Studies were conducted on a zinc coating produced on the surface of ductile iron grade EN-GJS-500-7 to determine the eutectic grain effect. For this purpose, castings with a wall thickness of 5 to 30 mm were made and the resulting structure was examined. To obtain a homogeneous metal matrix, samples were subjected to a ferritising annealing treatment. To enlarge the reaction surface, the top layer was removed from casting by machining. Then hot dip galvanising treatment was performed at 450°C to capture the kinetics of growth of the zinc coating (in the period from 60 to 600 seconds). Analysing the test results it was found that within the same time of hot dip galvanising, the differences in the resulting zinc coating thickness on samples taken from castings with different wall cross-sections were small but could, particularly for shorter times of treatment, reduce the continuity of the alloyed layer of the zinc coating.
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In the work, the system analysis in the foundry where the quality management system has been implemented was described. The generalized model of the foundry's production system was presented taking the company's surrounding and process attitude into account.
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In recent years a rapid development of a new, interdisciplinary knowledge area, called data mining, is observed. Its main task is extracting useful information from previously collected large amount of data. The main possibilities and potential applications of data mining in manufacturing industry are characterized. The main types of data mining techniques are briefly discussed, including statistical, artificial intelligence, data base and visualization tools. The statistical methods and visualization methods are presented in more detail, showing their general possibilities, advantages as well as characteristic examples of applications in foundry production. Results of the author's research are presented, aimed at validation of selected statistical tools which can be easily and effectively used in manufacturing industry. A performance analysis of ANOVA and contingency tables based methods, dedicated for determination of the most significant process parameters as well as for detection of possible interactions among them, has been made. Several numerical tests have been performed using simulated data sets, with assumed hidden relationships as well some real data, related to the strength of ductile cast iron, collected in a foundry. It is concluded that the statistical methods offer relatively easy and fairly reliable tools for extraction of that type of knowledge about foundry manufacturing processes. However, further research is needed, aimed at explanation of some imperfections of the investigated tools as well assessment of their validity for more complex tasks.
The FMEA (Failure Mode and Effects Analysis) method consists in analysis of failure modes and evaluation of their effects based on determination of cause-effect relationships for formation of possible product or process defects. Identified irregularities which occur during the production process of piston castings for internal combustion engines were ordered according to their failure rates, and using Pareto-Lorenz analysis, their per cent and cumulated shares were determined. The assessments of risk of defects occurrence and their causes were carried out in ten-point scale of integers, while taking three following criteria into account: significance of effects of the defect occurrence (LPZ), defect occurrence probability (LPW) and detectability of the defect found (LPO). A product of these quantities constituted the risk score index connected with a failure occurrence (a so-called “priority number,” LPR). Based on the observations of the piston casting process and on the knowledge of production supervisors, a set of corrective actions was developed and the FMEA was carried out again. It was shown that the proposed improvements reduce the risk of occurrence of process failures significantly, translating into a decrease in defects and irregularities during the production of piston castings for internal combustion engines.
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The first part of the study describes the methods used to determine Weibull modulus and the related reliability index of hypereutectic silumins containing about 17% Si, assigned for manufacture of high-duty castings to be used in automotive applications and aviation. The second part of the study discusses the importance of chemical composition, including the additions of 3% Cu, 1,5% Ni and 1,5% Mg, while in the third part attention was focussed on the effect of process history, including mould type (sand or metal) as well as the inoculation process and heat treatment (solutioning and ageing) applied to the cast AlSi17Cu3Mg1,5Ni1,5 alloy, on the run of Weibull distribution function and reliability index calculated for the tensile strength Rm of the investigated alloys.
The authors have made an attempt to enrich the knowledge about the influence of wax pattern washing process and its influence on the quality of the shell prime coat. Two types of wax were investigated: A7Fr/60 and KC2690. A7Fr60 is used for pattern fabrication, while KC2690 is typical sprue wax. The goal of work was to establish wax solubility accuracy in Trisol 60 Plus and Houghto Clean 530 versus time and influence of dipping time to wax samples surface quality. Additionally, after exposition of wax samples, their surface morphology was characterized with the use of laser profilometry and surface roughness measurement. The quality of formed prime coat was established by X-ray tomography. The measurement of wetting angle of the wax by binder was conducted. The results have shown that the main factor which influences the quality of the prime coat is surface wettability rather than wax surface roughness.
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