Box 5-1 Control Charts

Examples of property control charts that show a run of data (highlighted In box) Indicating that the system Is out of statistical control. 

The chosen coordinates defining minimum/maximum pH levels and minimum/maximum phosphate (as ppm P04) led to the production of various coordinated phosphate program control charts for different pressure ratings (maximum phosphate solubility is a function of pressure). The area within the coordinates providies a simple control box for BW testing purposes. 

Documentation is critical for assessment. Standard protocols provide directions for what must be documented and how the documentation is to be done, including how to record information in notebooks. For labs that rely on manuals of standard practices, it is imperative that tasks done to comply with the manuals be monitored and recorded. Control charts (Box 5-1) can be used to monitor performance on blanks, calibration checks, and spiked samples to see if results are stable over time or to compare the work of different employees. Control charts can also monitor sensitivity or selectivity, especially if a laboratory encounters a wide variety of matrixes. 

The major emphasis will be on the minimum variance stochastic control schemes of Box and Jenkins ( b) and Astrom (l ), and on modifications of them. These schemes have seen successful application in the polymer industry, and they are intuitively appealing and yet simple enough to be implemented by the plant operators using either a programmable hand calculator or control charts and tables. More powerful adaptive versions can be implemented if a small online mini-computer is available. 

Within a slightly different context, a third approach appears which considered the existence of adjustment costs. The implementation of control charts acting as a supervisor of the control actions was the way found by several authors to minimize adjustment costs (e.g. Box and Luceno, 1997 andRuhhal et al., 2000). 

Raw material characterization. A simple, rapid single-point melt index (MI) test is used (see Chapter 10). Although the MI does not completely characterize a resin, for purposes of SPC it does not need to. Also used is a simple time-dependent sampling method. The resin supplier should sequentially number each box/container in the preliminary runs. A sample from each box is measured, and results are plotted using a standard control chart format. 

When control charts are developed for abnormal data distributions, as in the studied case, the results are as saw in Figure 3. In this figure, the control graph for the THDV of the LI phase of Sample A shows a very high number of outliers, 37 out of a set of 39 elements, which is totally contrary to the definition of outlier in section 2 of this work. This behavior persists even when submitting the data set to a Box-Cox transformation in an attempt to correct the distribution bias, the differences of the variances on the time axis or the possible nonlinearity of the data. 

Control chart. The graph in Box 5-1 shows mean values for five replicate quality control samples measured each day. The standard operating procedure calls for stopping work to identify the source of error if the mean daily quality control result is outside the action lines ( 3a/V7i). This condition does not occur in Box 5-1. Are any other rejection conditions from Box 5-1 observed in this data ... 

There are many process control methods often leading to the use of control charts for the purposes of process monitoring. One basic assumption for the use of these control charts is that the process variables are independent and identically distributed (IID). Unfortunately, much of the data used in statistical process control is non-IID. As Alwan and Radson note, non-IID behavior such, as cyclical, seasonal and trend often exists in practice. Alwan and Radson also note that because of the efforts of G.E.P. Box, the chemical industry has recognized for many years that autocorrelation exists in their processes. Baxley, " Berthouex et al., Ermer et al., Harris and Ross, and Hunter " have noted that continuous process industries often have autocorrelated process data. 

Double-clicking the controller icon opens a controller faceplate, as shown in Figure 3.66. The controller faceplate is where all the features of the controller can be examined and adjusted. There are seven buttons at the top. The first one from the left puts the controller in automatic. The second puts the controller on manual. The setpoint (SP), process variable (PV), and controller output (OP) signals are displayed in the bottom three bar charts, with numerical values given in the boxes. 

Fig. 19.2 Flow chart of environmental control of spawning in Nereis. Timing is used to describe factors influencing the maturation of a population Zeitgeber is the terminus used to describe the factors controlling the date and location of the reproductive event pheromone boxes show involvement of the chemical signals. Reproduced from Hardege et al. (1998) with kind permission from Ecoscience, Kanada...

The data in Fig. 6 are described according to how it is to be plotted. Values and processed data from two tests with different operators are indicated. Column 1 shows the four Cm controls, the mean value calculated from these four controls in any single plate, and the SD of the data. The second column shows the data from a test involving a single plate. The mean value (0.78) and the SD (0.03) are put into relevant boxes after their calculation. These are plotted on the DDD charts (gray shaded boxes). The date and operator are added. The SDC value is calculated for the sum of all the mean values on all plates in a given test (in this case 1 plate so that SDC data are identical to the DDD data). 

There were, however, some convincing examples of major improvements within the run chart data collected locally some of the data capture was clearly both sustained and controlled (Box 19.4). For instance, patients received correctly timed antibiotics before surgery and the introduction of a care bundle in one site significantly reduced the incidence of ventilator associated pneumonia. In patients on mechanical ventilation, the cumulative risk of pneumonia increases with the duration of ventilation. This infection has serious potential complications and a high mortality rate, so improvement in the reliability of the care delivered has important implications. 

FIGURE 5 (Top) Side and (bottom) plan views of a quenched-flow apparatus. Key RES, reservoirs (three) DS, drive syringes (three) MS, microswitch R, rack P, pinion M, motor Tl, thermo-stating fluid inlet TO, outlet M1, first mixer M2, second mixer Q, quartz windows (two) W, waste outlet BN, brass nut (three) PS, motor power supply L, lamp MO, monochromator FL, focusing lens PM, photomultiplier tube MA, milliammeter CB, control box CRO, cathode-ray oscilloscope DR, data recorder CR, chart recorder 1-6, taps shaded area, PTFE blocks. [From Goodman, R D., Kemp, T. J., and Pinot de Moira, P. (1981). J. Chem. Soc., Perkin Trans. 2,1221.]... 

The control room is also equipped with a temperature console where as many as 140 temperature points in the cold boxes can be read. Any 12 of these points can be recorded continuously and give us the means to follow and chart dynamic conditions of plant components. In addition to controls, the graphic panel has a number of flow recording devices, which make it possible to make up daily material balances and production records of the plant. 

Figure 11.11 Flow chart for the self-consistent construction of a CE Hamiltonian, (a) Initial input data from DFT and information about all possible clusters on a lattice L form the initial setup, (b) Some clusters C are chosen and the CE sum is fitted to the energies of the input structures

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