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Prof. Dr. Katarzyna Antosz
Rzeszow University of Technology, Faculty of Mechanical Engineering and Aeronautics, Al. Powstancow Warszawy 12 35-959 Rzeszów, Poland

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0 Maintenance
0 Production Engineering
0 Decision Support Systems
0 systems reliability
0 lean maintenance

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Conference paper
Published: 17 June 2021 in Recent Advances in Computational Mechanics and Simulations
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Dynamic industrial data growth necessitates the development of several new concepts of these data analysis that will allow to select not only the right data, but also to apply appropriate methods in order to extract knowledge from them. For this purpose, the possible use of decision trees as a decision support tool for a machining process data analysis was discussed in this article. With the use of the generated decision rules, we identify parameters that affect the state of a blade (blunt, sharp). In consequence that makes it possible to predict its future state at specific values of the identified parameters. Decision trees enable the analyses of the importance of each variable for the dependent variable. This makes it possible to analyse how each individual parameter and the relationships between them affect the condition of a cutter blade. The results of variables importance for a decision tree analysis can be used to determine the most important input variables, while rejecting those which do not affect the condition of a cutter blade. The study offers some promising results. It is confirmed by the achieved prediction model quality indicators.

ACS Style

Katarzyna Antosz; Dariusz Mazurkiewicz; Edward Kozłowski; Jarosław Sęp; Tomasz Żabiński. Machining Process Time Series Data Analysis with a Decision Support Tool. Recent Advances in Computational Mechanics and Simulations 2021, 14 -27.

AMA Style

Katarzyna Antosz, Dariusz Mazurkiewicz, Edward Kozłowski, Jarosław Sęp, Tomasz Żabiński. Machining Process Time Series Data Analysis with a Decision Support Tool. Recent Advances in Computational Mechanics and Simulations. 2021; ():14-27.

Chicago/Turabian Style

Katarzyna Antosz; Dariusz Mazurkiewicz; Edward Kozłowski; Jarosław Sęp; Tomasz Żabiński. 2021. "Machining Process Time Series Data Analysis with a Decision Support Tool." Recent Advances in Computational Mechanics and Simulations , no. : 14-27.

Conference paper
Published: 26 May 2021 in Recent Advances in Computational Mechanics and Simulations
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Slide burnishing is one of the methods of metal processing that use the phenomenon of surface plastic cold deformation. This article presents the results of a study investigating the effect of slide burnishing on the surface roughness of 42CrMo4 steel shafts. The burnishing process was performed with the use of a polycrystalline diamond tip tool. Before burnishing, the samples were subjected to turning on the toolmaker’s lathe. Investigations were conducted based on PS/DS-P:Ha3 Hartley’s plan, which makes it possible to define the regression equation in the form of a second-degree polynomial. Moreover, the artificial neural network (ANN) models have been used to predict the surface roughness of shafts in the burnishing process. The input process parameters considered include the applied pressure, burnishing rate, and feed rate. In all analyzed burnishing cases, the value of the mean surface roughness was reduced. The differences between the experimental data and Hartley’s model do not exceed 24%. The best representation of Hartley’s model was obtained for the burnishing parameters: feed rate f = 0.32 mm/rev, applied pressure P = 130 N, and burnishing speed v = 180 rpm. ANN models were the best predictors of roller surface roughness of the shafts. With the Pearson’s correlation R2 coefficient = 0.99974, the values of prediction errors did not exceed 0.0016249.

ACS Style

Rafał Kluz; Tomasz Trzepiecinski; Magdalena Bucior; Katarzyna Antosz. Modelling of the Effect of Slide Burnishing on the Surface Roughness of 42CrMo4 Steel Shafts. Recent Advances in Computational Mechanics and Simulations 2021, 415 -424.

AMA Style

Rafał Kluz, Tomasz Trzepiecinski, Magdalena Bucior, Katarzyna Antosz. Modelling of the Effect of Slide Burnishing on the Surface Roughness of 42CrMo4 Steel Shafts. Recent Advances in Computational Mechanics and Simulations. 2021; ():415-424.

Chicago/Turabian Style

Rafał Kluz; Tomasz Trzepiecinski; Magdalena Bucior; Katarzyna Antosz. 2021. "Modelling of the Effect of Slide Burnishing on the Surface Roughness of 42CrMo4 Steel Shafts." Recent Advances in Computational Mechanics and Simulations , no. : 415-424.

Journal article
Published: 05 March 2021 in Energies
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This paper presents an empirical study on the impact of maintenance function on more sustainable manufacturing processes. The work methodology comprises four stages. At first, ten factors of maintenance activities from a sustainable manufacturing point of view were identified. Then, in the second stage, the matrix of crossed impact multiplications applied to a classification (MICMAC) was carried out to categorize these factors based on their influence and dependence values. In the third stage, the criteria for evaluation of maintenance factors were defined, then the fuzzy analytic hierarchy process (F-AHP) was applied to determine their relative weights. In the last stage, the results of MICMAC and F-AHP analyses were used as inputs for the fuzzy technique for order preference by similarity to ideal solution (F-TOPIS) to generate aggregate scores and selection of the most important maintenance factors that have an impact on sustainable manufacturing processes. A numerical example is provided to demonstrate the applicability of the approach. It was observed that factors “Implementation of preventive and prognostic service strategies”, “The usage of M&O data collection and processing systems”, and “Modernization of machines and devices” are the major factors that support the realization of sustainable manufacturing process challenges.

ACS Style

Małgorzata Jasiulewicz-Kaczmarek; Katarzyna Antosz; Ryszard Wyczółkowski; Dariusz Mazurkiewicz; Bo Sun; Cheng Qian; Yi Ren. Application of MICMAC, Fuzzy AHP, and Fuzzy TOPSIS for Evaluation of the Maintenance Factors Affecting Sustainable Manufacturing. Energies 2021, 14, 1436 .

AMA Style

Małgorzata Jasiulewicz-Kaczmarek, Katarzyna Antosz, Ryszard Wyczółkowski, Dariusz Mazurkiewicz, Bo Sun, Cheng Qian, Yi Ren. Application of MICMAC, Fuzzy AHP, and Fuzzy TOPSIS for Evaluation of the Maintenance Factors Affecting Sustainable Manufacturing. Energies. 2021; 14 (5):1436.

Chicago/Turabian Style

Małgorzata Jasiulewicz-Kaczmarek; Katarzyna Antosz; Ryszard Wyczółkowski; Dariusz Mazurkiewicz; Bo Sun; Cheng Qian; Yi Ren. 2021. "Application of MICMAC, Fuzzy AHP, and Fuzzy TOPSIS for Evaluation of the Maintenance Factors Affecting Sustainable Manufacturing." Energies 14, no. 5: 1436.

Journal article
Published: 02 March 2021 in Materials
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This article presents the results of tests aimed at determining the effect of slide burnishing parameters on the surface roughness of shafts made of 42CrMo4 heat-treatable steel. The burnishing process was carried out using tools with polycrystalline diamond and cemented carbide tips. Before burnishing, the samples were turned on a turning lathe to produce samples with an average surface roughness Ra = 2.6 µm. The investigations were carried out according to three-leveled Hartley’s poly selective quasi D (PS/DS-P: Ha3) plan, which enables a regression equation in the form of a second-order polynomial to be defined. Artificial neural network models were also used to predict the roughness of the surface of the shafts after slide burnishing. The input parameters of the process that were taken into account included the values of pressure, burnishing speed and feed rate. Overall, the burnishing process examined leads to a reduction in the value of the surface roughness described by the Ra parameter. The artificial neural networks with the best regression statistics predicted an average surface roughness of the shafts with R 2 = 0.987. The lowest root-mean-square error and mean absolute error were obtained with all the network structures analysed that were trained with the quasi Newton algorithm.

ACS Style

Rafał Kluz; Katarzyna Antosz; Tomasz Trzepieciński; Magdalena Bucior. Modelling the Influence of Slide Burnishing Parameters on the Surface Roughness of Shafts Made of 42CrMo4 Heat-Treatable Steel. Materials 2021, 14, 1175 .

AMA Style

Rafał Kluz, Katarzyna Antosz, Tomasz Trzepieciński, Magdalena Bucior. Modelling the Influence of Slide Burnishing Parameters on the Surface Roughness of Shafts Made of 42CrMo4 Heat-Treatable Steel. Materials. 2021; 14 (5):1175.

Chicago/Turabian Style

Rafał Kluz; Katarzyna Antosz; Tomasz Trzepieciński; Magdalena Bucior. 2021. "Modelling the Influence of Slide Burnishing Parameters on the Surface Roughness of Shafts Made of 42CrMo4 Heat-Treatable Steel." Materials 14, no. 5: 1175.

Journal article
Published: 08 February 2021 in Materials
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The influence of irradiation should be considered in fatigue reliability analyses of reactor structures under irradiation conditions. In this study, the effects of irradiation hardening and irradiation embrittlement on fatigue performance parameters were quantified and a fatigue life prediction model was developed. Based on this model, which takes into account the cumulative effect of a neutron dose, the total fatigue damage was calculated according to Miner’s linear cumulative damage law, and the reliability analysis was carried out using the Monte Carlo simulation method. The case results show that the fatigue life acquired by taking into account the cumulative effect of irradiation was reduced by 24.3% compared with that acquired without considering the irradiation effect. Irradiation led to the increase of the fatigue life at low strains and its decrease at high strains, which is in accordance with the findings of an irradiation fatigue test. The rate of increase in the fatigue life decreased gradually with the increase of the neutron dose. The irradiation performance parameters had a small influence on fatigue reliability, while the fatigue strength coefficient and the elastic modulus had a great influence on the fatigue reliability. Compared with the current method, which uses a high safety factor to determine design parameters, a fatigue reliability analysis method taking into account the cumulative effect of irradiation could be more accurate in the reliability analysis and life prediction of reactor structures.

ACS Style

Bo Sun; Junlin Pan; Zili Wang; Yi Ren; Dariusz Mazurkiewicz; Małgorzata Jasiulewicz-Kaczmarek; Katarzyna Antosz. Fatigue Reliability Analysis Method of Reactor Structure Considering Cumulative Effect of Irradiation. Materials 2021, 14, 801 .

AMA Style

Bo Sun, Junlin Pan, Zili Wang, Yi Ren, Dariusz Mazurkiewicz, Małgorzata Jasiulewicz-Kaczmarek, Katarzyna Antosz. Fatigue Reliability Analysis Method of Reactor Structure Considering Cumulative Effect of Irradiation. Materials. 2021; 14 (4):801.

Chicago/Turabian Style

Bo Sun; Junlin Pan; Zili Wang; Yi Ren; Dariusz Mazurkiewicz; Małgorzata Jasiulewicz-Kaczmarek; Katarzyna Antosz. 2021. "Fatigue Reliability Analysis Method of Reactor Structure Considering Cumulative Effect of Irradiation." Materials 14, no. 4: 801.

Conference paper
Published: 05 February 2021 in Recent Advances in Computational Mechanics and Simulations
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A maintenance process of internal vehicle transport is important from the production companies and also service providers. Failures of transport vehicles for a production company mean difficulties in the realization of production and auxiliary processes. Failures of transport vehicles for a service organization means those employees of the organization are assigned to carry out service activities for a longer time. This issue can be a particular problem, especially for small service organizations. Hence, in order to plan the maintenance activities, it is appropriate to predict failures to prevent them by undertaking adequate preventive actions. In this work, the failure risk was calculated based on the data from the maintenance processes collected. Additionally, it is proposed the solution, especially for small maintenance service providers, which can be used for maintenance activities taken under consideration the criticality of internal vehicles. The method presented in the article, which supports decision making regarding service planning, can help companies providing maintenance outsourcing services.

ACS Style

Katarzyna Antosz; Małgorzata Jasiulewicz-Kaczmarek. Intelligent Predictive Decision Support System for the Maintenance Service Provider. Recent Advances in Computational Mechanics and Simulations 2021, 3 -13.

AMA Style

Katarzyna Antosz, Małgorzata Jasiulewicz-Kaczmarek. Intelligent Predictive Decision Support System for the Maintenance Service Provider. Recent Advances in Computational Mechanics and Simulations. 2021; ():3-13.

Chicago/Turabian Style

Katarzyna Antosz; Małgorzata Jasiulewicz-Kaczmarek. 2021. "Intelligent Predictive Decision Support System for the Maintenance Service Provider." Recent Advances in Computational Mechanics and Simulations , no. : 3-13.

Journal article
Published: 08 November 2020 in Applied Sciences
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The increase in the performance and effectiveness of maintenance processes is a continuous aim of production enterprises. The elimination of unexpected failures, which generate excessive costs and production losses, is emphasized. The elements that influence the efficiency of maintenance are not only the choice of an appropriate conservation strategy but also the use of appropriate methods and tools to support the decision-making process in this area. The research problem, which was considered in the paper, is an insufficient means of assessing the degree of the implementation of lean maintenance. This problem results in not only the possibility of achieving high efficiency of the exploited machines, but, foremost, it influences a decision process and the formulation of maintenance policy of an enterprise. The purpose of this paper is to present the possibility of using intelligent systems to support decision-making processes in the implementation of the lean maintenance concept, which allows the increase in the operational efficiency of the company’s technical infrastructure. In particular, artificial intelligence methods were used to search for relationships between specific activities carried out under the implementation of lean maintenance and the results obtained. Decision trees and rough set theory were used for the analysis. The decision trees were made for the average value of the overall equipment effectiveness (OEE) indicator. The rough set theory was used to assess the degree of utilization of the lean maintenance strategy. Decision rules were generated based on the proposed algorithms, using RSES software, and their correctness was assessed.

ACS Style

Katarzyna Antosz; Łukasz Paśko; Arkadiusz Gola. The Use of Artificial Intelligence Methods to Assess the Effectiveness of Lean Maintenance Concept Implementation in Manufacturing Enterprises. Applied Sciences 2020, 10, 7922 .

AMA Style

Katarzyna Antosz, Łukasz Paśko, Arkadiusz Gola. The Use of Artificial Intelligence Methods to Assess the Effectiveness of Lean Maintenance Concept Implementation in Manufacturing Enterprises. Applied Sciences. 2020; 10 (21):7922.

Chicago/Turabian Style

Katarzyna Antosz; Łukasz Paśko; Arkadiusz Gola. 2020. "The Use of Artificial Intelligence Methods to Assess the Effectiveness of Lean Maintenance Concept Implementation in Manufacturing Enterprises." Applied Sciences 10, no. 21: 7922.

Journal article
Published: 02 November 2019 in IFAC-PapersOnLine
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Manufacturing companies continually aim at increasing the performance and effectiveness of maintenance processes. The emphasis is put on the elimination of unexpected failures which generate unnecessary costs and production losses. The element that has an impact on the efficiency of maintenance is not only the selection of an appropriate conservation strategy and the use of appropriate methods and tools to support the decision-making process in this area. The aim of this work is to present the possibility of using intelligent systems to support decision-making processes in the implementation of the Lean Maintenance concept, which allows to increase the operational efficiency of the company’s technical infrastructure.

ACS Style

Katarzyna Antosz; Lukasz Pasko; Arkadiusz Gola. The Use of Intelligent Systems to Support the Decision-Making Process in Lean Maintenance Management. IFAC-PapersOnLine 2019, 52, 148 -153.

AMA Style

Katarzyna Antosz, Lukasz Pasko, Arkadiusz Gola. The Use of Intelligent Systems to Support the Decision-Making Process in Lean Maintenance Management. IFAC-PapersOnLine. 2019; 52 (10):148-153.

Chicago/Turabian Style

Katarzyna Antosz; Lukasz Pasko; Arkadiusz Gola. 2019. "The Use of Intelligent Systems to Support the Decision-Making Process in Lean Maintenance Management." IFAC-PapersOnLine 52, no. 10: 148-153.

Conference paper
Published: 25 June 2019 in Advances in Intelligent Systems and Computing
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Industrial robots are an integral part of modern manufacturing systems. In order to fully use their potential, the information related to the robot’s accuracy should be known first of all. In most cases, the information considering robot’s errors, provided in a technical specification, is scarce. That’s why, this paper presents the issues of determining the error of industrial robots positioning repeatability. A neural mathematical model that allows for predicting its value with the error less than 5% was designed. The obtained results were compared to a classical mathematical model. It was revealed that a well-trained neural network enables the prediction of the error of positioning repeatability with the doubled accuracy.

ACS Style

Rafał Kluz; Katarzyna Antosz; Tomasz Trzepieciński; Arkadiusz Gola. Predicting the Error of a Robot’s Positioning Repeatability with Artificial Neural Networks. Advances in Intelligent Systems and Computing 2019, 41 -48.

AMA Style

Rafał Kluz, Katarzyna Antosz, Tomasz Trzepieciński, Arkadiusz Gola. Predicting the Error of a Robot’s Positioning Repeatability with Artificial Neural Networks. Advances in Intelligent Systems and Computing. 2019; ():41-48.

Chicago/Turabian Style

Rafał Kluz; Katarzyna Antosz; Tomasz Trzepieciński; Arkadiusz Gola. 2019. "Predicting the Error of a Robot’s Positioning Repeatability with Artificial Neural Networks." Advances in Intelligent Systems and Computing , no. : 41-48.

Conference paper
Published: 26 April 2019 in Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020)
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Industry 4.0, known as the fourth digital revolution, is the integration of modern systems and machines based on digital solutions that influences the productivity of an enterprise. This concept forces the use of more and more sophisticated and complex solutions by enterprises, i.e. technological or organizational, associated with data collection and analysis, the development of technology, the ability of a rapid response to both internal and external changes, and the improvement of present processes. Highly automated production processes will require qualified management staff as well as production workers experienced in the work with new materials, machines and, in particular, information. This work presents the course of a didactic process which aims at the acquisition of skills within the simulation and analysis of flexible manufacturing systems with the use of mass service systems theory. The main part of the work shows the course of classes which aim to study the work efficiency of a flexible manufacturing cell. As a criterion of the system work efficiency, basic indicators of the mass service system work were adopted, that is an average number of products waiting in a queue, average time of a product waiting in a queue and a manufacturing system as well as the expected downtime of a cell. The results were compared with the results of typical models describing the work of mass service systems (M/M/1, M/D/1, M/El/1, M/G/1).

ACS Style

Rafał Kluz; Katarzyna Antosz. Simulation of Flexible Manufacturing Systems as an Element of Education Towards Industry 4.0. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) 2019, 332 -341.

AMA Style

Rafał Kluz, Katarzyna Antosz. Simulation of Flexible Manufacturing Systems as an Element of Education Towards Industry 4.0. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020). 2019; ():332-341.

Chicago/Turabian Style

Rafał Kluz; Katarzyna Antosz. 2019. "Simulation of Flexible Manufacturing Systems as an Element of Education Towards Industry 4.0." Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) , no. : 332-341.

Journal article
Published: 17 January 2019 in Journal of Manufacturing Systems
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Manufacturing systems (MSs) have become more and more complex, due to global competition. Optimal spare parts provisioning plays a critical role in sustaining an anticipated operational competitiveness level, via efficient and effective maintenance of machinery. The forecasting of intermittent demand for spare parts is a challenge, as it is not always possible to avoid random unforeseen breakdowns, which reduce availability and increase the unreliability of manufacturing systems. The aforementioned requires a systemic perspective, in order to perform a criticality analysis and prioritization of the spare parts needed to increase a manufacturing system’s availability and reliability. This paper first demonstrates the development of an empirical model (EM), using a case study MS. The EM enables a criticality analysis to be performed, considering the system perspective of spare part management, by taking maintenance-related and logistics-related factors into account. After that, the machineries are categorized into groups, considering the factors related to the maintenance, logistics and criticality levels. The second part presents how to perform spare part prioritization within a selected group, via an analytic hierarchy process (AHP), to minimize ad hoc suboptimal assessments, together with sensitivity analyses. Finally, it presents the spare part prioritization and the subsequent sensitivity analysis results.

ACS Style

Katarzyna Antosz; R.M. Chandima Ratnayake. Spare parts’ criticality assessment and prioritization for enhancing manufacturing systems’ availability and reliability. Journal of Manufacturing Systems 2019, 50, 212 -225.

AMA Style

Katarzyna Antosz, R.M. Chandima Ratnayake. Spare parts’ criticality assessment and prioritization for enhancing manufacturing systems’ availability and reliability. Journal of Manufacturing Systems. 2019; 50 ():212-225.

Chicago/Turabian Style

Katarzyna Antosz; R.M. Chandima Ratnayake. 2019. "Spare parts’ criticality assessment and prioritization for enhancing manufacturing systems’ availability and reliability." Journal of Manufacturing Systems 50, no. : 212-225.

Conference paper
Published: 08 December 2018 in Lecture Notes in Control and Information Sciences
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The paper deals with problems concerning a maintenance process realized by maintenance service companies. In the paper the concept of wastes identification in such companies is presented. Then, a case study company is analysed. The company designs, manufactures, implements and performs maintenance processes of installations used in products control, sorting and packing in clients’ factories. The analysed problems concern data collection as well as their analysis in order to improve the maintenance company efficiency. The authors propose to implement the Six Sigma methodology to collect and analyse data, elements of the Lean concept to identify wastes and Industry 4.0 concept in order to improve the maintenance service processes.

ACS Style

Katarzyna Antosz; Dorota Stadnicka. Possibilities of Maintenance Service Process Analyses and Improvement Through Six Sigma, Lean and Industry 4.0 Implementation. Lecture Notes in Control and Information Sciences 2018, 465 -475.

AMA Style

Katarzyna Antosz, Dorota Stadnicka. Possibilities of Maintenance Service Process Analyses and Improvement Through Six Sigma, Lean and Industry 4.0 Implementation. Lecture Notes in Control and Information Sciences. 2018; ():465-475.

Chicago/Turabian Style

Katarzyna Antosz; Dorota Stadnicka. 2018. "Possibilities of Maintenance Service Process Analyses and Improvement Through Six Sigma, Lean and Industry 4.0 Implementation." Lecture Notes in Control and Information Sciences , no. : 465-475.

Journal article
Published: 01 September 2018 in Tehnicki vjesnik - Technical Gazette
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ACS Style

Katarzyna Antosz; Andrzej Pacana. Comparative Analysis of the Implementation of the SMED Method on Selected Production Stands. Tehnicki vjesnik - Technical Gazette 2018, 25, 276 -282.

AMA Style

Katarzyna Antosz, Andrzej Pacana. Comparative Analysis of the Implementation of the SMED Method on Selected Production Stands. Tehnicki vjesnik - Technical Gazette. 2018; 25 (Supplement):276-282.

Chicago/Turabian Style

Katarzyna Antosz; Andrzej Pacana. 2018. "Comparative Analysis of the Implementation of the SMED Method on Selected Production Stands." Tehnicki vjesnik - Technical Gazette 25, no. Supplement: 276-282.

Conference paper
Published: 01 August 2018 in Advances in Intelligent Systems and Computing
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This article presents the problem of determining the mountability level of the assembly station using an artificial neural network (ANN). The results of ANN modelling were compared with the results of experimental research and classical mathematical modelling. It was found that the error in predicting the mountability level using the artificial neural network is about two-fold lower than in the case of the error determined by classical mathematical modelling. Although the neural network ensures a lower prediction error, to obtain a good prediction it is necessary to conduct many experiments in the whole workspace of the robots to build a training set. Despite the worst prediction, a mathematical model of the mountability level only requires an analytical description of the kinematic structure of the assembly robot, so in industrial applications this is preferred due to the lower labour requirement.

ACS Style

Rafał Kluz; Katarzyna Antosz; Tomasz Trzepiecinski. Forecasting the Mountability Level of a Robotized Assembly Station. Advances in Intelligent Systems and Computing 2018, 175 -184.

AMA Style

Rafał Kluz, Katarzyna Antosz, Tomasz Trzepiecinski. Forecasting the Mountability Level of a Robotized Assembly Station. Advances in Intelligent Systems and Computing. 2018; ():175-184.

Chicago/Turabian Style

Rafał Kluz; Katarzyna Antosz; Tomasz Trzepiecinski. 2018. "Forecasting the Mountability Level of a Robotized Assembly Station." Advances in Intelligent Systems and Computing , no. : 175-184.

Journal article
Published: 06 June 2018 in Eksploatacja i Niezawodnosc - Maintenance and Reliability
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ACS Style

Katarzyna Antosz. Maintenance – identification and analysis of the competency gap. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2018, 20, 484 -494.

AMA Style

Katarzyna Antosz. Maintenance – identification and analysis of the competency gap. Eksploatacja i Niezawodnosc - Maintenance and Reliability. 2018; 20 (3):484-494.

Chicago/Turabian Style

Katarzyna Antosz. 2018. "Maintenance – identification and analysis of the competency gap." Eksploatacja i Niezawodnosc - Maintenance and Reliability 20, no. 3: 484-494.

Conference paper
Published: 20 October 2017 in Recent Advances in Computational Mechanics and Simulations
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An Overall Equipment Effectiveness (OEE) indicator is one of the most often used indicators, especially in large companies, to assess the level of the successful utilization of equipment. Many companies still do not calculate OEE, although the procedure of the OEE calculation is well known. On the basis of the literature review and from companies practice, it occurs that different methods of the OEE assessment are used. It is because companies identify different disturbances which influence the OEE value. The authors summarized these disturbances. In the paper, two case studies concerning the OEE calculations from manufacturing companies are presented. On the basis of the first company, it is shown how the Total Productive Maintenance (TPM) implementation may improve the value of OEE. On the base of the other company, the way the OEE calculation procedure can be improved and the results of the calculation procedure modification are presented. Finally, the authors propose to introduce weights to differentiate the influence of different OEE components. The results of the new procedure implementation are presented in the paper.

ACS Style

Dorota Stadnicka; Katarzyna Antosz. Overall Equipment Effectiveness: Analysis of Different Ways of Calculations and Improvements. Recent Advances in Computational Mechanics and Simulations 2017, 45 -55.

AMA Style

Dorota Stadnicka, Katarzyna Antosz. Overall Equipment Effectiveness: Analysis of Different Ways of Calculations and Improvements. Recent Advances in Computational Mechanics and Simulations. 2017; ():45-55.

Chicago/Turabian Style

Dorota Stadnicka; Katarzyna Antosz. 2017. "Overall Equipment Effectiveness: Analysis of Different Ways of Calculations and Improvements." Recent Advances in Computational Mechanics and Simulations , no. : 45-55.

Conference paper
Published: 18 August 2017 in Advances in Intelligent Systems and Computing
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A maintenance process of forklifts presented in this work is realized by a service organization which delivers services for several companies that use forklifts. In the work, the fuzzy logic was implemented to assess the risk of failures for different groups of forklifts. The results of the analysis are to be taken into consideration by the service company in the decision making process. The plan of maintenance activities for each client’s forklifts can be developed and adequate maintenance activities can be indicated for each group on the basis of the risk of failures.

ACS Style

Katarzyna Antosz; Dorota Stadnicka. An Intelligent System Supporting a Forklifts Maintenance Process. Advances in Intelligent Systems and Computing 2017, 13 -22.

AMA Style

Katarzyna Antosz, Dorota Stadnicka. An Intelligent System Supporting a Forklifts Maintenance Process. Advances in Intelligent Systems and Computing. 2017; ():13-22.

Chicago/Turabian Style

Katarzyna Antosz; Dorota Stadnicka. 2017. "An Intelligent System Supporting a Forklifts Maintenance Process." Advances in Intelligent Systems and Computing , no. : 13-22.

Conference paper
Published: 18 August 2017 in Advances in Intelligent Systems and Computing
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A maintenance process of medical equipment is very important because people’s life or the quality of people’s life depend on such equipment. The maintenance of some equipment can be only done by specialists. Nevertheless, some actions can be undertaken by the less specialized personnel. In this paper, on the basis of the data concerning complaints, the kind of failures and exchanged parts in equipment, preventive actions were proposed. However, the actions are recommended not to prevent failures but to avoid a long waiting time for the equipment to be repaired. The authors propose to use a fuzzy logic analysis to assess the risk of failures of a certain piece of equipment. The defects which can be eliminated by the less specialized personnel were indicated. The results of the analysis are taken into consideration in a decision making process identifying the situations in which a certain person, i.e. a dealer, should be trained to be able to make a repair without sending the equipment to a manufacturer.

ACS Style

Katarzyna Antosz; Dorota Stadnicka. An Intelligent System Supporting a Maintenance Process of Specialised Medical Equipment. Advances in Intelligent Systems and Computing 2017, 637, 23 -32.

AMA Style

Katarzyna Antosz, Dorota Stadnicka. An Intelligent System Supporting a Maintenance Process of Specialised Medical Equipment. Advances in Intelligent Systems and Computing. 2017; 637 ():23-32.

Chicago/Turabian Style

Katarzyna Antosz; Dorota Stadnicka. 2017. "An Intelligent System Supporting a Maintenance Process of Specialised Medical Equipment." Advances in Intelligent Systems and Computing 637, no. : 23-32.

Journal article
Published: 01 July 2017 in IFAC-PapersOnLine
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ACS Style

Katarzyna Antosz; Dorota Stadnicka; R.M. Chandima Ratnayake. Development of a risk matrix for the assessment of maintenance suppliers: A study based on empirical knowledge. IFAC-PapersOnLine 2017, 50, 9026 -9031.

AMA Style

Katarzyna Antosz, Dorota Stadnicka, R.M. Chandima Ratnayake. Development of a risk matrix for the assessment of maintenance suppliers: A study based on empirical knowledge. IFAC-PapersOnLine. 2017; 50 (1):9026-9031.

Chicago/Turabian Style

Katarzyna Antosz; Dorota Stadnicka; R.M. Chandima Ratnayake. 2017. "Development of a risk matrix for the assessment of maintenance suppliers: A study based on empirical knowledge." IFAC-PapersOnLine 50, no. 1: 9026-9031.

Journal article
Published: 01 March 2017 in Management and Production Engineering Review
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Manufacturing firms continuously strive to increase the efficiency and effectiveness in the maintenance management processes. Focus is placed on eliminating the unexpected failures which cause unnecessary costs and the production losses. Risk-based maintenance (RBM) strategies enable to address the above through the identification of probability and consequences of potential failures whilst providing a way for prioritisation of maintenance actions based on the risk of possible failures. Such prioritisations enable to identify the optimal maintenance strategy, intervals of maintenance tasks, and optimal level of spare parts inventory. However, the risk assessment activities are performed with the support of a risk matrix. Suboptimal classifications and/or prioritisations arise due to the inherent nature of the risk matrix. This is caused by the fact that there are no means to incorporate actual circumstances at the boundary of the input ranges or at the levels of linguistic data and risk categories. In this paper, a risk matrix is first developed in collaboration with one of the manufacturing firms in Poland. Then, it illustrates the use of fuzzy logic for minimisation of suboptimal prioritisation and/or classifications using a fuzzy inference system (FIS) together with illustrative membership functions and a rule base. Finally, an illustrative risk assessment is also demonstrated to illustrate the methodology.

ACS Style

R.M. Chandima Ratnayake; Katarzyna Antosz. Risk-Based Maintenance Assessment in the Manufacturing Industry: Minimisation of Suboptimal Prioritisation. Management and Production Engineering Review 2017, 8, 38 -45.

AMA Style

R.M. Chandima Ratnayake, Katarzyna Antosz. Risk-Based Maintenance Assessment in the Manufacturing Industry: Minimisation of Suboptimal Prioritisation. Management and Production Engineering Review. 2017; 8 (1):38-45.

Chicago/Turabian Style

R.M. Chandima Ratnayake; Katarzyna Antosz. 2017. "Risk-Based Maintenance Assessment in the Manufacturing Industry: Minimisation of Suboptimal Prioritisation." Management and Production Engineering Review 8, no. 1: 38-45.