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Tytuł:
New Grey Integrated Model to Solve a Machine Selection Problem for a Textile Company
Nowy zintegrowany model rozwiązujący problem wyboru maszyny dla firmy tekstylnej
Autorzy:
Ulutaş, Alptekin
Powiązania:
https://bibliotekanauki.pl/articles/231577.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Biopolimerów i Włókien Chemicznych
Tematy:
AHP
ROV-G
sewing machine selection
machine selection problem
wybór maszyny do szycia
problem z wyborem maszyny
Opis:
The textile sector has become an indispensable part of the Turkish economy. The sewing machine is a long-lasting and easy-to-use tool widely used in the garment industry, which is a branch of the textile industry. The sewing machine is an indispensable production tool for the textile industry and sewing machine selection is a significant decision for the production performance of textile companies. Selecting an appropriate sewing machine increases production performance, while selecting an improper one reduces production performance. The sewing machine selection problem is a typical machine selection issue. Many criteria, such as cost, productivity, safety etc. are considered in the machine selection. Therefore, MCDM methods are applicable to solve the machine selection problem. This study develops an integrated grey MCDM model including Grey AHP and ROV-G to select the most appropriate sewing machine for an apparel textile company.
Sektor tekstylny stał się nieodłączną częścią tureckiej gospodarki. Maszyna do szycia jest trwałym i łatwym w użyciu narzędziem szeroko stosowanym w przemyśle odzieżowym, który jest gałęzią przemysłu tekstylnego. Maszyna do szycia jest niezbędnym narzędziem produkcyjnym dla przemysłu tekstylnego, a wybór maszyny do szycia jest znaczącą decyzją w zakresie wydajności produkcyjnej firm tekstylnych. Wybór odpowiedniej maszyny do szycia zwiększa wydajność produkcji, a wybór niewłaściwej zmniejsza wydajność produkcji. Problem wyboru maszyny do szycia jest typowym problemem przy wyborze maszyny. Przy wyborze maszyny branych jest pod uwagę wiele kryteriów, takich jak: koszt, wydajność, bezpieczeństwo itp. Dlatego metody MCDM mają zastosowanie do rozwiązania problemu wyboru maszyny. W badaniu, w celu wybrania najbardziej odpowiedniej maszyny do szycia dla firmy produkującej odzież, opracowano zintegrowany model MCDM, w tym AHP i ROV-G.
Źródło:
Fibres & Textiles in Eastern Europe; 2020, 1 (139); 20-25
1230-3666
2300-7354
Pojawia się w:
Fibres & Textiles in Eastern Europe
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
System dynamics as a decision support system for machine tool selection
Autorzy:
Adane, T. F.
Nicolescu, M.
Powiązania:
https://bibliotekanauki.pl/articles/99389.pdf
Data publikacji:
2016
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
machine selection
decision making
performance analysis
system dynamics modelling
Opis:
The worldwide competitive economy, the increase in sustainable issue and investment of new production line is demanding companies to choose the right machine from the available ones. An improper selection can negatively affect the overall performance of the manufacturing system like productivity, quality, cost and companys responsive manufacturing capabilities. Thus, selecting the right machine is desirable and substantial for the company to sustain competitive in the market. The ultimate objective of this paper is to formulate a framework for machining strategy and also provide methodology for selecting machine tool from two special purpose machine tools in consideration of interaction of attributes. A decision support system for the selection of machine tool is developed. It evaluates the performance of the machining process and enhances the manufacturer (decision maker) to select the machine with respect to the performance and the pre-chosen criteria. Case study was conducted in a manufacturing company. A system dynamics modelling and simulation techniques is demonstrated towards efficient selection of machine tool that satisfy the future requirement of engine-block production.
Źródło:
Journal of Machine Engineering; 2016, 16, 3; 102-125
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Approach to solving mining machine selection problem by using grey theory
Autorzy:
Milisavljevic, V.
Martinetti, A.
Cvjetic, A.
Powiązania:
https://bibliotekanauki.pl/articles/111264.pdf
Data publikacji:
2018
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
machine selection
grey theory
multiple-attribute
uncertain information
mining industry
Opis:
The selection of a mining machine is a multiple-attribute problem that involves the consideration of numerous parameters of various origins. A common task in the mining industry is to select the best machine among several alternatives, which are frequently described both with numerical variables as well as linguistic variables. Numerical variables are mostly related to the technical characteristics of the machines, which are available in detail in most cases. On the other hand, some equally important parameters such as price, reliability, support for service and spare parts, operating cost, etc., are not available at the required level for various reasons; hence, these can be considered uncertain information. For this reason, such information is described with linguistic variables. This paper presents research related to overcoming this problem by using grey theory for selecting a proper mining machine. Grey theory is a well-known method used for multiple-attribute selection problems that involves a system in which parts of the necessary information are known and parts are unknown.
Źródło:
Mining – Informatics, Automation and Electrical Engineering; 2018, 56, 3; 59-64
2450-7326
2449-6421
Pojawia się w:
Mining – Informatics, Automation and Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modern machine tools in application to advanced aerospace components manufacturing
Autorzy:
Radkowski, G.
Szyszka, G.
Powiązania:
https://bibliotekanauki.pl/articles/99531.pdf
Data publikacji:
2010
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
advanced aerospace structure
machine tool selection
software
service
Opis:
The article describes general characteristics of components produced by WSK "PZL-Rzeszow" S.A. (WSK) and their influence on machine tool's technical requirements and special accessories defined during the procurement process of new machining center or lathe. It shortly presents the investment process in new machine tool and a new product implementation path. A point on CAD/CAM and CNC systems existing in WSK and some specific aspects concerning such software is also mentioned. Maintenance challenges have also been pointed to based on WSK's experience.
Źródło:
Journal of Machine Engineering; 2010, 10, 2; 82-94
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Computer aided FMS machine tools subsystem selection using the evolutionary system of multicriteria analysis
Autorzy:
Gola, A.
Montusiewicz, J.
Świć, A.
Powiązania:
https://bibliotekanauki.pl/articles/118157.pdf
Data publikacji:
2011
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
machine tools selection
Evolutionary System of Multicriteria Analysis
ESAW
Opis:
One of the key problems in the area of flexible manufacturing systems (FMS) design is a problem of proper design of manufacturing subsystem and especially the machine tools selection. Although the problem seems to be simple, in fact it is difficult to solve because of large variety and number of parameters and also brief foredesign which are highly influential for the decision. This study shows possibility of implementation the Evolutionary System of Multicriteria Analysis for defining the importance of solutions in the process of casing-class FMS machine tools selection.
Źródło:
Applied Computer Science; 2011, 7, 1; 18-29
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
MLP neural nets in design of technological process
Sieci neuronowe MLP w projektowaniu procesu technologicznego
Autorzy:
Rojek, I.
Powiązania:
https://bibliotekanauki.pl/articles/176084.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
neural nets
selection of tools
selection of machine tools
selection of machining parameters
technological process
sieci neuronowe
dobór narzędzi
dobór obrabiarek
dobór parametrów skrawania
proces technologiczny
Opis:
This paper proposes MLP neural nets to improve technological process design. The first stage of research concerned the creation of models to selection of machine tools, the second stage pertained the creation of models to selection of tools and the third stage concerned the creation of models to selection of machining parameters. In addition, use of tools is forecasted at various time intervals. The models were created using Statsoft STATISTICA Data Miner. These models were compared in order to obtain the best selection. Based on the models, it is possible to create different scenarios of the design of technological process.
W artykule przedstawiono opracowanie sieci neuronowych MLP w celu poprawy projektowania procesu technologicznego. Pierwszy etap dotyczył tworzenia modeli wyboru obrabiarek, drugi modeli wyboru narzędzi i trzeci tworzenia modeli do wyboru parametrów obróbki skrawaniem. Dodatkowo w opracowanych modelach uwzględniono prognozowanie użycia narzędzi w różnych przedziałach czasowych. Stosowano program Statsoft STATISTICA Data Miner. Prowadzono analizy wyników dla poszczególnych modeli i opracowano kryteria doboru. Stwierdzono, że wprowadzenie sieci neronowych umożliwia tworzenie różnych scenariuszy projektowania procesu technologicznego.
Źródło:
Advances in Manufacturing Science and Technology; 2015, 39, 1; 87-95
0137-4478
Pojawia się w:
Advances in Manufacturing Science and Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid feature selection and support vector machine framework for predicting maintenance failures
Autorzy:
Tarik, Mouna
Mniai, Ayoub
Jebari, Khalid
Powiązania:
https://bibliotekanauki.pl/articles/30148252.pdf
Data publikacji:
2023
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
predictive maintenance
machine learning
features selection
SMOTE-Tomek
Support Vector Machine
Opis:
The main aim of predictive maintenance is to minimize downtime, failure risks and maintenance costs in manufacturing systems. Over the past few years, machine learning methods gained ground with diverse and successful applications in the area of predictive maintenance. This study shows that performing preprocessing techniques such as over¬sampling and feature selection for failure prediction is promising. For instance, to handle imbalanced data, the SMOTE-Tomek method is used. For feature selection, three different methods can be applied: Recursive Feature Elimination, Random Forest and Variance Threshold. The data considered in this paper for simulation are used in literature. They are used to measure aircraft engine sensors to predict engine failures, while the prediction algorithm used is a Support Vector Machine. The results show that classification accuracy can be significantly boosted by using the preprocessing techniques.
Źródło:
Applied Computer Science; 2023, 19, 2; 112-124
1895-3735
2353-6977
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sleep Snoring Sound Recognition Based on Wavelet Packet Transform
Autorzy:
Ding, Li
Peng, Jianxin
Zhang, Xiaowen
Song, Lijuan
Powiązania:
https://bibliotekanauki.pl/articles/31339924.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
snoring recognition
wavelet packet transform
feature selection
machine learning
Opis:
Snoring is a typical and intuitive symptom of the obstructive sleep apnea hypopnea syndrome (OSAHS), which is a kind of sleep-related respiratory disorder having adverse effects on people’s lives. Detecting snoring sounds from the whole night recorded sounds is the first but the most important step for the snoring analysis of OSAHS. An automatic snoring detection system based on the wavelet packet transform (WPT) with an eXtreme Gradient Boosting (XGBoost) classifier is proposed in the paper, which recognizes snoring sounds from the enhanced episodes by the generalization subspace noise reduction algorithm. The feature selection technology based on correlation analysis is applied to select the most discriminative WPT features. The selected features yield a high sensitivity of 97.27% and a precision of 96.48% on the test set. The recognition performance demonstrates that WPT is effective in the analysis of snoring and non-snoring sounds, and the difference is exhibited much more comprehensively by sub-bands with smaller frequency ranges. The distribution of snoring sound is mainly on the middle and low frequency parts, there is also evident difference between snoring and non-snoring sounds on the high frequency part.
Źródło:
Archives of Acoustics; 2023, 48, 1; 3-12
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Computer aided FMS machine tools subsystem selection - conception of methodology
Autorzy:
Gola, A.
Świć, A.
Powiązania:
https://bibliotekanauki.pl/articles/117983.pdf
Data publikacji:
2009
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
computer aided selection
flexible manufacturing system
FMS machine tools subsystem
Opis:
The aim of the article is to present a new methodology of computer aided FMS machine tools selection. Flexible manufacturing systems (FMSs) are systems which allows manufacturing parts in small lot sizes keeping high level of productivity and low costs of production. Despite the fact applied research on designing FMS systems have been continued for several years there are no methodical solution that can help design engineers to select machine tools for FMS in a optimal way. This article shows the main algorithm and stages of the methodology which is based on computer database systems, algorithms of elimination and method of multicriteria optimisation.
Źródło:
Applied Computer Science; 2009, 5, 1; 27-38
1895-3735
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Machine learning methods for optimal compatibility of materials in ecodesign
Autorzy:
Rojek, I.
Dostatni, E.
Powiązania:
https://bibliotekanauki.pl/articles/202203.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
machine learning methods
classification models
ecodesign
selection of materials
compatibility
Opis:
Machine learning (ML) methods facilitate automated data mining. The authors compare the effectiveness of selected ML methods (RBF networks, Kohonen networks, and random forest) as modelling tools supporting the selection of materials in ecodesign. Applied in the design process, ML methods help benefit from the knowledge, experience and creativity of designers stored in historical data in databases. Implemented into a decision support system, the knowledge can be utilized – in the case under analysis – in the process of design of environmentally friendly products. The study was initiated with an analysis of input data for the selection of materials. The input data, specified in cooperation with designers, include both technological and environmental parameters which guarantee the desired compatibility of materials. Next, models were developed using selected ML methods. The models were assessed and implemented into an expert system. The authors show which models best fit their purpose and why. Models supporting the selection of materials, connections and disassembly methods help boost the recycling properties of designed products.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2020, 68, 2; 199-206
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Supervised probabilistic failure prediction of tuned mass damper-equipped high steel frames using machine learning methods
Autorzy:
Farrokhi, Farshid
Rahimi, Sepideh
Powiązania:
https://bibliotekanauki.pl/articles/1845128.pdf
Data publikacji:
2020
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
failure analysis
supervised machine learning
feature selection
tuned mass damper
Opis:
In this study, firstly, the behavior of a high steel frame equipped with tuned mass damper (TMD) due to several seismic records is investigated considering the structural and seismic uncertainties. Then, machine learning methods including artificial neural networks (ANN), decision tree (DT), Naïve Bayes (NB) and support vector machines (SVM) are used to predict the behavior of the structure. Results showed that among the machine learning models, SVM with Gaussian kernel has better performance since it is capable of predicting the drift of stories and the failure probability with R2 value equal to 0.99. Furthermore, results of feature selection algorithms revealed that when using TMD in high steel structures, seismic uncertainties have greater influences on drift of stories in comparison with structural uncertainties. Findings of this study can be used in design and probabilistic analysis of high steel frames equipped with TMDs.
Źródło:
Studia Geotechnica et Mechanica; 2020, 42, 3; 179-190
0137-6365
2083-831X
Pojawia się w:
Studia Geotechnica et Mechanica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Determinants of selecting research laboratory – recommendations for manufacturers of agricultural machines
Determinanty wyboru laboratorium badawczego – rekomendacje dla producentów maszyn rolniczych
Autorzy:
Nogalski, B.
Niewiadomski, P.
Bartłomiejczak, K.
Powiązania:
https://bibliotekanauki.pl/articles/335239.pdf
Data publikacji:
2018
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Maszyn Rolniczych
Tematy:
selection determinants
research laboratory
agricultural machine
determinanty wyboru
laboratorium badawcze
maszyna rolnicza
Opis:
The subject of this paper – being a preliminary study – are the determinants of selecting a research laboratory for the needs of carrying out safety tests of useness, evaluating the conformity in order to issue an EC conformity declaration, and to voluntarily certify for the "B "safety mark. The research was conducted from the point of view of small, medium, and large manufacturers of agricultural machines. The fundamental purpose of the study is to answer the question: what factors – from the point of view of the manufacturers of agricultural machines – are relevant when selecting a research entity. The main goal required formulating and implementing the partial goals, which included: determining the significance of starting cooperation by a Polish manufacturer with a research laboratory in the context of the binding regulations and standards; by reconstructing and interpreting the literature of the subject – choosing the factors to be considered when selecting a research entity; compiling the determinants constituting the foundation of a research tool in the form of an assessment sheet being a resultant of literature studies, and a discussion among intentionally selected experts from the agricultural machines sector. The specified explications became the background that defines correct direction for further research works (assessment of the significance of requirements), whose results will be presented in the subsequent part of the study.
Przedmiotem badań niniejszego opracowania – stanowiącego badanie przygotowawcze – są determinanty wyboru laboratorium badawczego dla potrzeb przeprowadzania badań bezpieczeństwa użytkowania, oceny zgodności w celu wystawienia deklaracji zgodności WE oraz dobrowolnej certyfikacji na znak bezpieczeństwa „B”. Badania prowadzono z perspektywy małych, średnich i dużych przedsiębiorstw produkujących maszyny rolnicze. Fundamentalnym celem badań jest próba odpowiedzi na pytanie: jakie czynniki – z punktu widzenia wytwórców maszyn rolniczych – są istotne przy wyborze jednostki badawczej. Osiągnięcie celu głównego wymagało sformułowania i zrealizowania celów cząstkowych, do których zaliczono: określenie znaczenia podjęcia współpracy polskiego wytwórcy z laboratorium badawczym w kontekście obowiązujących przepisów i norm, wykorzystując metodę rekonstrukcji i interpretacji literatury przedmiotu – nominowanie czynników branych pod uwagę przy wyborze jednostki badawczej; skompilowanie determinant stanowiących fundament narzędzia badawczego w postaci arkusza oceny będącego wypadkową eksploracji piśmiennictwa oraz dyskusji wśród celowo dobranych ekspertów związanych z sektorem maszyn rolniczych. Skonkretyzowane eksplikacje stały się substratem definiującym właściwy kierunek dalszych prac badawczych (ocena istotności wymagań), których wyniki zostaną zaprezentowane w kolejnej części opracowania.
Źródło:
Journal of Research and Applications in Agricultural Engineering; 2018, 63, 4; 150-155
1642-686X
2719-423X
Pojawia się w:
Journal of Research and Applications in Agricultural Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Ensembles of instance selection methods: A comparative study
Autorzy:
Blachnik, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/330413.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
machine learning
instance selection
ensemble methods
uczenie maszynowe
selekcja przypadków
metoda zespołowa
Opis:
Instance selection is often performed as one of the preprocessing methods which, along with feature selection, allows a significant reduction in computational complexity and an increase in prediction accuracy. So far, only few authors have considered ensembles of instance selection methods, while the ensembles of final predictive models attract many researchers. To bridge that gap, in this paper we compare four ensembles adapted to instance selection: Bagging, Feature Bagging, AdaBoost and Additive Noise. The last one is introduced for the first time in this paper. The study is based on empirical comparison performed on 43 datasets and 9 base instance selection methods. The experiments are divided into three scenarios. In the first one, evaluated on a single dataset, we demonstrate the influence of the ensembles on the compression–accuracy relation, in the second scenario the goal is to achieve the highest prediction accuracy, and in the third one both accuracy and the level of dataset compression constitute a multi-objective criterion. The obtained results indicate that ensembles of instance selection improve the base instance selection algorithms except for unstable methods such as CNN and IB3, which is achieved at the expense of compression. In the comparison, Bagging and AdaBoost lead in most of the scenarios. In the experiments we evaluate three classifiers: 1NN, kNN and SVM. We also note a deterioration in prediction accuracy for robust classifiers (kNN and SVM) trained on data filtered by any instance selection methods (including the ensembles) when compared with the results obtained when the entire training set was used to train these classifiers.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2019, 29, 1; 151-168
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Prediction of protein subcellular localization using support vector machine with the choice of proper kernel
Autorzy:
Hasan, M.A.M.
Ahmad, S.
Molla, M.K.I.
Powiązania:
https://bibliotekanauki.pl/articles/81150.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
subcellular localization
protein
prediction
support vector machine
model selection
kernel
radial base function
Źródło:
BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology; 2017, 98, 2
0860-7796
Pojawia się w:
BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Enhancing Intrusion Detection in Industrial Internet of Things through Automated Preprocessing
Autorzy:
Sezgin, Anıl
Boyacı, Aytuğ
Powiązania:
https://bibliotekanauki.pl/articles/2201911.pdf
Data publikacji:
2023
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
feature selection
intrusion detection
machine learning
industrial internet of things
Internet of things
IIoT
Opis:
Industrial Internet of Things (IIoT) is a rapidly growing field, where interconnected devices and systems are used to improve operational efficiency and productivity. However, the extensive connectivity and data exchange in the IIoT environment make it vulnerable to cyberattacks. Intrusion detection systems (IDS) are used to monitor IIoT networks and identify potential security breaches. Feature selection is an essential step in the IDS process, as it can reduce computational complexity and improve the accuracy of the system. In this research paper, we propose a hybrid feature selection approach for intrusion detection in the IIoT environment using Shapley values and a genetic algorithm-based automated preprocessing technique which has three automated steps including imputation, scaling and feature selection. Shapley values are used to evaluate the importance of features, while the genetic algorithm-based automated preprocessing technique optimizes feature selection. We evaluate the proposed approach on a publicly available dataset and compare its performance with existing state-of-the-art methods. The experimental results demonstrate that the proposed approach outperforms existing methods, achieving high accuracy, precision, recall, and F1-score. The proposed approach has the potential to enhance the performance of IDS in the IIoT environment and improve the overall security of critical industrial systems.
Źródło:
Advances in Science and Technology. Research Journal; 2023, 17, 2; 120--135
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
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