This article discusses passages in the works of Greek and Roman writers, from Homer to the Church Fathers and Procopius, in which the seaside is a place of carefree play, those in which looking at the sea seems to have a good influence on the human mind, those in which walking on the shore is an opportunity for a philosophical dispute, and those in which pleasure is derived from being alone near the sea.
The paper presents some aspects of a development project related to Industry 4.0 that was executed at Nemak, a leading manufacturer of the aluminium castings for the automotive industry, in its high pressure die casting foundry in Poland. The developed data analytics system aims at predicting the casting quality basing on the production data. The objective is to use these data for optimizing process parameters to raise the products’ quality as well as to improve the productivity. Characterization of the production data including the recorded process parameters and the role of mechanical properties of the castings as the process outputs is presented. The system incorporates advanced data analytics and computation tools based on the analysis of variance (ANOVA) and applying an MS Excel platform. It enables the foundry engineers and operators finding the most efficient process variables to ensure high mechanical properties of the aluminium engine block castings. The main features of the system are explained and illustrated by appropriate graphs. Chances and threats connected with applications of the data-driven modelling in die casting are discussed.
Statistical Process Control (SPC) based on the Shewhart’s type control charts, is widely used in contemporary manufacturing industry, including many foundries. The main steps include process monitoring, detection the out-of-control signals, identification and removal of their causes. Finding the root causes of the process faults is often a difficult task and can be supported by various tools, including datadriven mathematical models. In the present paper a novel approach to statistical control of ductile iron melting process is proposed. It is aimed at development of methodologies suitable for effective finding the causes of the out-of-control signals in the process outputs, defined as ultimate tensile strength (Rm) and elongation (A5), based mainly on chemical composition of the alloy. The methodologies are tested and presented using several real foundry data sets. First, correlations between standard abnormal output patterns (i.e. out-of-control signals) and corresponding inputs patterns are found, basing on the detection of similar patterns and similar shapes of the run charts of the chemical elements contents. It was found that in a significant number of cases there was no clear indication of the correlation, which can be attributed either to the complex, simultaneous action of several chemical elements or to the causes related to other process variables, including melting, inoculation, spheroidization and pouring parameters as well as the human errors. A conception of the methodology based on simulation of the process using advanced input - output regression modelling is presented. The preliminary tests have showed that it can be a useful tool in the process control and is worth further development. The results obtained in the present study may not only be applied to the ductile iron process but they can be also utilized in statistical quality control of a wide range of different discrete processes.
We propose a class of m-crane control systems, that generalizes two- and three-dimensional crane systems. We prove that each representant of the described class is feedback equivalent to the second order chained form with drift. In consequence, we prove that it is differentially flat. Then we investigate its control properties and derive a control law for tracking control problem.
The paper undertakes an important topic of evaluation of effectiveness of SCADA (Supervisory Control and Data Acquisition) systems, used for monitoring and control of selected processing parameters of classic green sands used in foundry. Main focus was put on process studies of properties of so-called 1st generation molding sands in the respect of their preparation process. Possible methods of control of this processing are presented, with consideration of application of fresh raw materials, return sand (regenerate) and water. The studies conducted in one of European foundries were aimed at pointing out how much application of new, automated plant of sand processing incorporating the SCADA systems allows stabilizing results of measurement of selected sand parameters after its mixing. The studies concerned two comparative periods of time, before an implementation of the automated devices for green sands processing (ASMS - Automatic Sand Measurement System and MCM – Main Control Module) and after the implementation. Results of measurement of selected sand properties after implementation of the ASMS were also evaluated and compared with testing studies conducted periodically in laboratory.
Simulation software can be used not only for checking the correctness of a particular design but also for finding rules which could be used in majority of future designs. In the present work the recommendations for optimal distance between a side feeder and a casting wall were formulated. The shrinkage problems with application of side feeders may arise from overheating of the moulding sand layer between casting wall and the feeder in case the neck is too short as well as formation of a hot spot at the junction of the neck and the casting. A large number of simulations using commercial software were carried out, in which the main independent variables were: the feeder’s neck length, type and geometry of the feeder, as well as geometry and material of the casting. It was found that the shrinkage defects do not appear for tubular castings, whereas for flat walled castings the neck length and the feeders’ geometry are important parameters to be set properly in order to avoid the shrinkage defects. The rules for optimal lengths were found using the Rough Sets Theory approach, separately for traditional and exothermic feeders.