A new version of the JM-SPC computer program written by J. Mutwil in Delphi for statistical control of production processes is presented. All changes have been by users suggestions caused. For the attribute valued data type most of new features have been joined to data introducing option. In this way the program allows to consider a wider data spectrum. Usefulness of the introduced solutions for statistical analysis of the attribute valued data type gained from real processes has been presented on the example of Al-Si high-pressure die casting production. The analysis refers to a serial produced casting and includes: 1) the analysis of defect fraction in sample (by using the p-chart), 2) the analysis of relative differences in importance of each defects categories (by using of the Pareto diagram).
2
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
Usefulness of the JM-SPC computer program for a statistical analysis of variable valued data proceeded from an Al-Si high-pressure die casting production processes was examined. An analysis subject were results of dimensional measurement of 16 casting dimensions systematically controlled on coordinate-measuring machine. For analysis two criterion have been used: 1) X-s control chart and the performance indicator of processes by using of two commonly used indices: potential process capability index (Cp) and process capability index (Cpk).
3
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
Usefulness of newest version of the JM-SPC computer program for a statistical analysis of production processes was examined. An analysis subject were results of measurements of 16 geometrical features of an Al-Si high-pressure die casting systematically controlled after machining on a coordinate-measuring machine. For analysis two criterion have been used: 1) Xave control chart and 2) a performance indicator of processes expressed by two commonly used indices: potential process capability index (Cp) and process capability index (Cpk).
4
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
A computer program written by author in Delphi for statistical control of production processes is presented. The JM-SPC program can be used for both the variable valued and the attribute valued data type. The data are introduced manually into table (up to 20 columns; up to 10000 rows). The option of data introducing is with some function equipped, which make this process very easy. The data analysis option offer many of analytical techniques. For variable valued data sets following control tools are available: individual values chart, average values chart, moving average values chart, exponentially moving average values chart, median values chart, range chart, standard deviation chart. Also two-signal control charts are available, for example: X-R, X-S, Me-R, Me-S. For variable valued data the performance of processes can be evaluated by using of two commonly used indices: potential process capability index (Cp) and process capability index (Cpk). For the attribute valued data type the user can select: p- and np-chart, c- and u-chart, Pareto diagram. Application of JM-SPC program for statistical analysis of real processes has been presented on the example of Al-Si high-pressure die casting production. For example of production of two different frame castings following analyses have been conducted: 1) the analysis of defect fraction in sample (by using the p-chart), 2) the analysis of relative differences in importance of each defects categories (by using of the Pareto diagram).
5
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
A problem of splinter formation during machining the AC47000 alloy high pressure die casting has been experimental investigated. In order to establish the reason of this occurrence a set of 200 high pressure die casting of the tensile strength samples have been prepared. The tensile tests were carried out using a Zwick Z050 universal testing machine. JM-SPC program has been used for statistical analysis of test results. A large variability of tensile strength results has been found. In order to find the reason of this variability the fracture surface investigations (macrographs for all of samples and SEM micrographs for chosen samples) have been carried out. It has been establish that in all cases a significant decrease of tensile strength was caused by presence of inclusions or porosity.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.