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Understanding the temperature–working condition relationship is crucial for optimizing machining processes to ensure dimensional accuracy, surface finish quality, and overall spindle longevity. Monitoring and controlling spindle temperature through appropriate cooling systems and operational parameters are essential for efficient and reliable machining operations. This paper presents an in-depth analysis of the thermal equilibrium and deformation characteristics of a high-speed motorized spindle unit utilized in grinding machine tools. Through a series of thermal equilibrium experiments and meticulous data acquisition, the study investigates the nuanced influence of various working conditions, including spindle speeds, coolant types, and coolant flow rates, on spindle temperatures and thermal deformations. Leveraging the power of Artificial Neural Networks (ANNs), predictive models are meticulously developed to accurately forecast spindle behavior. Subsequently, the models are seamlessly transitioned to a cloud computing infrastructure to ensure remote accessibility and scalability, facilitating real-time monitoring and forecasting of spindle performance. The validity and reliability of the predictive models are rigorously assessed through comparison with experimental data, demonstrating excellent agreement and high accuracy in forecasting spindle thermal behavior. Furthermore, the study underscores the critical role of key working condition variables as precise predictors of spindle temperature and thermal deformation, emphasizing their significance in optimizing overall spindle efficiency and performance. This comprehensive analysis offers valuable insights and practical implications for enhancing spindle operation and advancing the field of grinding machine tools.

The performance of the final part of the turning process, a topic of practical importance, heavily depends on the cutting parameters. Surface quality, a crucial product attribute in manufacturing, often tops consumer demands during machining due to its significant influence on product functionality. This paper assesses the correlation between the detected vibration signal, statistical parameters (Crest, Kurtosis and I-kaz3D coefficient) and surface roughness and provides valuable insights for practical applications. When the tool experiences vibrations during material removal, these oscillations leave a ripple effect on the surface of the workpiece. We aim to determine the impact of cutting parameters on surface roughness while turning 42CrMo4 steel using a carbide tool insert. Cutting parameters, such as spindle speed, feed, and depth of cut, were used. Signal processing is carried out using different techniques to identify the effect of the cutting parameters on vibration signals. Finally, we delve into the interaction effects between the cutting parameters, vibration signals and surface roughness, offering a comprehensive understanding of real-world manufacturing scenarios. Higher I-kaz3D coefficients correspond to higher surface roughness values. The I-kaz3D coefficient decreases as the surface roughness measurements decrease, indicating that the I-kaz3D technique can accurately indicate an increase or decrease in surface roughness. On the other hand, the cutting force Fc was the component most strongly correlated with surface roughness (Ra), yielding the best results across all indices (adjusted R²adj = 95.1%, er=.8 ± 2.3%). [ABSTRACT FROM AUTHOR]

This paper presents the development and evaluation of neural network models using a small input–output dataset to predict the thermal behavior of a high-speed motorized spindles. Different neural multi-output regression models were developed and evaluated using Keras, one of the most popular deep learning frameworks at the moment. ANN was developed and evaluated considering the following: the influence of the topology (number of hidden layers and neurons within), the learning parameter, and validation techniques. The neural network was simulated using a dataset that was completely unknown to the network. The ANN model was used for analyzing the effect of working conditions on the thermal behavior of the motorized grinder spindle. The prediction accuracy of the ANN model for the spindle thermal behavior ranged from 95% to 98%. The results show that the ANN model with small datasets can accurately predict the temperature of the spindle under different working conditions. In addition, the analysis showed a very strong effect of type coolant on spindle unit temperature, particularly for intensive cooling with water.

Surface quality is one of the most important indicators of the quality of machined parts. The analytical method of defining the arithmetic mean roughness is not applied in practice due to its complexity and empirical models are applied only for certain values of machining parameters. This paper presents the design and development of artificial neural networks (ANNs) for the prediction of the arithmetic mean roughness, which is one of the most common surface roughness parameters. The dataset used for ANN development were obtained experimentally by machining AA7075 aluminum alloy under various machining conditions. With four factors, each having three levels, the full factorial design considers a total of 81 experiments that have to be carried out. Using input factor-level settings and adopting the Taguchi method, the experiments were reduced from 81 runs to 27 runs through an orthogonal design. In this study we aimed to check how reliable the results of artificial neural networks were when obtained based on a small input-output dataset, as in the case of applying the Taguchi methodology of planning a four-factor and three-level experiment, in which 27 trials were conducted. Furthermore, this paper considers the optimization of machining parameters for minimizing surface roughness in machining AA7075 aluminum alloy. The results show that ANNs can be successfully trained with small data and used to predict the arithmetic mean roughness. The best results were achieved by backpropagation multilayer feedforward neural networks using the BR algorithm for training.

In order to avoid the failure of machine tools spindles in the real machining process due to an increase in temperature, it is essential to predict its thermal behavior in the designing phase. The characteristics of machine tools significantly depend on the thermal-elastic behavior of the spindle. These parameters directly affect the productivity and quality of machining operations. This paper presents a thermal - elastic model of the machine tool spindle which was based on the quasi-static model of bearings and the finite element (FE) model of the spindle shaft. Based on quasi-static model of bearings with angular contact, heat generated and thermal contact resistances (TCR) are determined for each position of the balls. The aforementioned constraints have been applied to the 3D FE model of the spindle which allowed for establishing non-stationary change of temperature and thermal deformation. In order to prove the efficacy of the proposed model, experimental measurements of spindle and bearing temperatures were done using thermocouples and thermal imager.

Drinking water and fire safety are strongly bonded to each other. Actual drinking water demand and fire flows are both delivered through the same network, and are both devoted to public health and safety. In The Netherlands, the discussion about fire flows supplied by the drinking water networks has drawn fire fighters and drinking water companies together, searching for novel approaches to improve public safety. One of these approaches is the application of residential fire sprinkler systems fed by drinking water. This approach has an impact on the layout of domestic drinking water systems (DDWSs), as extra plumbing is required. This study examined the influence of the added plumbing on quality of both fresh and 10 h stagnant water in two full scale DDWSs: a conventional and an extended system. Overnight stagnation was found to promote copper and zinc leaching from pipes in both DDWSs. Microbial numbers and viability in the stagnant water, measured by heterotrophic plate count (HPC), flow cytometry (FCM) and adenosine tri-phosphate (ATP), depended on the temperature of fresh water, as increased microbial numbers and viability was measured in both DDWSs when the temperature of fresh water was below the observed tipping point (15 °C for the HPC and 17 °C for the FCM and ATP measurements respectively) and vice versa. A high level of similarity between water and biofilm communities, >98% and >70–94% respectively, indicates that the extension of the DDWS did not affect either the microbial quality of fresh drinking water or the biofilm composition.

In maize, at least five auxin-binding proteins (ABPs) have been identified, yet their functions remain unclear. The present study reports the use of maize abp1, abp4, and abp1abp4 mutants to investigate the role of ABPs during maize growth and development. Single and double abp mutant plants grown in a greenhouse differ from the wild type (WT) in their leaf declination and leaf blade growth. The effect of the dark (D), blue light (BL), red light (RL), and exogenous auxin on the development of mutant seedlings was also studied. Relative to WT, etiolated mutant seedlings were shorter and showed a reduced responsiveness to exogenous auxin. In BL or RL, the responsiveness of maize seedlings to auxin was distinctly less than in D. The reducing effect of light on seedling responsiveness to auxin is mediated at least by phytochromes. The suppression of ABP1 and (or) ABP4 led to a distinct accumulation of free indole-3-acetic acid (IAA) in etiolated and light-grown seedling organs. We concluded that ABP1 and ABP4 participate in the growth of maize seedlings, mediate seedling responses to auxin, and interact with light signaling pathway(s). We also deduce a functional interaction between ABP1 and ABP4, which is that the relationship between them is light-, organ- and response-dependent. Key words: auxin, auxin-binding protein, growth, light, maize. Les auteurs ont identifie cinq proteines liant l'auxines << auxin-binding proteins >> (ABPs), chez le mai's, sans pouvoir etablir clairement leurs fonctions. Ils ont utilise trois mutants de mai's (abp1, abp4 et abp1abp4) pour comprendre le role des ABPs dans la croissance et le developpement du mai's. En serre, les mutants different du temoin par la croissance de la feuille et son angle d' insertion sur la tige. Ils ont egalement etudie la croissance des mutants cultives in vitro, dans le noir, exposes a la lumiere bleue (BL) ou rouge (RL), en presence d'auxine exogene. Les plantules etiolees des mutants s'averent plus courtes et moins sensibles a l'auxine que les temoins de type sauvage. Les BL et RL attenuent la sensibilite des plantules a l'auxine, cette reaction etant partiellement controlee par les phytochromes. La suppression de ABP1 et (ou) ABP4 se caracterise par une accumulation differente d'auxine dans les organes des plantules etiolees ou cultivees a la lumiere. En conclusion, ABP1 et ABP4 jouent un role dans la croissance des plantules de mai's et leur reponse a l'auxine, et interagissent avec la(es) voie(s) de signalisation de la lumiere. Nous suggerons une interaction entre ABP1 et ABP4, toutefois dependante de la lumiere, de l' organe et de la reaction etudies. Mots-cles : auxine, proteine liant l'auxine, croissance, lumiere, mai's., Introduction Auxins play a central role in plant growth and development, as they are involved in broad spectrum processes, including embryogenesis, stem elongation, apical dominance, photo- and gravitropism, and lateral [...]

As a second messenger, calcium is involved in auxin signaling, and previous studies demonstrated that Arabidopsis CAX1 ([Ca.sup.2+]/[H.sup.+] exchanger) is involved in the auxin transduction pathway. This study was performed to investigate the possible role of auxin-binding proteins ABP1 and ABP4 in [Ca.sup.2+]/auxin-regulated growth in maize (Zea mays L.). We identified and cloned two AtCAXl homologs in maize, ZCAX2 and ZCAX3. Using maize loss-of-function abpl and abp4 mutants, the role of ABPs in [Ca.sup.2+]dependent growth and in the [Ca.sup.2+]/ auxin-regulated expression of the CAX genes was investigated in etiolated maize seedlings. Exogenous [Ca.sup.2+] enhanced mesocotyl but not coleoptile growth in WT, abpl, abp4, and abp1/abp4 mutants, but the maximum stimulation was in abp4. As well, in the abp4 mutant, maximum accumulation of [Ca.sup.2+] was observed when seedlings were exposed to exogenous [Ca.sup.2+]. In the mesocotyl of abp4 and double mutants, the expression of ZCAX3 was significantly reduced in the absence of exogenous [Ca.sup.2+], whereas exogenous [Ca.sup.2+] significantly up-regulated its expression in both mutants. This effect of [Ca.sup.2+] was not observed in the coleoptile. In the absence of NAA, knockout of ABP4 led to significant drop of ZCAX3 expression in the mesocotyl, and exogenous auxin significantly inhibited expression of the ZCAX3 in WT, but not in abp mutants. This effect of auxin was not observed in the coleoptile. Our results indicate that in the absence of NAA, functional ABP4 is required for ZCAX3 expression and that ABP4 mediates the inhibitory effect of NAA on ZCAX3 expression. We provided evidence for a cross talk between ABP4, exogenous auxin, [Ca.sup.2+], and ZCAX3 during growth of etiolated maize mesocotyl. Key words: auxin-binding protein, ABP4, AtCAXl, calcium, CAX, growth, maize, mesocotyl. En tant que messager secondaire, le calcium joue un role dans la voie de signalisation de l'auxine. Des etudes ont demontre que CAXl (echangeur [Ca.sup.2+]/[H.sup.+])d'Arabidopsis est implique dans cette voie de signalisation. Cette etude a ete menee de facon a determiner le role des proteines liant l'auxine, ABPl et ABP4, dans la croissance du mais (Zea mays L.) regulee par [Ca.sup.2+]/auxine. Nous avons identifie et clone chez le mais deux homologues de AtCAXl, ZCAX2 et ZCAX3. En utilisant les mutants de mais perte-de-fonction abpl et abp4, nous avons etudie le role des ABPs d'une part dans la croissance dependante du [Ca.sup.2+] et d'autre part dans l'expression des genes CAX regulee a la fois par le [Ca.sup.2+] et l'auxine. Le [Ca.sup.2+] exogene stimule la croissance du mesocotyle mais pas du coleoptile chez le WT, les mutants abp1, abp4 et abp1/abp4, meme si l'effet optimum est observe pour le mutant abp4. De la meme facon, chez le mutant abp4, l'accumulation maximale de [Ca.sup.2+] est observee lorsque les plantules sont exposees au [Ca.sup.2+] exogene. Dans le mesocotyle de abp4 et du double mutant, l'expression de ZCAX3 est significativement reduite en l'absence de [Ca.sup.2+] exogene ; a l'oppose, l'application de [Ca.sup.2+] induit significativement l'expression de ZCAX3 chez ces deux mutants. Ceteffet du[Ca.sup.2+]n'estpas observe dans le coleoptile. En l'absence de NAA, l'absence dugene ABP4 se caracterise par une diminution significative de l'expression de ZCAX3 dans le mesocotyle, et la presence d'auxine exogene inhibe significativement l'expression de ZCAX3 chez le WT mais pas chez les mutants abp. Cet effet de l'auxine n'est pas observe au niveau du coleoptile. Nos resultats indiquent qu'en l'absence de NAA, ABP4 est requis pour assurer l'expression de ZCAX3 et que ABP4 sert d'intermediaire dans l'effet inhibiteur de NAA sur l'expression de ZCAX3. Nous apportons ici l'evidence d'une interaction entre ABP4, auxine exogene, [Ca.sup.2+] et ZCAX3 pendant la croissance du mesocotyle etiole de mais. Mots-cles: proteine liant l'auxine, ABP4, AtCAXl, calcium, CAX, croissance, mais, mesocotyle., Introduction For growth and development, plants require metal ions and mineral nutrients whose intracellular concentration has to be maintained at an optimal level. Calcium (Ca) is one of the essential [...]