Excel control charts

This shde contains hnks to EXCEL-sheets from ExcelKontrol 2.1. This sheets can be nsed to mn control charts with checks for out-of-control situations and with graphical displays. In the electronic material you will find the whole zipped program, which also allows target control charts. 

The software EXCELKONTROL 2.1 is an EXCEL -programme for control charts, for which Microsoft EXCEL 2000 (or later) is required. 

Figure 5.6 Example of output from the SPC XL control chart plotting MS Excel add-in.

The intent in this chapter is not to present in great detail the mathematics behind the statistical methods discussed. An excellent reference manual assembled by the Automotive Industry Action Group (AIAG), Fundamental Statistical Process Control, details process control systems, variation, action on special or common causes, process control and capability, process improvement, control charting, and benefits derived from using each of these tools. Reprinted with permission from the Fundamental Statistacal Process Control Reference Manual (Chrysler, Ford, General Motors Supplier uality Requirements Task Force , Measurement Systems Analysis, MSA Second Edition, 1995, ASQC Press. 

Control charts are an excellent analysis tool to both monitor and improve in-process performance during process development and later during production, where it is desired to follow process characteristics over time within batches or runs. The most common examples of tablet process characteristics that are measured in-process are weight, thickness, and hardness. The parameters measured need to be controllable so that adjustments can be made. During the initial runs, it is desirable to limit process adjustments to a minimum to observe the process in its natural state. Any adjustments made should be recorded and explained. Out-oflimit results should never be removed prior to performing a process capability analysis. If special cause variation is detected, then process improvements should be made to eliminate the special cause variation. 

Accreditation is mainly concerned with routine tests or analysis. It includes the use of reference materials (e.g. LRMs or in-house RMs) for control charts which are hardly available on the market it is hence timely to start producing RMs for routine analysis in high quantities and at low cost for those measurements which have a major economic importance in relation to social and environmental implications as mentioned above, such a production should follow minimum quality requirements to avoid commercialisation and use of bad quality products which would only add to confusion. There is obviously a need to focus/consolidate technical expertise for CRM production in a few centres of excellence and actions should be stimulated to create a possible network of CRM producers which should be composed of practitioners , i.e. experts in both the production of CRMs and the respective analytical fields, so that questions arising from routine laboratories could be readily and practically responded to [44] while efforts made by metrological laboratories to create a system of metrology in chemistry are certainly important, these are far remote from the needs of routine laboratories which, however, carry out the vast majority of analytical work worldwide. Pragmatism should... 

An internal quality control standard with an analyte concentration of 50 mg kg is analysed in a laboratory for 25 consecutive days, the sample size being four on each day. The results are given in Table 4.2, which is in the form of an Excel spreadsheet. Determine the value of R and hence plot control charts for the mean and range of the laboratory analyses. 

Neave and Wheeler [12] present an excellent discussion on the proper use of control charts and show how the notion of probability introduced into the application by statisticians since its inception by Shewhart has actually promulgated false notions about Shewhart s original intent when he stated, We are not concerned with the functional form of the universe, but merely with the assumption that a universe exists. ... 

The continuously analysis and control of the manufacturing process is the precondition for the obtaining of excellent products. The two established methods are quality control charts and the relayed process capability indices. Quality Control Charts (QCC) can be used without an exact knowledge of the characteristic distribution model and are useful in the analysis of manufacturing risks. QCCs show the mean and scattering of each product characteristic in relation to the given tolerance areas. Furthermore, alert and intervention limits can be adapted inside QCC, if needed. This method is an industrial standard, further explanations can be found in (Timischl 2002). It is possible... 

A coordinated time base is essential. This simple requirement is not necessarily trivial on-board ship. Many analytical instruments and recording devices keep time by counting electrical cycles. This timekeeping method uses the excellent frequency control commonly found in U.S. electric power systems. At sea, however, frequency drifts, thus, clocks drift too. If all laboratory data were logged immediately into a computer data base, it would be relatively easy to coordinate computer time and real time. However, the situation can be confused when signals first go to strip-chart recorders for subsequent evaluation and then transfer to the general files. Provision then must be made for regular time marks on the chart. 

A flow chart for the procedures is shown in Figure 6. The main control program for the automated assay was programmed with Visual Basic . The e-sco unit was remotely controlled through its proprietary ActiveX interface. An EXCEL template file contained all relevant information about the sample and the desired automatic processing (number of samples, spectrum file names, peak position and line width). At the end of the assay, the measurement results and signal intensity plots are generated automatically. 

The VSM has given the team an excellent tool for understanding the materials and information flow. Sometimes, however, this is not sufficient for environments where the information flow is very complex. In these cases it would be valuable to create a systems flow chart so that more of the information process could be detailed out. The systems flow chart was needed for the Z Base process, and a very summary example of the flow chart can be seen in Chart 8.4. The actual flow chart had several dozen information flow lines in it, and about one-third of these lines were determined to be for control purposes or for error recovery purposes. The goal of one of the events was to eliminate the non-value-added information flow lines that existed. 

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