Design methodology for fully dynamic-controlled polynomial profiles and reduced tracking error in CNC machines

High speed and high precision on computer numerically controlled (CNC) machines are major issues for most industrial automation processes. Among the most important factors for precise motion control are the control law, the controller implementation, and the profile reference. The effects of the control law and controller implementation on the tracking error in CNC machines have been widely studied, while the issue of profile reference has not received the required attention. To improve the dynamics provided by the conventional profile reference, several techniques have been proposed, focusing on peak jerk limitation. The novelty of this work is to develop a generalized methodology designed for producing dynamically constrained higher degree piecewise polynomial profiles, without limits in maximum polynomial degrees. They lead to define in an arbitrary way the dynamics shape, while the peak dynamics values constrained are maintained in order to improve the tracking error on CNC systems and giving the possibility to design fully dynamic-controlled trajectories. For experimentation purposes, a two-axis proportional–integral–derivative controller and profile reference generator are implemented in a low-cost field programmable gate array. The experimentation demonstrates the efficiency of the proposed methodology, showing the peak jerk and tracking error reduction, compared against recent reports from literature.     

Pattern Formation in Silicate Glass Corrosion Zones

Alteration zones of archeological glasses often show intriguing lamellar patterns in backscattered electron images. Here, we report results of static glass corrosion experiments with two different silicate glasses that revealed laminar porosity and subordinately chemical patterns inside silica-based corrosion zones that resemble those seen in naturally altered, ancient glasses. Aside from common laminar patterns, more complex patterns were observed in corrosion zones that developed along a fracture network. The formation of such patterns cannot be explained by any of the existing glass corrosion models. We suggest that silica-based corrosion zones form by a process that involves the congruent dissolution of the glass network, which is spatially and temporally coupled to the deposition of amorphous silica at an inwardly moving reaction interface. The patterns likely form in response to fluctuations of the pH and salinity in the interfacial solution, which govern the silica solubility, deposition, and dissolution rate, and thus, its microstructure and porosity, and, in turn, are controlled by the dissolution rate of the glass and the transport properties of the silica reaction layers. However, the exact feedback mechanism producing pH fluctuations in the interfacial solution has not yet been identified and is an open question for future research.     

Fungal dyes for textile applications: testing of industrial conditions for wool fabrics dyeing

Natural dyes and pigments have been proposed as an eco-friendly alternative to artificial pigments. Among the diverse organisms able to synthesize natural dyes and pigments, several wood inhabiting fungi produce extracellular compounds which have been tested to dye fabrics at laboratory conditions with good results. However, the dyeing conditions used at laboratory level not necessary meet the real conditions in which dyeing of fabrics is conducted at industrial level. In this work, yellow and red dyes producing fungi, Penicillium murcianum and Talaromyces australis, respectively, were isolated from wood samples and used to dye wool fabrics at conditions of temperature, pH, additives, and equipment similar to those used at industrial level. After dyeing treatments, color fastness to washing, wet and dry rubbing, and tensile strength were tested. Satisfactory results were found when the dyes were used individually and mixed to different proportions. According to the results, natural dyes synthesized by these two wood inhabiting fungi have great potential to be used for dyeing of wool at industrial level.     

Biohythane production from organic waste: Recent advancements,technical bottlenecks and prospects

The availability of fossil fuels is a major factor that determines the economy of a country. However, possible exhaustion of fossil fuel deposits as well as increased pollution, and other adverse effects on the environment has prompted us to search for alternative fuels. This resulted in the development of hythane, a blend of hydrogen with methane, at concentrations of 10%–30%. The breakdown of organic substrates using sequential dark fermentation (DF) and anaerobic digestion (AD) leads to biohythane production. The quality and quantity of biohythane can be improved by altering the following aspects: selection, development, and/or genetic engineering of suitable microbial consortium; the use of cheap, appropriate substrates; improved design of bioreactors; and the implementation of two-stage fermentation system. This review focusses on the mechanism of biohythane production and the different aspects involved in increasing both its production rate and quality. A comparative study has also been done to demonstrate the superiority of biohythane over other biofuels.     

Comparative analysis on the application of neuro‐fuzzy models for complex engineered systems: Case study from a landfill and a boiler

This work aims at developing an explicit neuro‐fuzzy (NF) model to characterize complex engineered systems associated with high nonlinearity, uncertainties, and multivariable couplings. The NF model synergistically exploits the advantages of fuzzy belongingness of each input variable to all output variables and learning ability of neural networks. Owing to the inherent complexities associated with 2 complex engineered systems, a landfill and a boiler were selected to develop models that provide intelligent decisions for optimizing the operational parameters. Data compiled from field‐scale investigation/real plant operation involving various operating scenarios were used to develop the models. Predicting capability of the developed models was evaluated through the correlation coefficient and mean absolute percentage error values. Superiority of the proposed NF model to other similar models has been justified and demonstrated.     

In‐line monitoring of the injection molding process by dielectric spectroscopy

In recent years, electrical techniques like microdielectrometry have increasingly been utilized for their ability to continuously monitor, in a nondestructive way, the advancement of the reaction of thermoset resins under cure. This paper discusses an extension of this technique for the “in‐situ” monitoring of the crystallization of thermoplastics applied during an injection molding process. Electric sensors were positioned at the walls of the mold cavity so that an analysis of the volume dielectric properties of material during the filling, the post‐filling, and the cooling steps could be carried out. Poly(vinylidene fluoride) was chosen for this study. A correlation between the evolution of the dielectric parameters and the succession of the steps in this process was undertaken. The dielectric response was sufficiently sensitive to identify the steps of the closing of the mold, filling, post‐filling, cooling, and ejection of the part. In addition, information concerning the crystallization phenomenon near the wall or in the middle of the sample was collected. The gradual filling of the cavity of the mold was also identified by dielectric measurements. The temperature dependence of dielectric properties of the sample was beneficial in evaluating the increase of the temperature of the mold with the succession of injection cycles. The influence of the packing pressure has been clearly identified and confirms the usefulness of the dielectric method as a probe for detecting the shrinkage of the part during the optimization phase of the machine parameters. The dielectric method detailed herein provides a new non‐invasive technique and could be applied to a closed‐loop control of the injection molding process.