Model-based observer proposal for surface roughness monitoring

Comunicación presentada a MESIC 2019 8th Manufacturing Engineering Society International Conference (Madrid, 19-21 de Junio de 2019)In the literature, many different machining monitoring systems for surface roughness and tool condition have been proposed and validated experimentally. However, these approaches commonly require costly equipment and experimentation. In this paper, we propose an alternative monitoring system for surface roughness based on a model-based observer considering simple relationships between tool wear, power consumption and surface roughness. The system estimates the surface roughness according to simple models and updates the estimation fusing the information from quality inspection and power consumption. This monitoring strategy is aligned with the industry 4.0 practices and promotes the fusion of data at different shop-floor levels

Variation propagation of bench vises in multi-stage machining processes

Comunicación presentada a MESIC 2019 8th Manufacturing Engineering Society International Conference (Madrid, 19-21 de Junio de 2019)Variation propagation has been successfully modeled by the Stream of Variation (SoV) approach in multistage machining processes. However, the SoV model basically supports 3-2-1 fixtures based on punctual locators and other workholding systems such as conventional vises are not considered yet. In this paper, the SoV model is expanded to include the fixture- and datum-induced variations on workholding devices such as bench vises. The model derivation is validated through assembly and machining simulations on Computer Aided Design software. The case study analyzed shows an average error of part quality prediction between the SoV model and the CAD simulations of 0.26%

Evaluation of the impact of gamification on students’ performance and engagement in manufacturing engineering courses

In engineering courses with a large number of students, fail and dropout rates are usually high even in courses that can be expected to be interesting to the students. Gamification tools have arisen as an interesting way to motivate the students for a real continuous assessment, increasing the student’s attendance and performance. In this paper, a gamification approach based on a Kahoot tool, Moodle activities, and commemorative badges is proposed within a manufacturing course. The designed activities let the students compete among themselves to get the maximum number of points, which will be converted into extra grades that are added to the final exam grade. The gamification experience has been proven to be highly positive according to students’ and instructors’ perceptions, and the average increase of pass rate and course attendance with respect to previous years have increased from 22% to 34% and from 38% to 66%, respectively

Reversible exposure of hydrophobic residues on albumin as a novel strategy for formulation of nanodelivery vehicles for taxanes

AG Garro1, DM Beltramo1,2,3, RV Alasino1, V Leonhard1,2, V Heredia1, ID Bianco1,2,41Center of Excellence in Products and Processes of Córdoba; 2National Research Council of Argentina (CONICET); 3School of Chemistry, Catholic University of Córdoba; 4Department of Exact, Physical and Natural Sciences, National University of La Rioja, ArgentinaBackground: We report herein a novel strategy for the preparation of protein-based nanodelivery vehicles for hydrophobic active pharmaceutical ingredients.Methods: The procedure consisted of three steps, ie, exposure of hydrophobic residues of a protein to a pH-induced partial unfolding: interaction between hydrophobic residues on the protein and the hydrophobic active pharmaceutical ingredient, and a final step where the structure of the protein was reversed to a native-like state by returning to neutral pH. As proof of concept, the interaction of paclitaxel with partially unfolded states of human serum albumin was evaluated as a potential method for the preparation of water-soluble complexes of the taxane with albumin.Results: We found that paclitaxel readily binds to pH-induced partially unfolded albumin, leading to the formation of optically clear water-soluble complexes. The complexes thus formed were more stable in solution when the albumin native state was at least partially restored by neutralization of the solution to a pH around 7. It was also observed that the hydrodynamic radius of human serum albumin was only slightly increased after the cycle of pH changes, remaining in a monomeric state with a size according to paclitaxel binding. Furthermore, paclitaxel binding did not affect the overall exposure of charged groups of human serum albumin, as evaluated by its interaction with an ionic exchange resin.Conclusion: The in vitro biological activity of the complexes formed was qualitatively equivalent to that of a Cremophor®-based formulation.Keywords: human serum albumin, paclitaxel, unfolded states, solubilit

A methodology for data-driven adjustment of variation propagation models in multistage manufacturing processes

In the current paradigm of Zero Defect Manufacturing, it is essential to obtain mathematical models that express the propagation of manufacturing deviations along Multistage Manufacturing Processes (MMPs). Linear physical-based models such as the Stream of Variation (SoV) model are commonly used, but its accuracy may be limited when applied to MMPs with a large amount of stages, mainly because of the modeling errors at each stage that are accumulated downstream. In this paper we propose a methodology to calibrate the SoV model using data from the inspection stations and prior engineering-based knowledge. The data used for calibration does not contain information about the sources of variation, and they must be estimated as part of the model adjustment procedure. The proposed methodology consists of a recursive algorithm that minimizes the difference between the sample covariance of the measured Key Product Characteristic (KPC) deviations and its estimation, which is a function of a variation propagation matrix and the covariance of the deviation of the variation sources. To solve the problem with standard convex optimization tools, Schur complements and Taylor series linearizations are applied. The output of the algorithm is an adjusted model, which consists of a variation propagation matrix and an estimation of the aforementioned variation source covariance. In order to validate the performance of the algorithm, a simulated case study is analyzed. The results, based on Monte Carlo simulations, show that the estimation errors of the KPC deviation covariances are proportional to the measurement noise variance and inversely proportional to the number of processed parts that have been used to train the algorithm, similarly to other process estimators in the literature.Funding for open access charge: CRUE-Universitat Jaume

Model-based tool condition prognosis using power consumption and scarce surface roughness measurements

In machining processes, underusing and overusing cutting tools directly affect part quality, entailing economic and environmental impacts. In this paper, we propose and compare different strategies for tool replacement before processed parts exceed surface roughness specifications without underusing the tool. The proposed strategies are based on an online part quality monitoring system and apply a model-based algorithm that updates their parameters using adaptive recursive least squares (ARLS) over polynomial models whose generalization capabilities have been validated after generating a dataset using theoretical models from the bibliography. These strategies assume that there is a continuous measurement of power consumption and a periodic measurement of surface roughness from the quality department (scarce measurements). The proposed strategies are compared with other straightforward tool replacement strategies in terms of required previous experimentation, algorithm simplicity and self-adaptability to disturbances (such as changes in machining conditions). Furthermore, the cost of each strategy is analyzed for a given benchmark and with a given batch size in terms of needed tools, consumed energy and parts out of specifications (i.e., rejected). Among the analyzed strategies, the proposed model-based algorithm that detects in real-time the optimal instant for tool change presents the best results.Funding for open access charge: CRUE-Universitat Jaume

Extension of the Stream-of-Variation Model for General-Purpose Workholding Devices: Vices and Three-Jaw Chucks

Nowadays, advanced manufacturing models, such as the stream-of-variation (SoV) model, have been successfully applied to derive the complex relationships between fixturing, manufacturing, and datum errors throughout a multistage machining process. However, the current development of the SoV model is still based on 3-2-1 fixturing schemes, and although some improvements have been done, e.g., N-2-1 fixtures, the effect of general workholding systems, such as bench vices or three-jaw chucks, has not yet been included into the model. This article presents the extension of the SoV model to include fixture and datum errors considering both bench vices and three-jaw chucks as fixturing devices in multistage machining processes. The model includes different workholding configurations, and it is shown how to include the workholding accuracy to estimate part quality. The extended SoV model is validated in a three-stage machining process by both machining experimentation and CAD simulations

Secadero solar forzado para productos agricolas

Se propone un secadero solar forzado, formado por un colector solar y una cámara de secado donde se coloca el producto. El colector construido tiene una cobertura de policarbonato de 7.5 m2 . Las paredes de la cámara construida con placas de cemento autoclavadas, tiene una cubierta de policarbonato y una puerta de ingreso en la parte posterior. En el interior se colocan bandejas apiladas donde se coloca el producto. El aire de secado fluye a través del producto por circulación forzada impulsado por medio de dos ventiladores de 0,45 kW, colocados debajo de las bandejas. Para el primer ensayo se eligió papa cortada en bastones. El contenido de humedad de las papas se redujo al 20 % durante 2 días de secado. Se analizan los resultados experimentales durante el tiempo de secadoFil: García, V.. Universidad Nacional de Catamarca; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Salta. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Iriarte, Adolfo Antonio. Universidad Nacional de Catamarca; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Salta. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Justinovich, S.. Universidad Nacional de Catamarca; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Salta. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Angel, L.. Universidad Nacional de Catamarca; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Salta. Instituto de Investigaciones en Energía no Convencional; ArgentinaFil: Heredia, T.. Universidad Nacional de Catamarca; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Salta. Instituto de Investigaciones en Energía no Convencional; Argentin

Diversity of N2-fixing cyanobacteria from Andalusian paddy fields and analysis of their potential as bioinoculants

The marshes of the Guadalquivir River contain the largest area of rice cultivation in Spain, where more than 40,000 ha are used every year for rice production. These wetland areas provide a perfect place for rice cultivation, and represent a unique aquatic-terrestrial habitat that hold more wintering waterfowl than any other European wetland.Paddies require large amounts nitrogen and phosphorus for their growth, development and production. Though, flooded conditions used for rice cultivation drastically diminish efficiency inorganic nitrogen fertilizers, being only 30–40% used by the plant, and in some cases even less. Large amounts of nitrogen fertilizers are dissolved in the surface water and lost, causing environmental pollution and health problems due to losses through N2O and NO volatilization, denitrification, and leaching (Ishii et al., 2011).The paddy field ecosystem provides a favourable environment for the growth of phototrophic microorganisms including nitrogen-fixing cyanobacteria, as it meets their requirements for light, water, temperature and nutrient availability. The ability of this type of cyanobacteria to fix N2 provides a natural source of fixed nitrogen to the plant that is evidently priceless, and encourages research to develop new cyanobacteria-based biofertilizers for rice cultivation. In our laboratory, diversity of N2-fixing cyanobacteria from Andalusian paddies has been studied by means of metagenomic analysis and classical microbiological approaches. We have found that agronomic techniques influence microbial diversity (Ramírez-Moncayo et al., 2018). We have also isolated Nitrogen-fixing cyanobacteria from the paddy fields and we have found that Nostocaceae and Rivulariaceae are the dominant N2-fixing cyanobacteria families in these isolates (Alves-Martínez et al., 2017). Genetic analysis of the different isolates revealed the presence of new uncharacterized strains. We have evaluated their potential as bioinoculants for plant fortification. Some of the strains showed a strong attraction and attachment to rice roots, which could be an indication of possible supply to the plant of nitrogen-fixed metabolites by the cyanobacterium. These isolates might be used for the formulation of new ecological biofertilizers alternative to chemical synthetic fertilizers

A Sequential Inspection Procedure for Fault Detection in Multistage Manufacturing Processes

Fault diagnosis in multistage manufacturing processes (MMPs) is a challenging task where most of the research presented in the literature considers a predefined inspection scheme to identify the sources of variation and make the process diagnosable. In this paper, a sequential inspection procedure to detect the process fault based on a sequential testing algorithm and a minimum monitoring system is proposed. After the monitoring system detects that the process is out of statistical control, the features to be inspected (end of line or in process measurements) are defined sequentially according to the expected information gain of each potential inspection measurement. A case study is analyzed to prove the benefits of this approach with respect to a predefined inspection scheme and a randomized sequential inspection considering both the use and non-use of fault probabilities from historical maintenance data