Control of the technological processes of coal enrichment takes place in the presence of wide disturbances. Thus, one of the basic tasks of the coal enrichment process control systems is the stabilization of coal quality parameters at a preset level. An important problem is the choice of the controller which is robust for a variety of disturbances. The tuning of the controller parameters is no less important in the control process . Many methods of tuning the controller use the dynamic characteristics of the controlled process (dynamic model of the controlled object). Based on many studies it was found that the dynamics of many processes of coal enrichment can be represented by a dynamic model with properties of the inertial element with a time delay. The identification of object parameters (including the time constant) in industrial conditions is usually performed during normal operation (with the influence of disturbances) from this reason, determined parameters of the dynamic model may differ from the parameters of the actual process. The control system with controller parameters tuned on the basis of such a model may not satisfy the assumed control quality requirements. In the paper, the analysis of the influence of changes in object model parameters in the course of the controlled value has been carried out. Research on the controller settings calculated according to parameters T and τ were carried out on objects with other parameter values. In the studies, a sensitivity analysis method was used. The sensitivity analysis for the three methods of tuning the PI controller for the coal enrichment processes control systems characterized by dynamic properties of the inertial element with time delay has been presented. Considerations are performed at various parameters of the object on the basis of the response of the control system for a constant value of set point. The assessment of considered tuning methods based on selected indices of control quality have been implemented.
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 the method of on-line diagnostics of the bed temperature controller for the fluidized bed boiler. Proposed solution is based on the methods of statistical process control. Detected decrease of the bed temperature control quality is used to activate the controller self-tuning procedure. The algorithm that provides optimal tuning of the bed temperature controller is also proposed. The results of experimental verification of the presented method is attached. Experimental studies were carried out using the 2 MW bubbling fluidized bed boiler.
The goal of the proposed computational model was to evaluate the dynamical properties of air gauges in order to exploit them in such industrial applications as in-process control, form deviation measurement, dynamical measurement. The model is based on Reynolds equations complemented by the k-ε turbulence model. The boundary conditions were set in different areas (axis of the chamber, side surfaces, inlet pipeline and outlet cross-section) as Dirichlet's and Neumann's ones. The TDMA method was applied and the efficiency of the calculations was increased due to the "line-by-line" procedure. The proposed model proved to be accurate and useful for non-stationary two-dimensional flow through the air gauge measuring chamber.
In the article, the authors analyze and discuss several models used to the calculation of air gauge characteristics. The model based on the actual mass flow (which is smaller than the theoretical one) was proposed, too. Calculations have been performed with a dedicated software with the second critical parameters included. The air gauge static characteristics calculated with 6 different models were compared with the experimental data. It appeared that the second critical parameters model (SCP) provided the characteristics close to the experimental ones, with an error of ca. 3% within the air gauge measuring range.
This study presents cause-effect dependencies between inputs and outputs of business transitions that are software objects designed for processing information-decision state variables in integrated enterprise process control (EntPC) systems. Business transitions are elementary components of controlling units in enterprise processes that have been defined as self-controlling, generalized business processes, which may serve not only as business processes but also as business systems or their roles. Business events, which have zero durations by definition, are interpreted as executions of business actions that are main operations of business transitions. Any ordered set of business actions, performed in the controlling unit of a given enterprise process and attributed to the same discrete-time instant, is referred to as ‘the information-decision process’. The i-d processes may be substituted by managerial business processes, performed on the lower organizational level, where durations of activity executions are greater than zero, but discrete-time periods are considerably shorter. In such a case, procedures of business actions are performed by corresponding activities of managerial processes, but on the level of business transitions the durations of their executions are imperceptible, and many different business events may occur at the same discrete-time instant. It has been demonstrated in the paper how to control business actions to ensure that a given i-d state variable may not change more than once at a given instant. Furthermore, the rules of designing the i-d process structures, which prevent random changes of transitory states, have been presented.
The dynamics of the turning process of a thin-walled cylinder in manufacturing is modeled using flexible multibody system theory. The obtained model is time varying due to workpiece rotation and tool feed and retarded, due to repeated cutting of the same surface. Instabilities can occur due to these consecutive cuts that must be avoided in practical application because of the detrimental effects on workpiece, tool and possibly the machine. Neglecting the small feed, the stability of the resulting periodic system with time-delay can be analyzed using the semi-discretization method. The use of an adaptronic tool holder comprising actuators and sensors to improve the dynamic stability is then investigated. Different control concepts, two collocated and two model-based, are implemented in simulation and tuned to increase the domain of stable cutting. Cutting of a moderately thin workpiece exhibits instabilities mainly due to tool vibration. In this case, the stability boundary can be significantly improved. When the instability is due to workpiece vibration, the collocated concepts fail completely. Model based concepts can still obtain some improvements, but are sensitive to modeling errors in the coupling of workpiece and tool.
Compared with the robots, humans can learn to perform various contact tasks in unstructured environments by modulating arm impedance characteristics. In this article, we consider endowing this compliant ability to the industrial robots to effectively learn to perform repetitive force-sensitive tasks. Current learning impedance control methods usually suffer from inefficiency. This paper establishes an efficient variable impedance control method. To improve the learning efficiency, we employ the probabilistic Gaussian process model as the transition dynamics of the system for internal simulation, permitting long-term inference and planning in a Bayesian manner. Then, the optimal impedance regulation strategy is searched using a model-based reinforcement learning algorithm. The effectiveness and efficiency of the proposed method are verified through force control tasks using a 6-DoFs Reinovo industrial manipulator.
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).
In this work problems associated with requirements related to pollution emissions in compliance with more restrictive standards, low-emission combustion technology, technical realization of the monitoring system as well as algorithms allowing combustion process diagnostics are discussed. Results of semi-industrial laboratory facility and industrial (power station) research are presented as well as the possibility of application of information obtained from the optical fibre monitoring system for combustion process control. Moreover, directions of further research aimed to limit combustion process environmental negative effects are presented.
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.
The proportional-integral-derivative (PID) controllers have experienced series of structural modifications and improvements. Example of such modifications are set-point weighting and fractional ordering. While the former is to achieve two-degree-of-freedom (2DOF) ability of set-point tracking and disturbance rejection, the latter is to ensure smooth control action. Therefore, this paper reviews various forms of PID controllers and provides a comparative analysis of 2DOF PID and 2DOF fractional order PID (FOPID) controllers. The paper also discusses the conversion of one PID form to another. For the comparative analysis of the various controllers, a class of unstable systems are considered. Simulation result shows that in most cases the conversion from one form to another does not significantly affect the performance of the system. It is also observed that the 2DOF controllers (2DOF PID and 2DOF FOPID) improved significantly the performance of the ordinary PID controllers.
There exist numerous modelling techniques and representation methods for digital control algorithms, aimed to achieve required system or process parameters, e.g. precision of process modelling, control quality, fulfilling the time constrains, optimisation of consumption of system resources, or achieving a trade-off between number of parameters. This work illustrates usage of Finite State Machines (FSM) modelling technique to solve a control problem with parameterized external variables. The structure of this work comprises six elements. The FSM is presented in brief and discrete control algorithm modelling is discussed. The modelled object and control problem is described and variables are identified. The FSM model is presented and control algorithm is described. The parameterization problem is identified and addressed, and the implementation in PLC programming LAD language is presented. Finally, the conclusion is given and future work areas are identified.
The paper provides statistical analysis of the photographs of four various granular materials (peas, pellets, triticale, wood chips). For analysis, the (parametric) ANOVA and the (nonparametric) Kruskal-Wallis tests were applied. Additionally, the (parametric) two-sample t-test and (non-parametric) Wilcoxon Rank-Sum Test for pairwise comparisons were performed. In each case, the Bonferroni correction was used. The analysis shows a statistical evidence of the presence of differences between the respective average discrete pixel intensity distributions (PID), induced by the histograms in each group of photos, which cannot be explained only by the existing differences among single granules of different materials. The proposed approach may contribute to the development of a fast inspection method for comparison and discrimination of granular materials differing from the reference material, in the production process.
Achieving control of coating thickness in foundry moulds is needed in order to guarantee uniform properties of the mould but also to achieve control of drying time. Since drying time of water based coatings is heavily dependent on the amount of water present in the coating layer, a stable coating process is prerequisite for a stable drying process. In this study, we analyse the effect of different variables on the coating layer properties. We start by considering four critical variables identified in a previous study such as sand compaction, coating density, dipping time and gravity and then we add centre points to the original experimental plans to identify possible non-linear effects and variation in process stability. Finally, we investigate the relation between coating penetration (a variable that is relatively simple to measure in production) and other coating layer thickness properties (relevant for the drying process design). Correlations are found and equations are provided. In particular it is found that water thickness can be directly correlated to penetration with a simple linear equation and without the need to account for other variables.
The effects of different types of process control agents (PCA) on the microstructure evolution of Ni-based oxide dispersion-strengthened superalloy have been investigated. Alloy synthesis was performed on elemental powders having a nominal composition of Ni-15Cr-4.5Al-4W-2.5Ti-2Mo-2Ta-0.15Zr-1.1Y2O3 in wt % using high energy ball milling for 5 h. The prepared powders are consolidated by spark plasma sintering at 1000oC. Results indicated that the powder ball-milled with ethanol as PCA showed large particle size, low carbon content and homogeneous distribution of elemental powders compared with the powder by stearic acid. The sintered alloy prepared by ethanol as PCA exhibited a homogeneous microstructure with fine precipitates at the grain boundaries. The microstructural characteristics have been discussed on the basis of function of the PCA.
The theoretical analysis of the charge exchange process in a spark ignition engine has been presented. This process has significant impact on the effectiveness of engine operation because it is related to the necessity of overcoming the flow resistance, followed by the necessity of doing a work, so-called the charge exchange work. The flow resistance caused by the throttling valve is especially high during the part load operation. The open Atkinson-Miller cycle has been assumed as a model of processes taking place in the engine. Using fully variable inlet valve timing the A-M cycle can be realized according to two systems: system with late inlet valve closing and system with early inlet valve closing. The systems have been analysed individually and comparatively with the open Seiliger-Sabathe cycle which is a theoretical cycle for the classical throttle governing of the engine load. Benefits resulting from application of the systems with independent inlet valve control have been assessed on the basis of the selected parameters: fuel dose, cycle work, charge exchange work and a cycle efficiency. The use of the analysed systems to governing of the SI engine load will enable to eliminate a throttling valve from the system inlet and reduce the charge exchange work, especially within the range of part load operation.
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.