Multiple In-Mold Sensors for Quality and Process Control in Injection Molding.

The simultaneous improvement of injection molding process efficiency and product quality, as required by Industry 4.0, is a complex, non-trivial task that requires a comprehensive approach, which involves a combination of sensoring and information techniques. In this study, we investigated the suitability of in-mold pressure sensors to control the injection molding process in multi-cavity molds. We have conducted several experiments to show how to optimize the clamping force, switchover, or holding time by measuring only pressure in a multi-cavity mold. The results show that the pressure curves and the pressure integral are suitable for determining optimal clamping force. We also proved that in-channel sensors could be effectively used for a pressure-controlled SWOP. In the volume-controlled method, only the sensors in the cavity were capable of correctly detecting the end of the filling. We proposed a method to optimize the holding phase. In this method, we first determined the integration time of the area under the pressure curve and then performed a model fit using the relationship between the pressure integral and product mass. The saturation curve fitted to the pressure data can easily determine the gate freeze-off time from pressure measurements.

Machine Learning in Injection Molding: An Industry 4.0 Method of Quality Prediction.

One of the essential requirements of injection molding is to ensure the stable quality of the parts produced. However, numerous processing conditions, which are often interrelated in quite a complex way, make this challenging. Machine learning (ML) algorithms can be the solution, as they work in multidimensional spaces by learning the structure of datasets. In this study, we used four ML algorithms (kNN, naïve Bayes, linear discriminant analysis, and decision tree) and compared their effectiveness in predicting the quality of multi-cavity injection molding. We used pressure-based quality indexes (features) as inputs for the classification algorithms. We proved that all the examined ML algorithms adequately predict quality in injection molding even with very little training data. We found that the decision tree algorithm was the most accurate one, with a computational time of only 8-10 s. The average performance of the decision tree algorithm exceeded 90%, even for very little training data. We also demonstrated that feature selection does not significantly affect the accuracy of the decision tree algorithm.

Personalized Mass Production by Hybridization of Additive Manufacturing and Injection Molding.

The new trend in the composites industry, as dictated by Industry 4.0, is the personalization of mass production to match every customer's individual needs. Such synergy can be achieved when several traditional manufacturing techniques are combined within the production of a single part. One of the most promising combinations is additive manufacturing (AM) with injection molding. AM offers higher production freedom in comparison with traditional techniques. As a result, even very sophisticated geometries can be manufactured by AM at a reasonable price. The bottleneck of AM is the production rate, which is several orders of magnitude slower than that of traditional plastic mass production technologies. On the other hand, injection molding is a manufacturing technique for high-volume production with little possibility of customization. The customization of injection-molded parts is usually very expensive and time-consuming. In this research, we offered a solution for the individualization of mass production, which includes 3D printing a baseplate with the subsequent overmolding of a rib element on it. We examined the bonding between the additive-manufactured component and the injection-molded component. As bonding strength between the coupled elements is significantly lower than the strength of the material, we proposed five strategies to improve bonding strength. The strategies are optimizing the printing parameters to obtain high surface roughness, creating an infill density in fused filament fabrication (FFF) parts, creating local infill density, creating microstructures, and incorporating fibers into the bonding area. We observed that the two most effective methods to increase bonding strength are the creation of local infill density and the creation of a microstructure at the contact area of FFF-printed and injection-molded elements. This increase was attributed to the porous structures that both methods created. The melt during injection molding flowed into these pores and formed micro-mechanical interlocking.

Development and Validation of a Test Mold for Thermoplastic Resin Transfer Molding of Reactive PA-6.

Thermoplastic resin transfer molding (T-RTM) is a cutting-edge manufacturing technique for high-volume production of composites with a recyclable thermoplastic matrix. Although a number of reactive thermoplastic matrices as well as industrial manufacturing equipment for T-RTM are commercially available today, the design of a T-RTM mold is still based on the skills and personal experience of the designer. This study summarizes the best knowledge and expertise in mold design and manufacturing and introduces an innovative mold for T-RTM. A concept and basic principles for designing a T-RTM mold are formulated in this study. The mold developed is manufactured and validated.

Modeling the Thermal Conductivity Inhomogeneities of Injection-Molded Particle-Filled Composites, Caused by Segregation.

Many applications require new materials that have good thermal conductivity, are electrical insulators and can be processed easily and with relatively little energy. A new innovative solution for this problem is thermally conductive composites, which can replace metals in many cases. Many papers have focused on the prediction of their thermal conductivity. At the same time segregation has to be taken into account in the case of composites because it affects the distribution of thermally conductive particles, and thus local thermal conductivities. In this paper, we examined and modeled segregation during injection molding and its effect on thermal conductivity. We injection-molded samples from polypropylene with glass beads of different sizes and analyzed their filler content as a function of the flow path. We described the distribution of the filler with a mathematical model. Using this, we created a new, segregation-dependent model that describes the local thermal conductivity of polymer composites as a function of filler content with great accuracy.

A Review of Thermoplastic Resin Transfer Molding: Process Modeling and Simulation.

The production and consumption of polymer composites has grown continuously through recent decades and has topped 10 Mt/year. Until very recently, polymer composites almost exclusively had non-recyclable thermoset matrices. The growing amount of plastic, however, inevitably raises the issue of recycling and reuse. Therefore, recyclability has become of paramount importance in the composites industry. As a result, thermoplastics are coming to the forefront. Despite all their advantages, thermoplastics are difficult to use as the matrix of high-performance composites because their high viscosity complicates the impregnation process. A solution could be reactive thermoplastics, such as PA-6, which is synthesized from the ε-caprolactam (ε-CL) monomer via anionic ring opening polymerization (AROP). One of the fastest techniques to process PA-6 into advanced composites is thermoplastic resin transfer molding (T-RTM). Although nowadays T-RTM is close to commercial application, its optimization and control need further research and development, mainly assisted by modeling. This review summarizes recent progress in the modeling of the different aspects of the AROP of ε-CL. It covers the mathematical modeling of reaction kinetics, pressure-volume-temperature behavior, as well as simulation tools and approaches. Based on the research results so far, this review presents the current trends and could even plot the course for future research.

In-Mold Sensors for Injection Molding: On the Way to Industry 4.0.

The recent trend in plastic production dictated by Industry 4.0 demands is to acquire a great deal of data for manufacturing process control. The most relevant data about the technological process itself come from the mold cavity where the plastic part is formed. Manufacturing process data in the mold cavity can be obtained with the help of sensors. Although many sensors are available nowadays, those appropriate for in-mold measurements have certain peculiarities. This study presents a comprehensive overview of in-mold process monitoring tools and methods for injection molding process control. It aims to survey the recent development of standard sensors used in the industry for the measurement of in-mold process parameters, as well as research attempts to develop unique solutions for solving certain research and industrial problems of injection molding process monitoring. This review covers the established process monitoring techniques-direct temperature and pressure measurement with standard sensors and with the newly developed sensors, as well as techniques for the measurement of indirect process parameters, such as viscosity, warpage or shrinkage.

Thermoplastic Overmolding onto Injection-Molded and In Situ Polymerization-Based Polyamides.

We investigated products manufactured by in situ polymerization, which were reinforced with overmolded ribs. We developed our own mold and prototype product for the project. We used three different materials as preform: a material with a magnesium catalyst, manufactured by in situ polymerization, a Brüggemann AP-NYLON-based in situ polymerization material and an injection-molded PA6 (Durethan B30S, Lanxess GmbH) material. The ribs were formed from the same PA6 material (Durethan B30S, Lanxess GmbH). We examined the effect of the different technological parameters through the pull-off of the overmolded ribs. We measured the effect of melt temperature, holding pressure and holding time, and mold temperature. Considering the individual preforms, we pointed out that monomer migration and binding strength are related, which we concluded from the temperature-dependent mass loss of the materials, measured by thermogravimetric analysis (TGA). Finally, we designed a mold suitable for manufacturing overmolded parts. We designed and built pressure and temperature sensors into the mold to examine and analyze pressures and temperatures around the welding zone of the materials.

Enhanced Injection Molding Simulation of Advanced Injection Molds.

The most time-consuming phase of the injection molding cycle is cooling. Cooling efficiency can be enhanced with the application of conformal cooling systems or high thermal conductivity copper molds. The conformal cooling channels are placed along the geometry of the injection-molded product, and thus they can extract more heat and heat removal is more uniform than in the case of conventional cooling systems. In the case of copper mold inserts, cooling channels are made by drilling and heat removal is facilitated by the high thermal conductivity coefficient of copper, which is several times that of steel. Designing optimal cooling systems is a complex process; a proper design requires injection molding simulations, but the accuracy of calculations depends on how precise the input parameters and boundary conditions are. In this study, three cooling circuit designs and three mold materials (Ampcoloy 940, 1.2311 (P20) steel, and MS1 steel) were used and compared using numerical methods. The effect of different mold designs and materials on cooling efficiency were examined using calculated and measured results. The simulation model was adjusted to the measurement results by considering the joint gap between the mold inserts.

Honorary authorship and symbolic violence.

This paper invokes the conceptual framework of Bourdieu to analyse the mechanisms, which help to maintain inappropriate authorship practices and the functions these practices may serve. Bourdieu's social theory with its emphasis on mechanisms of domination can be applied to the academic field, too, where competition is omnipresent, control mechanisms of authorship are loose, and the result of performance assessment can be a matter of symbolic life and death for the researchers. This results in a problem of game-theoretic nature, where researchers' behaviour will be determined more by the logic of competition, than by individual character or motives. From this follows that changing this practice requires institutionalized mechanisms, and change cannot be expected from simply appealing to researchers' individual conscience. The article aims at showing that academic capital (administrative power, seniority) is translated into honorary authorship. With little control, undetected honorary authorship gives the appearance of possessing intellectual capital (scientific merit). In this way a dominant position is made to be seen as natural result of intellectual ability or scientific merit, which makes it more acceptable to those in dominated positions. The final conclusion of this paper is that undemocratic authorship decisions and authorship based performance assessment together are a form of symbolic violence.

Combined cluster and discriminant analysis: An efficient chemometric approach in diesel fuel characterization.

Combined cluster and discriminant analysis (CCDA) as a chemometric tool in compound specific isotope analysis of diesel fuels was studied. The stable carbon isotope ratios (δ13C) of n-alkanes in diesel fuel can be used to characterize or differentiate diesels originating from different sources. We investigated 25 diesel fuel samples representing 20 different brands. The samples were collected from 25 different service stations in 11 European countries over a 2 year period. The n-alkane fraction of diesel fuels was separated using solid-state urea clathrate formation combined with silica gel fractionation. The stable carbon isotope ratios of C10-C24 n-alkanes were measured with gas chromatography-isotope ratio mass spectrometry (GC-IRMS) using perdeuterated n-alkanes as internal standards. Beside the 25 samples one additional diesel fuel was prepared and measured three times to get totally homogenous samples in order to test the performance of our analytical and statistical routine. Stable isotope ratio data were evaluated with hierarchical cluster analysis (HCA), principal component analysis (PCA) and CCDA. CCDA combines two multivariate data analysis methods hierarchical cluster analysis with linear discriminant analysis (LDA). The main idea behind CCDA is to compare the goodness of preconceived (based on the sample origins) and random groupings. In CCDA all the samples were compared pairwise. The results for the parallel sample preparations showed that the analytical procedure does not have any significant effect on the δ13C values of n-alkanes. The three parallels proved to be totally homogenous with CCDA. HCA and PCA can be useful tools when the examining of the relationship among several samples is in question. However, these two techniques cannot be always decisive on the origin of similar samples. The initial hypothesis that all diesel fuel samples are considered chemically unique was verified by CCDA. The main advantage of CCDA is that it gives an objective index number about the level of similarity among the investigated samples. Thus the application of CCDA supplemented by the traditionally used multivariate methods greatly improves the efficiency of statistical analysis in the CSIA of diesel fuel samples.

Characterisation of the large-scale production process of oyster mushroom (Pleurotus ostreatus) with the analysis of succession and spatial heterogeneity of lignocellulolytic enzyme activities.

Oyster mushroom (Pleurotus ostreatus) lignocellulolytic enzyme activity pattern and variation was investigated in a large-scale facility from spawning until the end of the second flush. In the first cultivation cycle laccase production reached its peak during vegetative growth stage, while manganese-peroxidase showed the highest activity during fruiting body induction. Cellulose and hemicellulose degrading enzymes had maximal activity at the beginning of flush and harvest stage. The enzyme activities showed similar tendencies among five different mushroom substrate blocks representing a production house. The spatial variability analysis of enzyme activities pointed out the within substrate block heterogeneity as the main source if variation. This result was confirmed by Combined Cluster and Discriminant Analysis (CCDA) method showing minimal among block heterogeneity considering the whole investigation period; furthermore in the first cultivation cycle all blocks were grouped into one cluster.

Optimization of the monitoring network on the River Tisza (Central Europe, Hungary) using combined cluster and discriminant analysis, taking seasonality into account.

The most essential requirement for water management is efficient and informative monitoring. Operating water quality monitoring networks is a challenge from both the scientific and economic points of view, especially in the case of river sections ranging over hundreds of kilometers. Therefore, spatio-temporal optimization is vital. In the present study, the optimization of the monitoring system of the River Tisza, the second largest river in Central Europe, is presented using a generally applicable and novel method, combined cluster and discriminant analysis (CCDA). This area for the study was chosen because, spatial inhomogeneity of a river's monitoring network can more easily be studied in a mostly natural watershed - as in the case of the River Tisza - since the effects of man-made obstacles: e.g water barrage systems, hydroelectric power plants, artificial lakes, etc. are more pronounced. Furthermore, since the temporal sampling frequency was bi-weekly, the opportunity of optimizing the monitoring system on a temporal (monthly) scale arose. In the research, 15 water quality parameters measured at 14 sampling sites in the Hungarian section of the River Tisza were assessed for the time period 1975-2005. First, four within-year sections ("hydrochemical seasons") were determined, characterized with unequal lengths, namely 2, 4, 2, and 4 months long starting with spring. Homogeneous groups of sampling sites were determined in space for every season, with the main separating factors being the tributaries and man-made obstacles. Similarly, an overall pattern of homogeneity was determined. As an overall result, the 14 sampling sites could be grouped into 11 homogeneous groups leading to the possibility of reducing the number of sampling locations and thus making the monitoring system more cost-efficient.

Migration of Tinuvin P and Irganox 3114 into milk and the corresponding authorised food simulant.

Migration of Tinuvin P (UV stabiliser) and Irganox 3114 (antioxidant) from high-density polyethylene (HDPE) was studied. HDPE pieces were soaked in either milk (1.5% or 3.5% fat content) or 50% (v/v) ethanol-water mixture - the food simulant for milk as specified in Regulation No. 10/2011/EC. The obtained extracts were analysed by LC-MS/MS. For statistical assessment variography was used. It proved to be a useful tool for making a distinction between the early migration range and the equilibrium, despite the variance of the data. Regulation No. 10/2011/EC specifies 10 days of contact time for milk at 5°C. Our experiments with the food simulant with 24 dm(2) kg(-1) surface/mass ratio showed that both Tinuvin P and Irganox 3114 need less than 1 h to reach equilibrium. Furthermore, 10-day experiments with daily sampling showed that these additives are stable in milk, as well as in the food simulant. The effect of the concentration of the additives in HDPE was studied in the 0.01-5% (m/m) range. For both Tinuvin P and Irganox 3114 and all three extractants the migrated amount became independent of the concentration of the additive in the HDPE approximately at 1% (m/m). For Tinuvin P the food simulant gave a close estimate for the milk samples. However, using the food simulant for modelling the migration of Irganox 3114 into milk gave an overestimation with a factor of minimum 3.5. In the case of Tinuvin P special care must be taken, since the recommended amount in the HDPE can result in additive concentrations near or even over the specific migration limit (SML). However, Irganox 3114 cannot reach the SML either in milk or in the food simulant.

[Current issues in psychiatric ethics]. / A pszichiátriai etika aktuális kérdései.

The article analyzes some ethical problems in psychiatry that have been emerging in recent years. It deals with the ongoing intensive debates about the DSM-5 before its publication, and with some of the criticisms of the DSM-5 itself. Then it goes on to analyze the use of placebo. This is followed by the ethical problems of the treatment of ADHD with stimulant drugs, among which one is the question of authenticity, namely whether the pre-treatment or the post-treatment personality is the real, authentic self of the patient. This question has been raised not only in the case of the ADHD, but also in relation with the antidepressant treatment of depression earlier, and in relation with deep brain stimulation and dopamine replacement therapy now, all of which causes changes in the treated patient's personality and motivations. Finally the article describes some ethical problems of informed consent in the case of antidepressant medication, together with the necessity to involve psychiatric nurses and rating scales in the assessment of the patient's decision making capacity.

Polarization transition between sunlit and moonlit skies with possible implications for animal orientation and Viking navigation: anomalous celestial twilight polarization at partial moon.

Using full-sky imaging polarimetry, we measured the celestial distribution of polarization during sunset and sunrise at partial (78% and 72%) and full (100%) moon in the red (650 nm), green (550 nm), and blue (450 nm) parts of the spectrum. We investigated the temporal change of the patterns of degree p and angle α of linear polarization of sunlit and moonlit skies at dusk and dawn. We describe here the position change of the neutral points of sky polarization, and present video clips about the celestial polarization transition at moonlit twilight. We found that at partial moon and at a medium latitude (47° 15.481' N) during this transition there is a relatively short (10-20 min) period when (i) the maximum of p of skylight decreases, and (ii) from the celestial α pattern neither the solar-antisolar nor the lunar-antilunar meridian can be unambiguously determined. These meridians can serve as reference directions of animal orientation and Viking navigation based on sky polarization. The possible influence of these atmospheric optical phenomena during the polarization transition between sunlit and moonlit skies on the orientation of polarization-sensitive crepuscular/nocturnal animals and the hypothesized navigation of sunstone-aided Viking seafarers is discussed.

[Informed consent of the surgical patient]. / Tájékozott beleegyezés a sebészetben.

The article analyses the consequences of the paradigm shift in the surgical practice in the last fifty years. The earlier, paternalistic physician-patient relationship has been replaced by an equal one, which is based on informing the patient and involving him or her in the treatment decisions. This shift did not happen uniformly in various medical subspecialties. In this respect, surgery is more conservative than general medicine. The article analyses the most frequent problems of informing patients, and examines the major elements of information, together with their technical conditions in surgery. It reflects on specifics of surgical information disclosure and conditions of refusing medical interventions.

Honorary authorship epidemic in scholarly publications? How the current use of citation-based evaluative metrics make (pseudo)honorary authors from honest contributors of every multi-author article.

The current use of citation-based metrics to evaluate the research output of individual researchers is highly discriminatory because they are uniformly applied to authors of single-author articles as well as contributors of multi-author papers. In the latter case, these quantitative measures are counted, as if each contributor were the single author of the full article. In this way, each and every contributor is assigned the full impact-factor score and all the citations that the article has received. This has a multiplication effect on each contributor's citation-based evaluative metrics of multi-author articles, because the more contributors an article has, the more undeserved credit is assigned to each of them. In this paper, I argue that this unfair system could be made fairer by requesting the contributors of multi-author articles to describe the nature of their contribution, and to assign a numerical value to their degree of relative contribution. In this way, we could create a contribution-specific index of each contributor for each citation metric. This would be a strong disincentive against honorary authorship and publication cartels, because it would transform the current win-win strategy of accepting honorary authors in the byline into a zero-sum game for each contributor.

Response to the commentaries of Melissa S Anderson and Murray J Dyck.

Anderson and Dyck claim that the current trend of almost exclusively using citation-based evaluative metrics to assess the research output of scholars is unsound. I agree with them in this, but I feel that, for practical reasons, this system will not disappear in the near future, so we must concentrate on making it fairer. Both commentators doubt whether numerically expressing each contributor's relative contribution is feasible. I admit that an important precondition for this task is the possibility of an informed, democratic debate among equals about the relative contribution of each contributor to the article. Mechanisms should be established to protect vulnerable researchers in the academic field in the same way as safeguards exist today to protect vulnerable research participants. Theoretically, however, I think that the fair allocation of authorship credit is possible, and much of this task is already being performed routinely when contributors determine the order of their names in the byline, being well aware of the widespread assumption that this order mostly mirrors the order of their relative contributions. All they would have to do as an additional task is to express this order in numbers. If they cannot reach a consensus, they could always choose not to express their relative contribution in numbers, in which case the presumption would be that they contributed equally. My proposal could, at best, make the system fairer and, at worst, not reduce the options that evaluators already have.