Feed Screw Research Articles

Extrusion of a Curcuminoid-Enriched Oat Fiber-Corn-Based Snack Product.

Extruded snack products were made from an oat fiber-corn flour matrix fortified with 1.5% (w/w) curcuminoids (750mg curcuminoids/100 g) to improve the solubility and stability of curcuminoids. The effects of extruder feed moisture content (21%, 28%, and 35%) and screw speed (200 and 300 rpm) on the extrusion parameters and physical properties of final snacks were investigated. Curcuminoids lost during extrusion and curcuminoids loss during subsequent drying of extrudates were analyzed, to separate the losses occurring in each unit process. Drying post extrusion (at 50°C for 4hr) was essential to obtain a crunchy shelf stable product (5% moisture). Curcuminoids loss during extrusion was from 17% to 84%, with high loss for the extrusion with low feed moisture content (21%). A further curcuminoids loss of 4% to 44% occurred during drying, with much higher loss for the extrudate with high moisture content. Total curcuminoids retained after extrusion and drying was 12% to 41% (59% to 88% loss), equivalent to 180 to 616 mg curcuminoids retained per 100 g snack, levels within recommended daily dose. Curcuminoids retained after drying was stable during 80 days of storage at 25°C. The results highlighted the importance of understanding the impact of each unit process separately (for example, extrusion and drying) on the stability of curcuminoids for the development of healthier extruded snacks. PRACTICAL APPLICATION: Extruded snacks products were developed by fortifying the snacks with oat fiber and curcuminoids in order to address the need for a healthy ready to eat food products. Some extrusion characteristics were selected to produce snack products which have favorable properties in terms of consumer acceptance.

Повышение точности взвешивания сыпучих материалов на поточном расходомере-дозаторе с двумя тензометрическими датчиками

A weighing algorithm for an on-stream dispenser flow meter based on two strain gauges is developed and investigated. The main objectives are to achieve more accurate dosing of bulk materials and to prevent the influence of uneven material distribution along the weighing axis. Better dosing accuracy is achieved by installing strain gages on the material feeding side and using an intelligent conveyor belt speed control system, which is the main element in the developed weighing algorithm. The conveyor belt speed is adjusted by means of a fuzzy controller, because the controlled plant is a complex system, and the controllers synthesized according to the classical automatic control theory fail to meet the response speed requirements. The results from testing the selected kinematic design clearly show adequate performance of the fuzzy controller. Namely, when the feed of bulk material decreases, so does the conveyor belt speed, and vice versa. As a result, it becomes possible to decrease the relative measurement error to less than 0.5%. The developed device can be used in the food and agricultural-industrial complexes, in the civil construction, and chemical industries, and in other branches of the national economy, namely, in the processes involving metering and measuring the flow of bulk material in continuous technological processes. When used in combination with a feeder, on-stream flow meters can be used for high-precision weighted metering of various bulk materials. The product is supplied by a sluice or screw feeder, which can additionally be equipped with a smaller diameter screw for operation in rough/precise modes.

Rheological Behaviour of PP Nanocomposites by Extrusion Process

The effect of organophilic clay (C15A) in PP compatibilized polymer (PP/PP-g-MA) through rheological experimental results is presented. This study focusses on the description of the rheological behaviour of the organophilic layers along the screws of a twin screw extruder by melting process, varying the screw profile as well as the processing conditions, namely screw speed, temperature and feed rate. Different levels of dispersion were found along the screws for all conditions and positions analyzed by rheology. The qualitative analysis of the images obtained by transmission electron microscopy, reinforced the results. Furthermore, the effects of the processing conditions on dispersion of C15A layers along the screw profile are analyzed using multiple linear regression techniques. The results show statistically significant differences of all rheology measures for all the processing conditions and positions along the extruder.

Modelling and Nonlinear Model Predictive Control of a Twin Screw Feeder

In this work, a dynamic model of a twin screw feeder, for continuous tablet manufacturing, has been developed. In particular, a First Order Plus Dead Time (FOPDT) model has been suggested. The delayed dynamics depends on operating conditions, equipment design and physical properties of the bulk solid. Model parameters are estimated by fitting the model to experimental data. Due to the nonlinear input-output relationships and the time delays involved, a Nonlinear Model Predictive Control (NMPC) is investigated to maintain an accurate mass flow rate, with the ultimate goal to improve product homogeneity in an inherently complex process. The performance of the designed control system is found to be satisfactory in a wide operating range and its potential use in a continuous manufacturing process is worth being investigated in the future.

Dynamic axial contact stiffness analysis of position preloaded ball screw mechanism

This article establishes an axial contact stiffness model of position preloaded ball screw mechanism based on Hertz contact theory. The analysis of dynamic axial contact stiffness is one of the foundations of the research on the dynamic characteristic of the ball screw feed drive system. The model takes into account the coupling relationship between the contact angle and the normal contact force, as well as the coupling relationship between the elastic deformation and the contact deformation coefficient. The static and dynamic axial contact stiffness characteristics of the preloaded ball screw mechanism are studied. The numerical analysis result shows that the static contact stiffness of the preloaded ball screw mechanism increases with the increase in the preload and decreases with the increase in the axial load. The dynamic contact stiffness of the preloaded ball screw mechanism increases with the increase in the screw’s rotational speed. The variation range of dynamic contact stiffness increases with the increase in axial load under the same preload. And the variation range of dynamic contact stiffness decreases with the increase in preload under the same axial load. The axial contact stiffness model established in this article can be used to analyze either static or dynamic contact stiffness of position preloaded ball screw mechanism.

Thermal Performances Prediction Analysis of High Speed Feed Shaft Bearings Under Actual Working Condition

High-speed machining is a key technology for greatly improving productivity and reducing production costs. Angular contact ball bearing is the key component of ball screw feed system. Predictive analysis of bearings thermal behavior is significant to ensure the working accuracy of machine tools. Due to the continuous dynamic changes under actual working conditions, it is difficult to predict and model of the bearings heating characteristics. This paper develops a comprehensive calculation method for predicting the thermodynamic characteristics on high speed feed shaft bearings. Based on quasi-static model and thermal dynamic model, Monte Carlo optimization algorithm is used to inverse the temperature field experimental temperature data. The real heating characteristics of heat source are comprehensively predicted and analyzed, so as to accurately predict the bearing thermal dynamic performances of feed shaft bearings. The research work in this paper lays a strong foundation for the thermal error modeling and thermodynamic analysis of the ball screw feed system of machine tools.

Dynamic Characteristic Optimization of Ball Screw Feed Drive in Machine Tool Based on Modal Extraction of State Space Model

The accurate prediction and research about the dynamic characteristic of machine tool during the design process are essential to develop high-performance machines. In order to consider the effect of mechanical modal characteristics on the whole dynamic performance and servo controller of ball screw feed drive fully, the modal characteristics of mechanical transmission are extracted and solved based on reduced state space matrix of ball screw feed system, which is also easy for integration with servo control model. On this basis, the step-by-step optimization method from the global to the local is proposed to optimize the servo controller and overall dynamic performance of ball screw feed drive. This step-by-step optimization method is as follows: first, the global initial optimal tuning of servo controller parameters under the influence of structure modal characteristics is originally realized through the analytic derivation of servo controller based on the extraction of state space modal characteristics. Second, the integrated model of the feed drive system is established. Finally, based on the above global optimization results, the overall dynamic performance, and the servo parameters of the feed drive system under the influence of the modal characteristics are further studied and optimized locally. Taking the ball screw feed drive studied in this paper like the example, its rise time and the settling time of step response are 0.089 and 0.104s before optimization, while these reduce to 0.038 and 0.092s after optimization. Its dynamic response performance after optimization is much better. The optimization result is also validated by the test: the rise time and the settling time by the test are 0.042 and 0.094s, which are close to that from the simulation. Also, the consistency of step response curves from experiment and simulation as well. All these show that: this prediction and optimization method of overall dynamic performance considering the modal characteristic influence of mechanical transmission fully is correct and reliable.

A comprehensive analysis and optimization of continuous twin-screw granulation processes via sequential experimentation strategy

Nowadays twin-screw granulation has been emerging as an attractive continuous wet granulation technique. This study was geared towards better process design and understanding with emphasis on bridging the knowledge gap between input and output variables by employing sequential experimentation strategy. A low-dose formulation for granulation experiments contained anhydrous caffeine as the model drug. In the first phase of parameter screening, D-optimal design and stepwise regression were leveraged to develop interaction models following the examination of various quantitative and qualitative factors of potential importance. To maximize the design space dictated by predefined quality target values, several variables were fixed at optimum levels: 700 rpm screw speed, 60° kneading element staggering angle, 5 kneading elements and distributive feed screw in the screw configuration. In the second phase of characterization, response surface design was utilized to investigate the dependence of critical quality attributes of granules and tablets on selected critical process parameters (L/S ratio, throughput and barrel temperature). The results indicated that the influence of throughput and barrel temperature was relatively inferior to L/S ratio. Higher degree of liquid saturation led to granules with narrower size distribution, smaller porosity and enhanced flowability and tablets with declining tensile strength yet slackened drug release.

Impact of material properties and process variables on the residence time distribution in twin screw feeding equipment

Screw feeders are integrated as dispensing units in most continuous manufacturing platforms. Hence, characterizing and modelling the residence time distribution (RTD) of materials in feeders is indispensable to understand the traceability of raw materials from the drum till tablet, enabling the separation of non-confirming material. The proposed methodology addressed this leap in knowledge by characterizing materials, performing RTD trials according to an experimental design, applying RTD models and establishing a partial least square (PLS) regression model that links the material properties and process variables with the RTD responses as outputs. Results showed that RTD in screw feeders can be represented by a combination of plug-flow and mixed-flow. Three variables were found to impact the residence time distribution in feeders: flow rate, hopper level and conditioned bulk density. Interestingly, the plug-flow fraction was not affected by variation in flow rate or material properties. Consequently, simple PLS models could be developed that use density and flow rate to predict RTD at a given hopper level. This approach is powerful for RTD prediction based on bulk density in the early phases of development when control strategies for clinical manufacturing need to be established and material availability is still limited.

Valorization of deoiled rice bran by development and process optimization of extrudates

The purpose of this study was to develop extruded snack products using a blend of rice flour, corn flour and deoiled rice bran. Effects of feed moisture (12%–18%), barrel temperature (86⁰C-154 °C) and screw speed (116–284 rpm) on the product properties like lateral expansion (LE), bulk density (BD), water absorption index (WAI), water solubility index (WSI) and hardness (H) were investigated. All these physical properties of extruded snacks were found to be significantly affected by changes in moisture, temperature and screw speed. The regression models for product responses like lateral expansion, bulk density, water absorption index, water solubility index and hardness were highly significant (p ≤ 0.001). The optimized extruded product was obtained at moisture content of 13%, barrel temperature 140 °C, and 203 rpm of screw speed. It was revealed that deoiled rice bran can be incorporated to produce snack products with desirable quality characteristics.

Dynamic Modeling and Experiment Research on Twin Ball Screw Feed System Considering the Joint Stiffness

It is of great significance to study the dynamic characteristics of twin ball screw (TBS) feed system to improve the precision of gantry-type dual-driven computer numerical control (CNC) machine tools. In this paper, an equivalent dynamic model of the TBS feed system is established utilizing lumped mass method considering the stiffness of joints. Equivalent axial stiffness of screw-nut joints and bearing joints are both calculated by Hertz contact theory. Furthermore, a friction model is proposed because the friction force of the screw nut affects the stiffness of the joints. Then, the friction parameters are obtained by using the nonlinear system identification method. Meanwhile, a finite element model (FEM) is developed to assess the dynamic characteristics of TBS feed system under the stiffness of joints. Finally, validation experiments are conducted, and the results show that the positions of the nut and the velocities of worktable greatly affect the dynamic characteristics of the TBS feed system. Compared with the theoretical calculation, FEM and experiments indicate that the dynamic modeling proposed in this article can reach a higher accuracy.

Thermal boundary condition optimization of ball screw feed drive system based on response surface analysis

Abstract To improve the simulation accuracy of the traditional transient thermal characteristics analysis model (TCAM) of the ball screw feed drive system (BSFDS), the optimization method of the thermal boundary conditions (TBCs), including the thermal loads, the convective heat transfer coefficient and the thermal contact resistance (TCR), was proposed. A multi-objective and multi-parameter optimization model was established based on the hybrid response surface (HRS) and a multi-objective genetic algorithm (MOGA) was developed to optimize the above TBCs. To simulate the thermal characteristics of the BSFDS under different working conditions, the generality of the method was extended to predict the TBCs under different feed rates. To validate the effectiveness of the method, the thermal characteristic experiments of BSFDS were conducted. The results showed that the simulation error for the temperature field was reduced from 25% to 10% and that the simulation error for the thermal elongation was reduced from 30% to 11%.

Multiobjective process optimization for betaine enriched spelt flour based extrudates

AbstractThe main purposes of this work are successful modeling of twin‐screw extrusion process using predictive models, investigating the effect of process parameters such as screw speed, feed rate, and feed moisture content on the process and product responses and finally optimizing the process regarding betaine content in the extruded product and energy consumption. The second order polynomial approximation models and the artificial neural network were developed to predict the betaine content, showing the high accuracy in the prediction of experimental results. This study introduces the multiobjective optimization (MOO) approach in the extrusion process of spelt flour. The maximal betaine content (between 1,506.8 and 1,605.2 mg/40 g) and minimal energy consumption (between 101.3 and 108.5 W hr/kg) were indicated by MOO procedure, which were gained using the following input parameters: feed flow rate feed about 24 kg/h, screw speed about 252 RPM and moisture content from 21.6 to 23.4%.Practical applicationsThis study introduces the multiobjective optimization (MOO) approach in the extrusion process of spelt flour, which provides the selection of optimal solution that enables the extruder to reach the optimum conditions of the process and provide decision maker with deeper understanding of the process. The present study analyzes the influence of extrusion cooking parameters like: screw speed, feed flow rate, and feed moisture content on the betaine content in the extrudate product and specific mechanical energy input during the processing of betaine enriched spelt flour based extrudates. One way to improve the intake of betaine in the general population can be to enrich foods with betaine. According to European Breakfast Cereal Association for extruded products portion sizes should be 40 g. Consuming a portion of a functional extrudate product with the addition of betaine (1,500 mg/day) could give expected health effects. Final extrudate product from this study satisfies these statements.

Developing ANN-Kriging hybrid model based on process parameters for prediction of mean residence time distribution in twin-screw wet granulation

Artificial neural network (ANN) modelling is applied to predict the mean residence time of pharmaceutical formulation in a twin-screw granulator. Process parameters including feed flow rate, screw speed, and liquid to solid ratio are correlated with the obtained values of mean residence time to build a predictive tool. In order to improve the ANN predictive capability, a kriging interpolation approach is utilised and both ANN models (before and after kriging) are compared. Experimental data is obtained for wet granulation of microcrystalline cellulose using a bench-scale 12 mm twin-screw granulator. In addition, the effect of screw configurations on mean residence time is investigated by the developed ANN. The ANN model is made of two hidden layers with 2 linear nodes in each layer, and the linear system of equations is derived for the improved ANN model. The results revealed that the developed model was capable of predicting the mean residence time in the granulator more accurately after applying kriging interpolation, with an R2 value of about 0.92 for both training and validation. ANN model after kriging shows a dramatic improvement of R2 by 4% and 22% in training and validating phases, respectively. Also, the RMSE was improved by 40% and 61.5% in training and validating phases, respectively. Furthermore, this improvement was reflected in the contour profiles of the ANN models before and after kriging interpolation, where the model that uses the interpolated data points shows a smoother contour profiles and wider prediction areas. Screw configuration has the most significant effect on the residence time of granules inside the granulator where adding more kneading zones results in a substantial increase in the mean residence time compared to other process parameters.

Effect of extrusion processing and hydrocolloids on the stability of added vitamin B12 and physico-functional properties of the fortified puffed extrudates

An alarming rate of increase in the prevalence of vitamin B12 deficiency has generated the demand for fortified foods therewith. This work focused on the development of vitamin B12 fortified rice extrudates wherein the effect of extrusion variables viz. die temperature (oC), screw speed (rpm) and feed rate (kg/h) on the stability of vitamin B12 and physico-functional properties were evaluated. The stability of vitamin B12 was greatly affected by die temperature and unaffected by screw speed and feed rate. The product with best physico-functional properties as obtained from experimental design (168 °C/229 rpm/4.6 kg/h) gave 54% retention of vitamin B12, while the product with best retention of 77% vitamin B12 (140 °C/150 rpm/4 kg/h) gave extrudates with low expansion ratio, WAI, WSI and high bulk density, hardness, breaking strength index and fracturability. To achieve the desirable combination of high retention of vitamin B12 and best physico-functional properties, hydrocolloids such as guar gum, xanthan gum or carboxymethyl cellulose were added at 5 and 10 g/kg of rice flour. Although all the hydrocolloids improved the physico-functional properties without affecting vitamin B12 stability, carboxymethyl cellulose at 5 g/Kg is recommended for such fortified snacks.

Experiment-based thermal behavior research about the feed drive system with linear scale

Positioning error of the feed drive system has great influence of the machining quality. In order to guarantee the positioning accuracy, the linear grating scale is adopted to form a full-closed loop. However, due to the inner heat sources and environmental temperature variations, the linear grating scale could expand and the thermally induced positional deviation is generated. In this article, temperatures and positional deviations of the ball screw feed drive system and the linear motor feed drive system equipped with linear scales were tested. The factors that affect the positioning error were analyzed. Then, the temperatures and positioning coordinates were used as inputs to build the thermally induced positional deviation model of full closed-loop feed drive system. Based on the model, coordinate values of the machine tool were adjusted and the compensation was implemented. The testing results verified that after compensation, the positional deviations were greatly reduced.

Dynamic modeling and analysis of the nut-direct drive system

For ball screw feed system, it has been a common practice that screw shaft is typically supported by bearings at both ends and is driven by a servo motor through coupling. However, this drive method has a relative low dynamic rigidity due to the influence of the support bearings. In this study, the nut-direct drive system is proposed, where the screw shaft is fixed at both ends and the screw nut is driven by the hollow servo motor through the bolted flange. In order to analyze the advantages of the nut-direct drive system compared with the classical drive, the dynamic models of the classical drive and the nut-direct drive are established based on lumped parameter method, respectively. According to the lumped parameter method, the influence of the table position, the length of screw shaft, and the nominal diameter of screw shaft on the natural frequency are analyzed. Furthermore, to analyze the influence of the mechanical system on position tracking accuracy, the mechanical systems of the classical drive and the nut-direct drive are integrated into the control system using the same control parameters, respectively. Results indicate that the nut-direct drive has faster responsiveness and better position tracking accuracy compared with the classical drive.

Extrusion of wood fibre reinforced poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV) biocomposites: Statistical analysis of the effect of processing conditions on mechanical performance

Wood fibre reinforced polyhydroxyalkanoate (PHA) composites have attracted significant interest as promising new sustainable biocomposites. However, their manufacture can be challenging due to PHA's relatively low thermal stability and melt viscosity. There is currently a lack of understanding of the effect of extrusion processing parameters on the molecular weight of the PHA matrix and, ultimately, on the mechanical properties of the composites. In this study, we show that commercially-relevant mechanical properties of a wood-poly(hydroxybutyrate-co-hydroxyvalerate) (PHBV) composite can be achieved through extrusion processing, even at temperatures as high as 190 °C, by adjusting screw speed and feeding rate, and consequently the induced shear rate and residence time. Moreover, the mechanical properties of 40 wt% wood-PHBV were found to be superior to properties previously reported in the literature. Relative to neat PHBV, a 73% increase in modulus and 80% retention of tensile strength was achieved. A Taguchi approach to experimental design was adopted to systematically investigate the effect of extrusion parameters (temperature profile, screw speed, feeding rate, and fibre mixing) on the processing of neat PHBV biopolymer and wood-PHBV composites with wood contents of 10, 20, 30, and 40 wt%. Evaluation of the mechanical performance was conducted through testing of tensile strength, tensile modulus and strain at maximum load. Changes in molecular weight were analysed via gel permeation chromatography (GPC). For both neat PHBV and wood-PHBV composites, molecular weight Mw was found to decrease under high shear stress and long residence time from 550-650 kDa to 350–550 kDa. However, Mw reductions were not enough to result in a decrease of mechanical performance. This discovery is significant for industrial-scale production as it shows that the processing window for wood-PHBV composites is not as narrow as expected, because thermal degradation can be limited by optimising a combination of processing parameters.

Investigating a Novel Hot Melt Extrusion-Based Drying Technique to Solidify an Amorphous Nanosuspension Using Design of Experiment Methodology.

The hot melt extrusion (HME) technology was explored and optimized to solidify an amorphous nanosuspension using Quality by Design (QbD) methodology. A design of experiments (DoE) approach was used to perform a set of 15 experiments, varying independent variables (feed rate, input temperature, and screw speed) within a design space. Redispersibility index (RDI), moisture content, and process yield constituted the critical quality attributes (CQAs) of the experimental design. Regression analysis and ANOVA were employed to identify and estimate significant main effects and two-way interactions, and model the process of HME drying for predictive purposes. The optimized HME-dried end product was characterized for physicochemical properties using differential scanning calorimetry (DSC), X-ray powder diffractions (XRPD), polarized light microscopy (PLM), Fourier transform infrared spectroscopy (FTIR), and in vitro dissolution studies. The statistical analysis reveals feed rate and input temperature as significant independent variables, critically influencing RDI and moisture content of solidified end product. The model developed for process yield was insignificant at a p-value of 0.05. The API retained its amorphous nature after the extrusion process which was confirmed using DSC and XRPD techniques. PLM was unsuitable to differentiate and determine crystallinity of drug moiety in the presence of a semi-crystalline bulking agent, microcrystalline cellulose (MCC). In vitro dissolution study depicted solubility and dissolution enhancement for HME-dried amorphous nanosuspension in both the dissolution media which can be attributed to amorphous nature of nanosized drug particles. A well-designed study implemented by DoE aided in developing a robust and novel HME technique to dry aqueous nanosuspension.

Process optimization of extrusion variables and its effect on properties of extruded cocoyam (Xanthosoma sagittifolium) noodles.

The current industrial demand for starchy foods has been dominated by other roots and tubers, while cocoyam, despite being rich in fiber, minerals, and vitamins has remained under exploited. In this study, the effect of feed moisture content (FMC), screw speed (SS) and barrel temperature (BT) on the quality characteristics of cocoyam noodles (proximate, thermo‐physical, physicochemical, texture, color, extrudate properties, and sensory characteristics) were investigated using central composite design (CCD) of response surface methodology (RSM). Flour was produced from fresh tubers of cocoyam (Xanthosoma sagittifolium) and subsequently processed into noodles using a twin screw extruder. Results showed that the proximate compositions, thermo‐physical, physicochemical properties, and color of the cocoyam noodles were significantly (p < 0.05) influenced by the extrusion process variables. The texture and extrudate properties of cocoyam noodles were equally significantly (p < 0.05) different. The experimental data obtained and predicted values of the response models were comparable, with statistical indices [absolute average deviation (AAD, 0–0.23), bias factor (B f, 1–1.08), and accuracy factor (A f, 1–1.23)] indicating the validity of the derived models. The optimal extrusion processing conditions for quality cocoyam noodles were FMC, SS, and BT of 47.5%, 700 rpm and 50°C, respectively, as cocoyam noodles obtained at these conditions had comparable properties and were most preferred and accepted by the sensory panelists.