Development and Validation of an In‐Line API Quantification Method Using AQbD Principles Based on UV‐Vis Spectroscopy to Monitor and Optimise Continuous Hot Melt Extrusion Process

open access journalA key principle of developing a new medicine is that quality should be built in, with a thorough understanding of the product and the manufacturing process supported by appropriate process controls. Quality by design principles that have been established for the development of drug products/substances can equally be applied to the development of analytical procedures. This paper presents the development and validation of a quantitative method to predict the concentration of piroxicam in Kollidon® VA 64 during hot melt extrusion using analytical quality by design principles. An analytical target profile was established for the piroxicam content and a novel in‐line analytical procedure was developed using predictive models based on UV‐Vis absorbance spectra collected during hot melt extrusion. Risks that impact the ability of the analytical procedure to measure piroxicam consistently were assessed using failure mode and effect analysis. The critical analytical attributes measured were colour (L* lightness, b* yellow to blue colour parameters—in‐process critical quality attributes) that are linked to the ability to measure the API content and transmittance. The method validation was based on the accuracy profile strategy and ICH Q2(R1) validation criteria. The accuracy profile obtained with two validation sets showed that the 95% β‐expectation tolerance limits for all piroxicam concentration levels analysed were within the combined trueness and precision acceptance limits set at ±5%. The method robustness was tested by evaluating the effects of screw speed (150–250 rpm) and feed rate (5–9 g/min) on piroxicam content around 15% w/w. In‐line UV‐Vis spectroscopy was shown to be a robust and practical PAT tool for monitoring the piroxicam content, a critical quality attribute in a pharmaceutical HME process

Scaling Effects in Laser-Based Additive Manufacturing Processes

Mechanical Engineerin

Thermophysical Phenomena in Metal Additive Manufacturing by Selective Laser Melting: Fundamentals, Modeling, Simulation and Experimentation

Among the many additive manufacturing (AM) processes for metallic materials, selective laser melting (SLM) is arguably the most versatile in terms of its potential to realize complex geometries along with tailored microstructure. However, the complexity of the SLM process, and the need for predictive relation of powder and process parameters to the part properties, demands further development of computational and experimental methods. This review addresses the fundamental physical phenomena of SLM, with a special emphasis on the associated thermal behavior. Simulation and experimental methods are discussed according to three primary categories. First, macroscopic approaches aim to answer questions at the component level and consider for example the determination of residual stresses or dimensional distortion effects prevalent in SLM. Second, mesoscopic approaches focus on the detection of defects such as excessive surface roughness, residual porosity or inclusions that occur at the mesoscopic length scale of individual powder particles. Third, microscopic approaches investigate the metallurgical microstructure evolution resulting from the high temperature gradients and extreme heating and cooling rates induced by the SLM process. Consideration of physical phenomena on all of these three length scales is mandatory to establish the understanding needed to realize high part quality in many applications, and to fully exploit the potential of SLM and related metal AM processes

Random field sampling for a simplified model of melt-blowing considering turbulent velocity fluctuations

In melt-blowing very thin liquid fiber jets are spun due to high-velocity air streams. In literature there is a clear, unsolved discrepancy between the measured and computed jet attenuation. In this paper we will verify numerically that the turbulent velocity fluctuations causing a random aerodynamic drag on the fiber jets -- that has been neglected so far -- are the crucial effect to close this gap. For this purpose, we model the velocity fluctuations as vector Gaussian random fields on top of a k-epsilon turbulence description and develop an efficient sampling procedure. Taking advantage of the special covariance structure the effort of the sampling is linear in the discretization and makes the realization possible

Near infrared and Raman spectroscopy for the in-process monitoring of pharmaceutical production processes

A

Kaedah pembelajaran lukisan kejuruteraan berasaskan simulasi

Kajian yang dijalankan ini adalah untuk melihat kebolehgunaan sebuah perisian pendidikan yang menerapkan Kaedah Pembelajaran Lukisan Kejuruteraan Berasaskan Simulasi bagi menyelesaikan masalah kurang faham , kurang minat dan kebergantungan yang terlalu memusat kepada guru di kalangan pelajar Tingkatan 4, Sekolah Menengah Ungku Aziz, Sabak Bernam, Selangor . Justeru, penyampaian isi kandungan yang bersesuaian dengan tahap pemikiran atau kognitif pelajar, aspek minat dan motivasi serta pembelajaran ala akses kendiri dirasakan sebagai faktor utama yang ingin dikenal pasti dalam perisian yang dibangunkan bagi menyelesaikan masalah tersebut. Macromedia Authorware versi 6.5 dipilih sebagai bahasa pengarangan bagi membangunkan perisian pendidikan ini. Seramai 30 responden dipilih untuk mendapatkan maklum balas terhadap kajian ini. Data yang didapati telah dianalisis menggunakan perisian Statistical Package for Social Science (SPSS) versi 11.0 menggunakan kaedah deskriptif min. Hasil kajian mendapati bahawa maklum balas adalah positif terhadap faktor-faktor yang telah dikaji

Accurate prediction of melt pool shapes in laser powder bed fusion by the non-linear temperature equation including phase changes - isotropic versus anisotropic conductivity

In this contribution, we validate a physical model based on a transient temperature equation (including latent heat) w.r.t. the experimental set AMB2018-02 provided within the additive manufacturing benchmark series, established at the National Institute of Standards and Technology, USA. We aim at predicting the following quantities of interest: width, depth, and length of the melt pool by numerical simulation and report also on the obtainable numerical results of the cooling rate. We first assume the laser to posses a double ellipsoidal shape and demonstrate that a well calibrated, purely thermal model based on isotropic thermal conductivity is able to predict all the quantities of interest, up to a deviation of maximum 7.3\% from the experimentally measured values. However, it is interesting to observe that if we directly introduce, whenever available, the measured laser profile in the model (instead of the double ellipsoidal shape) the investigated model returns a deviation of 19.3\% from the experimental values. This motivates a model update by introducing anisotropic conductivity, which is intended to be a simplistic model for heat material convection inside the melt pool. Such an anisotropic model enables the prediction of all quantities of interest mentioned above with a maximum deviation from the experimental values of 6.5\%. We note that, although more predictive, the anisotropic model induces only a marginal increase in computational complexity

The effects of impurities on the performance of silicon solar cells

The major factors that determine the tolerable concentrations of impurities in silicon feedstock for solar cells used in power generation are discussed in this report. It is concluded that a solar-grade silicon can be defined only for a specific manufacturing process. It is also concluded that it is the electrical effects, efficiency and resistivity, that are dominant in determining tolerable concentrations of impurities in the silicon feedstock. Crystal growth effects may become important when faster growth rates and larger crystal diameters are developed and used

Thermooxidative stability of PMMA composites

Tato práce se zabývá studiem termooxidační stability kompozitů polymethylmethakrylátu (PMMA) plněného mikro a nanočásticemi siliky. V připravených vzorcích byly použity různé objemové zlomky a různé velikosti částic siliky. Studium stability bylo prováděno pomocí termogravimetrie, která umožňuje simulovat podmínky termooxidační degradace. Indukční perioda byla stanovena za použití různých rychlostí ohřevu a aplikací izokonverzních metod. Závislosti teplot degradací na rychlostech ohřevu sloužily pro určení parametrů odvozených ze čtyř různých teplotních funkcí, které dovolují předpověď stability materiálu (indukční periody) při zvoleném rozsahu teplot. Zjištěné výsledky ukazují, že větší částice siliky snižuji stabilitu PMMA, zatímco nanočástice v nízkých koncentracích ji nijak neovlivňují.In this work the thermooxidative stability of poly(methyl metacrylate) (PMMA) composites reinforced with silica micro and nanoparticles was studied. Different volume fractions and particles sizes of silica particles were used. PMMA/silica composites were analysed by thermogravimetry which simulated the conditions of thermooxidative degradation. The induction periods were determined using different heating rates and applying the isoconversional methods. The dependence of degradation temperatures on heating rates were used for the determination of adjustable parameters derived for four different temperature functions allowing the prediction of material stability (induction periods) at chosen temperatures. Results showed that the larger silica particles destabilized the PMMA structure while smallest nanoparticles at low concentration had no effect on the stability.