Questjay cloud is a combined Questjay CUSUM and conformity system used for the statistical monitoring of concrete strength and compliance for concrete producers. The Questjay CUSUM uses traditional methods of plotting graphical trend lines for the mean cement content, standard deviation and the correlation between the early and late strengths. The Questjay CUSUM will automatically adjust these values and reset the graphs if a change is detected by the trend line crosses a V mask.
Economic Design of CUSUM Control Charts for Indian RMC Industry
Method A evaluates the first thirty five twenty eight day strengths using the mean of three non overlapping results.
Once thirty five results have been obtained the system switches over to monitor strengths using Method C. Method C again uses graphical trend lines to plot thirty five rolling twenty eight day strengths.
The graph uses a warning V mask showing where strengths are under performing and a non conforming V mask showing where strengths have not conformed. Warning messages are displayed and logged where either of these events have occurred.
Questjay also has the ability to run scenarios for Questjay CUSUM and conformity from any given point using user defined parameters. These parameters are used to generate and display new graphs and tables which can overwrite the existing data if the user feels it is more realistic than data generated by the system. Where any value has changed for either the Questjay CUSUM or conformity, Questjay will automatically store a log displaying the new values along with the date and time of change.
Request a demo Contact Us. Don't change the way you work to fit our software. We change our software to fit the way you work. Due to the modular nature of the application, companies can purchase either the whole end-to-end system or only the functionality you require.
Furthermore, our expert team will customise any aspect of the Minder suite to fit your processes. Just ask. Get in touch! Request a demo. Standards compliant Questjay cloud is a combined Questjay CUSUM and conformity system used for the statistical monitoring of concrete strength and compliance for concrete producers. Clear displays Questjay also has the ability to run scenarios for Questjay CUSUM and conformity from any given point using user defined parameters.
Software that fits your business Don't change the way you work to fit our software. Trusted by. ReadyMinder For ready mix concrete businesses. QuarryMinder Improving the running of your quarry. PlantMinder Improve your plant management. Streamlining your processes.Skip to content. Control charts are a very important tool in quality control. Variability in a manufactured product is unavoidable, but it is important to understand if the variability is controlled variation or uncontrolled variation.
Controlled variation is attributed to chance or common causes and is a consistent pattern of variation over time. Uncontrolled variation is attributed to assignable or special causes and is an inconsistent pattern of variation over time. The primary use of control charts is to quickly identify uncontrolled variation attributable to special causes. This can be difficult depending on the type of special cause. Some special causes, such as crusher liner wear, may cause a drift or a slow change to the gradation.
Other special causes, such as a change in mix design materials or equipment malfunction, may cause a step-change that is more abrupt Obla, In its most basic form, a control chart can be any chart containing control limits. Walter A. Shewhart charts are used to monitor the process average and process variability using either standard deviation or range. Control limits are typically upper and lower boundaries outside of which the process is statistically unlikely to produce results they represent the limits of the natural process or controlled variation.
In other words, control limits should be computed from the process rather than be specified limits, such as specifications. If your control limits are outside of your specification limits then your process is telling you that it is statistically likely to produce failures.
Control charts are used to identify signals such as when a data point is outside of the control limits, or two out of three successive points fall on the same side of the average NSSGA, Stonemont Software includes rule checking to help identify common signals.
Run charts are probably the most commonly used chart in Stonemont Software because they are the most easily understood. When data are normally distributed, control limits at 2 x SD should contain about Run charts help monitor the process mean and are useful for understanding the relationship between control limits based on 2xSD and specification limits, identifying trends using a best-fit trend line, and changes in mean using a moving average line.
In Stonemont Software, our standard control charts are based on Shewhart charts and they provide the ability analyze data as individual charts, average and range charts, and moving average and range charts. Average and moving average charts use subgroups of data points, which have the effect of smoothing out some of the erratic individual data points making overall trends or changes in mean easier to identify.
However, individual charts are more suited for data that is collected periodically to ensure that a change in the process is not missed NSSGA, Stonemont Software includes a special control chart for compressive strength data that shows the within-batch variation or the variation between cylinders made from the same concrete sample. This chart also shows the average, moving average, limits, design and required strengths. The range chart can be the actual within batch range, the normalized within batch range expressed as a percent, or the within batch coefficient of variation CVwhich is used as a measure of testing variability.
Cusum charts are designed to quickly identify a change in the process mean or average; commonly a 1 x SD change in the process mean. Cusum charts can be represented either as a standard or tabular form of the cusum. Stonemont Software uses the tabular cusum on individual cusum charts and the standard form on multi-variable cusum charts. The tabular cusum chart is much easier to read and understand because control limits can be used to quickly identify a change in mean.
However, a multi-variable cusum chart is useful for identifying correlations of change between variables such as whether concrete compressive strength changes correlate to those of concrete density, slump, or temperature.
Based on these correlations it appears that the cause may be an increase in water added to each load. Control charts are an extremely useful tool in quality control. Stonemont Software provides several different control charts, which allows quality control personnel to use the control chart that they feel is best suited for their application. Automated reporting is critical for your most common products.
OblaK.To discuss your requirements please contact Minder Software Ltdor telephone : Questjay cloud is a combined Questjay CUSUM and conformity system used for the statistical monitoring of concrete strength and compliance for concrete producers.
The Questjay CUSUM uses traditional methods of plotting graphical trend lines for the mean cement content, standard deviation and the correlation between the early and late strengths. The Questjay CUSUM will automatically adjust these values and reset the graphs if a change is detected by the trend line crosses a V mask.
Method A evaluates the first thirty five twenty eight day strengths using the mean of three non overlapping results. Once thirty five results have been obtained the system switches over to monitor strengths using Method C. Method C again uses graphical trend lines to plot thirty five rolling twenty eight day strengths. The graph uses a warning V mask showing where strengths are under performing and a non conforming V mask showing where strengths have not conformed.
Warning messages are displayed and logged where either of these events have occurred. Questjay also has the ability to run scenarios for Questjay CUSUM and conformity from any given point using user defined parameters. These parameters are used to generate and display new graphs and tables which can overwrite the existing data if the user feels it is more realistic than data generated by the system.
Where any value has changed for either the Questjay CUSUM or conformity, Questjay will automatically store a log displaying the new values along with the date and time of change. Standards Compliant Questjay cloud is a combined Questjay CUSUM and conformity system used for the statistical monitoring of concrete strength and compliance for concrete producers.In statistical quality controlthe CUSUM or cumulative sum control chart is a sequential analysis technique developed by E.
Page of the University of Cambridge. It is typically used for monitoring change detection.
He devised CUSUM as a method to determine changes in it, and proposed a criterion for deciding when to take corrective action. When the CUSUM method is applied to changes in mean, it can be used for step detection of a time series.
As its name implies, CUSUM involves the calculation of a cu mulative sum which is what makes it "sequential".
When the value of S exceeds a certain threshold value, a change in value has been found. The above formula only detects changes in the positive direction. When negative changes need to be found as well, the min operation should be used instead of the max operation, and this time a change has been found when the value of S is below the negative value of the threshold value.
Note that this is not equivalent to Matlab's "cumsum". Note that this differs from SPRT by always using zero function as the lower "holding barrier" rather than a lower "holding barrier". When the quality of the output is satisfactory the A. On the other hand, for constant poor quality the A. Cumulative observed-minus-expected plots  are a related method.
From Wikipedia, the free encyclopedia. For the Roman town of Cusum, see Petrovaradin. Statistical Methods in Medical Research. June Journal of the Royal Statistical Society. B Methodological 21, number 2 : — Statistical Research Memoirs. I : —Process or Product Monitoring and Control 6. Univariate and Multivariate Control Charts 6. What are Variables Control Charts? CUSUM charts, while not as intuitive and simple to operate as Shewhart charts, have been shown to be more efficient in detecting small shifts in the mean of a process.
In particular, analyzing ARL's for CUSUM control charts shows that they are better than Shewhart control charts when it is desired to detect shifts in the mean that are 2 sigma or less. The choice of which of these two quantities is plotted is usually determined by the statistical software package. If the process mean shifts upward, the charted CUSUM points will eventually drift upwards, and vice versa if the process mean decreases.
A visual procedure proposed by Barnard inknown as the V-Maskis sometimes used to determine whether a process is out of control. More often, the tabular form of the V -Mask is preferred. The tabular form is illustrated later in this section. A V -Mask is an overlay shape in the form of a V on its side that is superimposed on the graph of the cumulative sums.
The origin point of the V- Mask see diagram below is placed on top of the latest cumulative sum point and past points are examined to see if any fall above or below the sides of the V.
As long as all the previous points lie between the sides of the Vthe process is in control.
Otherwise even if one point lies outside the process is suspected of being out of control. In the diagram above, the V- Mask shows an out of control situation because of the point that lies above the upper arm. By sliding the V -Mask backwards so that the origin point covers other cumulative sum data points, we can determine the first point that signaled an out-of-control situation.
This is useful for diagnosing what might have caused the process to go out of control. These are the design parameters of the V -Mask. In practice, designing and manually constructing a V -Mask is a complicated procedure.
A CUSUM spreadsheet style procedure shown below is more practical, unless you have statistical software that automates the V -Mask methodology. Before describing the spreadsheet approach, we will look briefly at an example of a V -Mask in graph form. An example will be used to illustrate the construction and application of a V- Mask.
The 20 data points Based on process data, the process standard deviation is 1.
When the V -Mask is placed over the last data point, the mask clearly indicates an out of control situation. We next move the V -Mask and back to the first point that indicated the process was out of control.
This is point number 14, as shown below. The V -Mask is actually a carry-over of the pre-computer era.My hotel was amazing and all the tour guides were incredible. I had the most amazing time. Dan and Elaine, China Nuuk - Heart of Greenland, September 2015 In September, hiking in Ice fiord area is wonderful.
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