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Mathematical Model of Dynamic Work Conditions in the Measuring Chamber of an Air Gauge

Czeslaw Jermak Andrzej Spyra Miroslaw Rucki

Metrology and Measurement Systems | 2012 | No 1 | 29-38 | DOI: 10.2478/v10178-012-0002-2

Keywords air gauges dynamic measurement in-process control

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Abstract

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.

Authors and Affiliations

Czeslaw Jermak

Andrzej Spyra

Miroslaw Rucki

Comparison of the models of the air gauge static characteristics

Czeslaw Janusz Jermak Ryszard Piątkowski Janusz Dereżyński Miroslaw Rucki

Archive of Mechanical Engineering | 2017 | vol. 64 | No 1 | 93-110 | DOI: 10.1515/meceng-2017-0006

Keywords air gauges dynamic measurement in-process control

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Abstract

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.

Bibliography

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Authors and Affiliations

Czeslaw Janusz Jermak

1

Ryszard Piątkowski

2

Janusz Dereżyński

1

Miroslaw Rucki

3

Institute of Mechanical Technology, Poznan University of Technology, Poland
Chair of Thermal Engineering, Poznan Univesity of Technology, Poland
Faculty of Mechanical Engineering, Kazimierz Pulaski University of Technology and Humanities in Radom, Poland

Effectiveness of Dynamic Matrix Control algorithm with Laguerre functions

Piotr Tatjewski

Archives of Control Sciences | 2021 | vol. 31 | No 4 | 795-814 | DOI: 10.24425/acs.2021.139731

Keywords process control model predictive control DMC algorithm Laguerre functions

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Abstract

The paper is concerned with the presentation and analysis of the Dynamic Matrix Control (DMC) model predictive control algorithm with the representation of the process input trajectories by parametrised sums of Laguerre functions. First the formulation of the DMCL (DMC with Laguerre functions) algorithm is presented. The algorithm differs from the standard DMC one in the formulation of the decision variables of the optimization problem – coefficients of approximations by the Laguerre functions instead of control input values are these variables. Then the DMCL algorithm is applied to two multivariable benchmark problems to investigate properties of the algorithm and to provide a concise comparison with the standard DMC one. The problems with difficult dynamics are selected, which usually leads to longer prediction and control horizons. Benefits from using Laguerre functions were shown, especially evident for smaller sampling intervals.

Bibliography

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Authors and Affiliations

Piotr Tatjewski

1

Warsaw University of Technology, Nowowiejska15/19, 00-665 Warszawa, Poland

Analysis and Perspectives on Multivariate Statistical Process Control Charts used in the Industrial Sector: a Systematic Literature Review

Renan Mitsuo Ueda Ìcaro Romolo Sousa Agostino Adriano Mendonça Souza

Management and Production Engineering Review | 2022 | vol. 13 | No 2 | 48-60 | DOI: 10.24425/mper.2022.142054

Keywords Multivariate statistical process control Systematic review control charts manufacturing Industrial

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Abstract

The objective of this article is to carry out a systematic review of the literature on multivariate statistical process control (MSPC) charts used in industrial processes. The systematic review was based on articles published via Web of Science and Scopus in the last 10 years, from 2010 to 2020, with 51 articles on the theme identified. This article sought to identify in which industry the MSPC charts are most applied, the types of multivariate control charts used and probability distributions adopted, as well as pointing out the gaps and future directions of research. The most commonly represented industry was electronics, featuring in approximately 25% of the articles. The MSPC chart most frequently applied in the industrial sector was the traditional T2 of Harold Hotelling (Hotelling, 1947), found in 26.56% of the articles. Almost half of the combinations between the probabilistic distribution and the multivariate control graphs, i.e., 49.4%, considered that the data followed a normal distribution. Gaps and future directions for research on the topic are presented at the end.

Authors and Affiliations

Renan Mitsuo Ueda

1

Ìcaro Romolo Sousa Agostino

2

Adriano Mendonça Souza

1

Federal University of Santa Maria, Brazil
Federal University of Santa Catarina, Brazil

Self-improving Q-learning based controller for a class of dynamical processes

Jakub Musial Krzysztof Stebel Jacek Czeczot

Archives of Control Sciences | 2021 | vol. 31 | No 3 | 527-551 | DOI: 10.24425/acs.2021.138691

Keywords process control Q-learning algorithm reinforcement learning intelligent control on-line learning

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Abstract

This paper presents how Q-learning algorithm can be applied as a general-purpose selfimproving controller for use in industrial automation as a substitute for conventional PI controller implemented without proper tuning. Traditional Q-learning approach is redefined to better fit the applications in practical control loops, including new definition of the goal state by the closed loop reference trajectory and discretization of state space and accessible actions (manipulating variables). Properties of Q-learning algorithm are investigated in terms of practical applicability with a special emphasis on initializing of Q-matrix based only on preliminary PI tunings to ensure bumpless switching between existing controller and replacing Q-learning algorithm. A general approach for design of Q-matrix and learning policy is suggested and the concept is systematically validated by simulation in the application to control two examples of processes exhibiting first order dynamics and oscillatory second order dynamics. Results show that online learning using interaction with controlled process is possible and it ensures significant improvement in control performance compared to arbitrarily tuned PI controller.

Bibliography

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Authors and Affiliations

Jakub Musial

1

Krzysztof Stebel

1

Jacek Czeczot

1

Silesian University of Technology, Faculty of Automatic Control, Electronics and Computer Science, Department of Automatic Control and Robotics, 44-100 Gliwice, ul. Akademicka 16, Poland

The magnitude optimum design of the PI controller for plants with complex roots and dead time

Jan Cvejn

Archives of Control Sciences | 2022 | vol. 32 | No 1 | 5-35 | DOI: 10.24425/acs.2022.140862

Keywords dead time frequency response magnitude optimum PID controller process control stability margin

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Abstract

Analytical design of the PID-type controllers for linear plants based on the magnitude optimum criterion usually results in very good control quality and can be applied directly for high-order linear models with dead time, without need of any model reduction. This paper brings an analysis of properties of this tuning method in the case of the PI controller, which shows that it guarantees closed-loop stability and a large stability margin for stable linear plants without zeros, although there are limitations in the case of oscillating plants. In spite of the fact that the magnitude optimum criterion prescribes the closed-loop response only for low frequencies and the stability margin requirements are not explicitly included in the design objective, it reveals that proper open-loop behavior in the middle and high frequency ranges, decisive for the closed-loop stability and robustness, is ensured automatically for the considered class of linear systems if all damping ratios corresponding to poles of the plant transfer function without the dead-time term are sufficiently high.

Authors and Affiliations

Jan Cvejn

1

University of Pardubice, Faculty of Electrical Engineering and Informatics, Studentska 95, 532 10 Pardubice, Czech Republic

Methodology for Diagnosing the Causes of Die-Casting Defects, Based on Advanced Big Data Modelling

A. Okuniewska M.A. Perzyk J. Kozłowski

Archives of Foundry Engineering | 2021 | vo. 21 | No 4 | 103-109 | DOI: 10.24425/afe.2021.138687

Keywords fault diagnosis die casting process control Data analytics Application of information technology to the foundry industry

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Abstract

The purpose of this paper was to develop a methodology for diagnosing the causes of die-casting defects based on advanced modelling, to correctly diagnose and identify process parameters that have a significant impact on product defect generation, optimize the process parameters and rise the products’ quality, thereby improving the manufacturing process efficiency. The industrial data used for modelling came from foundry being a leading manufacturer of the high-pressure die-casting production process of aluminum cylinder blocks for the world's leading automotive brands. The paper presents some aspects related to data analytics in the era of Industry 4.0. and Smart Factory concepts. The methodology includes computation tools for advanced data analysis and modelling, such as ANOVA (analysis of variance), ANN (artificial neural networks) both applied on the Statistica platform, then gradient and evolutionary optimization methods applied in MS Excel program’s Solver add-in. The main features of the presented methodology are explained and presented in tables and illustrated with appropriate graphs. All opportunities and risks of implementing data-driven modelling systems in high-pressure die-casting processes have been considered.

Bibliography

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[6] Lewis, M. (2018). Seeing through the Cloud of Industry 4.0. In 73rd WFC, 23-27, (pp. 519-520). Krakow, Poland: Polish Foundrymen’s Association.
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[14] Adamane, A.R., Arnberg, L., Fiorese, E., Timelli, G., Bonollo, F. (2015). Influence of injection parameters on the porosity and tensile properties of high-pressure die cast Al-Si alloys: A Review. International Journal of Meterials. 9(1), 43-53.
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Authors and Affiliations

A. Okuniewska

1

M.A. Perzyk

1

J. Kozłowski

1

Institute of Manufacturing Technologies, Warsaw University of Technology, Narbutta 85, 02-524 Warsaw, Poland

Statistical process control of commercial force-sensing resistors

Carlos Andrés Palacio Gómez Leonel Paredes-Madrid Andrés Orlando Garzon

Metrology and Measurement Systems | 2022 | vol. 29 | No 3 | 469-481 | DOI: 10.24425/mms.2022.142267

Keywords sensing resistors (FSR) pressure sensor statistical process control hysteresis error drift error

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Abstract

The manufacturing and characterization of polymer nanocomposites is an active research trend nowadays. Nonetheless, statistical studies of polymer nanocomposites are not an easy task since they require several factors to consider, such as: large amount of samples manufactured from a standardized procedure and specialized equipment to address characterization tests in a repeatable fashion. In this manuscript, the experimental characterization of sensitivity, hysteresis error and drift error was carried out at multiple input voltages (��) for the following commercial brands of FSRs ( force sensing resistors): Interlink FSR402 and Peratech SP200-10 sensors. The quotient between the mean and the standard deviation was used to determine dispersion in the aforementioned metrics. It was found that a low mean value in an error metric is typically accompanied by a comparatively larger dispersion, and similarly, a large mean value for a given metric resulted in lower dispersion; this observation was held for both sensor brands under the entire range of input voltages. In regard to sensitivity, both sensors showed similar dispersion in sensitivity for the whole range of input voltages. Sensors’ characterization was carried out in a tailored test bench capable of handling up to 16 sensors simultaneously; this let us speed up the characterization process.

Authors and Affiliations

Carlos Andrés Palacio Gómez

1

Leonel Paredes-Madrid

2

Andrés Orlando Garzon

2

GIFAM Group, Universidad Antonio Nariño, Cra 7 No. 21-84, 150001 Tunja, Boyacá, Colombia
Universidad Católica de Colombia, Faculty of Engineering, Carrera 13 # 47-30, Bogota, Colombia

Solving the Problem of Discrete Process Control Synthesis Using Optimization on a Sliding Interval

Zhazira Julayeva Waldemar Wójcik Gulzhan Kashaganova Kulzhan Togzhanova Saken Mambetov

International Journal of Electronics and Telecommunications | 2023 | vol. 69 | No 2 | 383-389 | DOI: 10.24425/ijet.2023.144374

Keywords discrete process control optimization sliding interval closed loop control system equation of a closed loop system

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Abstract

The paper presents a solution to the problem of synthesis of control with respect to the sliding interval length for the optimization of a class of discrete linear multidimensional objects with a quadratic performance criterion. The equation of motion of a closed multidimensional discrete system in the general non-stationary case is derived based on the length of the optimization interval and their main properties. The closed-loop is fitted with a signal representing the predicted values averaged over the whole sliding interval of optimization with a certain weight. A problem with a sliding optimization interval may not require a real-time solution by means of a sequence of solutions on compressed intervals. Therefore, the study of control systems with optimization on a sliding interval is of undoubted interest for a number of practically important control problems.

Authors and Affiliations

Zhazira Julayeva

1

Waldemar Wójcik

2

Gulzhan Kashaganova

3

Kulzhan Togzhanova

4

Saken Mambetov

4

Academy of Logistics and Transport, Almaty Technological University, Almaty, Kazakhstan
Lublin University of Technology, Lublin, Poland
Turan University and Satbayev University, Almaty, Kazakhstan
Almaty Technological University, Almaty, Kazakhstan

Comparative Simulation of the Production Flow with the Implementation of Kanban and DBR

Klaudia Tomaszewska

Management and Production Engineering Review | 2023 | vol. 14 | No 2 | 79-87 | DOI: 10.24425/mper.2023.146025

Keywords Modeling for control optimization Real-time control process control Lean Manufacturing Theory of constraints

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Abstract

Currently, we live in a culture of being overly busy, but this does not translate into efficiency, speed of implementation of the actions taken. Enterprises are constantly looking for methods and tools to make them more efficient. The most popular method of production management is Lean Manufacturing, less known is Theory of Constraints. This work is a continuation of the research on the comparison of these methods with apply a computer simulation, which the analyzed production process in the selected enterprise, after 24 hours and week. An attempt was made to simplify the comparison of the methods based on the obtained simulation in terms of costs. In analyzed case, more advantageous solution is to use the DBR method. To produce various orders that do not require 100% production on the bottleneck position, the use of Kanban is a frequent practice as it provides greater flexibility in order execution.

Authors and Affiliations

Klaudia Tomaszewska

1

Faculty of Management Engineering, Bialystok University of Technology, Poland

Stochastic number of concrete families and the likelihood of such a value

Józef Jasiczak Marcin Kanoniczak Łukasz Smaga

Archives of Civil Engineering | 2022 | vol. 68 | No 1 | 27-44 | DOI: 10.24425/ace.2022.140154

Keywords compressive strength of concrete continuous concreting process control concrete family statistical method

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Abstract

Modern construction standards, both from the ACI, EN, ISO, as well as EC group, introduced numerous statistical procedures for the interpretation of concrete compressive strength results obtained on an ongoing basis (in the course of structure implementation), the values of which are subject to various impacts, e.g., arising from climatic conditions, manufacturing variability and component property variability, which are also described by specific random variables. Such an approach is a consequence of introducing the method of limit states in the calculations of building structures, which takes into account a set of various factors influencing structural safety. The term “concrete family” was also introduced, however, the principle of distributing the result or, even more so, the statistically significant size of results within a family was not specified. Deficiencies in the procedures were partially supplemented by the authors of the article, who published papers in the field of distributing results of strength test time series using the Pearson, ��-Student, and Mann–Whitney U tests. However, the publications of the authors define neither the size of obtained subset and their distribution nor the probability of their occurrence. This study fills this gap by showing the size of a statistically determined concrete family, with a defined distribution of the probability of its isolation.

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Authors and Affiliations

Józef Jasiczak

1

e-mail:

ORCID:

Marcin Kanoniczak

1

e-mail:

ORCID:

Łukasz Smaga

2

e-mail:

ORCID:

Poznan University of Technology, Faculty of Civil and Transport Engineering, Piotrowo 5, 60-965 Poznan, Poland
Adam Mickiewicz University, Faculty of Mathematics and Computer Science, 61-614 Poznan, Poland

1

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