motivation for researchers to design them with the lowest cost. Usually in most researches, only one objective named cost function is minimized subject to statistical constraints, which is not effective method for economic-statistic...

The CCC-r chart is developed based on cumulative count of a conforming (CCC) control chart that considers the cumulative number of items inspected until observing r nonconforming ones. Typically, the samples obtained from the process are analyzed through 100% inspection to exploit the CCC-r chart. However, considering the inspection cost and time would limit its implementation. In this paper, w...

The cumulative conformance count (CCC) charts are widespread in process monitoring of high-yield manufacturing. Recently, it is found the use of variable sampling interval (VSI) scheme could further enhance the efficiency of the standard CCC charts. The average time to signal (ATS) a shift in defect rate has become traditional measure of efficiency of a chart with the VSI scheme. Determining th...