The aim of the research was the evaluation of wastewater management in terms of stability and efficiency of wastewater treatment, using statistical quality control. For this purpose, the analysis of the operation and operation of the “Kujawy” Sewage Treatment Plant was made, which is one of the most important and largest sewage management facilities in the city of Cracow. This assessment was done using control charts x for 59 observations. The analysed research period covered the multi-year from 2012 to 2016. Five key pollutant indicators were used to evaluate the work of the tested object: BOD5, CODCr, total suspension, total nitrogen and total phosphorus. In the case of the majority of them, based on the analysis of control charts, full stability of their removal was found in the tested sewage management facility. The exception was total nitrogen, for which periods of disturbed stability of its disposal processes were noted. Analysis of the effectiveness of wastewater treatment showed each time that the required efficiency of reduction of the analysed pollution indicators in the “Kujawy” Sewage Treatment Plant was achieved.
The paper presents an analysis of SPC (Statistical Process Control) procedures usability in foundry engineering. The authors pay particular attention to the processes complexity and necessity of correct preparation of data acquisition procedures. Integration of SPC systems with existing IT solutions in area of aiding and assistance during the manufacturing process is important. For each particular foundry, methodology of selective SPC application needs to prepare for supervision and control of stability of manufacturing conditions, regarding specificity of data in particular “branches” of foundry production (Sands, Pouring, Metallurgy, Quality).
Statistical Process Control (SPC) based on the well known Shewhart control charts, is widely used in contemporary manufacturing industry, including many foundries. However, the classic SPC methods require that the measured quantities, e.g. process or product parameters, are not auto-correlated, i.e. their current values do not depend on the preceding ones. For the processes which do not obey this assumption the Special Cause Control (SCC) charts were proposed, utilizing the residual data obtained from the time-series analysis. In the present paper the results of application of SCC charts to a green sand processing system are presented. The tests, made on real industrial data collected in a big iron foundry, were aimed at the comparison of occurrences of out-of-control signals detected in the original data with those appeared in the residual data. It was found that application of the SCC charts reduces numbers of the signals in almost all cases It is concluded that it can be helpful in avoiding false signals, i.e. resulting from predictable factors.