Austempered Ductile Iron Manufacturing Data Acquisition Process with the Use of Semantic Techniques

Wilk-Kołodziejczyk, D.; Kluska-Nawarecka, A. S.; Regulski, K.; Adrian, Weronika T.; Jaśkowiec, Krzysztof

doi:10.1515/amm-2016-0339

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…The basic assumption of the model is that each pharmaceutical company implements the Industry 4.0 strategy in the production of drugs and uses one or many of the different concepts of horizontal communication, i.e., Cloud Computing [ 44 ], IIoT [ 45 ], Connectivity [ 46 ], Big Data [ 47 ], Digital Twins [ 48 ], ID/Loc [ 46 , 49 ], Semantics [ 50 , 51 ], SOA [ 52 ]. Of course, we can assume other solutions, but the eight mentioned are key concepts of the CPS I4.0.…”

Section: Methodsmentioning

confidence: 99%

Application of Feature Extraction Methods for Chemical Risk Classification in the Pharmaceutical Industry

Topolski

2021

Sensors

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The features that are used in the classification process are acquired from sensor data on the production site (associated with toxic, physicochemical properties) and also a dataset associated with cybersecurity that may affect the above-mentioned risk. These are large datasets, so it is important to reduce them. The author’s motivation was to develop a method of assessing the dimensionality of features based on correlation measures and the discriminant power of features allowing for a more accurate reduction of their dimensions compared to the classical Kaiser criterion and assessment of scree plot. The method proved to be promising. The results obtained in the experiments demonstrate that the quality of classification after extraction is better than using classical criteria for estimating the number of components and features. Experiments were carried out for various extraction methods, demonstrating that the rotation of factors according to centroids of a class in this classification task gives the best risk assessment of chemical threats. The classification quality increased by about 7% compared to a model where feature extraction was not used and resulted in an improvement of 4% compared to the classical PCA method with the Kaiser criterion, with an evaluation of the scree plot. Furthermore, it has been shown that there is a certain subspace of cybersecurity features, which complemented with the features of the concentration of volatile substances, affects the risk assessment of chemical hazards. The identified cybersecurity factors are the number of packets lost, incorrect Logins, incorrect sensor responses, increased email spam, and excessive traffic in the computer network. To visualize the speed of classification in real-time, simulations were carried out for various systems used in Industry 4.0.

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Section: Methodsmentioning

confidence: 99%

Application of Feature Extraction Methods for Chemical Risk Classification in the Pharmaceutical Industry

Topolski

2021

Sensors

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“…Austempering of steel results in the formation of microstructure consisting of the acicular ferrite and iron carbide (cementite), but in the case of the austempered cast iron the microstructure consists of the high-carbon austenite and acicular ferrite [20][21][22][23][24][25][26]. It should be noted that not only the basic elements present in cast iron, but also certain alloying elements significantly influence the heat treatment process.…”

Section: Introductionmentioning

confidence: 99%

Archives of Foundry Engineering

Jakubus

2022

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The article presents the results of research on the abrasion resistance of cast iron with vermicular graphite in the as-cast state and after austempering (the latter material is referred to as AVGI -Austempered Vermicular Graphite Iron). Austenitization was carried out at the temperature values of either 900°C or 960°C, and austempering at the temperature values of either 290°C and or 390°C. Both the austenitization and the austempering time was equal to 90 minutes. The change of the pearlitic-ferritic matrix to the ausferritic one resulted in an increase in mechanical properties. Abrasion tests were conducted by means of the T-01M pin-on-disc tribometer. The counter-sample (i.e. the disc) was made of the JT6500 friction material. Each sample was subject to abrasion over a sliding distance of 4000 m. The weight losses of both samples and counter-samples were determined by the gravimetric method. It was found that the vermicular cast iron austenitized at 900°C and austempered at 290°C was characterized by the lowest wear among the evaluated cast iron types. The geometric structure of the surface layer after the dry friction test exhibited irregular noticeable grooves, distinct oriented abrasion traces, plastic flow of the material, microcracks, and pits generated by tearing out the abraded material. The largest surface roughness was found for the AVGI cast iron heat-treated according to the variant 3 (Tγ =900 ºC; Tpi = 390°C), while the smallest one occurred in AVGI cast iron subject to either the variant 2 (Tγ =960 ºC; Tpi = 290°C) or the variant 4 (Tγ =900 ºC; Tpi = 290°C) of heat treatment and was equal to either 2.5 µm or 2.66 µm, respectively. It can be seen that the surface roughness decreases with the decrease in the austempering temperature.

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Context-aware workflow management for smart manufacturing: A literature review of semantic web-based approaches

Ochoa

Larrinaga

Pérez

2023

Future Generation Computer Systems

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Austempered Ductile Iron Manufacturing Data Acquisition Process with the Use of Semantic Techniques

Cited by 3 publications

References 17 publications

Application of Feature Extraction Methods for Chemical Risk Classification in the Pharmaceutical Industry

Application of Feature Extraction Methods for Chemical Risk Classification in the Pharmaceutical Industry

Archives of Foundry Engineering

Context-aware workflow management for smart manufacturing: A literature review of semantic web-based approaches

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