Low-cost Process monitoring for polymer extrusion

Polymer extrusion is regarded as an energy-intensive production process, and the real-time monitoring of both energy consumption and melt quality has become necessary to meet new carbon regulations and survive in the highly competitive plastics market. The use of a power meter is a simple and easy way to monitor energy, but the cost can sometimes be high. On the other hand, viscosity is regarded as one of the key indicators of melt quality in the polymer extrusion process. Unfortunately, viscosity cannot be measured directly using current sensory technology. The employment of on-line, in-line or off-line rheometers is sometimes useful, but these instruments either involve signal delay or cause flow restrictions to the extrusion process, which is obviously not suitable for real-time monitoring and control in practice. In this paper, simple and accurate real-time energy monitoring methods are developed. This is achieved by looking inside the controller, and using control variables to calculate the power consumption. For viscosity monitoring, a ‘soft-sensor’ approach based on an RBF neural network model is developed. The model is obtained through a two-stage selection and differential evolution, enabling compact and accurate solutions for viscosity monitoring. The proposed monitoring methods were tested and validated on a Killion KTS-100 extruder, and the experimental results show high accuracy compared with traditional monitoring approaches.

Automatic extruder for processing recycled polymers with ultrasound and temperature control system

Melt viscosity is one of the main factors affecting product quality in extrusion processes particularly with regard to recycled polymers. However, due to wide variability in the physical properties of recycled feedstock, it is difficult to maintain the melt viscosity during extrusion of polymer blends and obtain good quality product without generating scrap. This research investigates the application of ultrasound and temperature control in an automatic extruder controller, which has ability to maintain constant melt viscosity from variable recycled polymer feedstock during extrusion processing. An ultrasonic modulation system has been developed and fitted to the extruder prior to the die to convey ultrasonic energy from a high power ultrasonic generator to the polymer melt. Two separate control loops have been developed to run simultaneously in one controller: the first loop controls the ultrasonic energy or temperature to maintain constant die pressure, the second loop is used to control extruder screw speed to maintain constant throughput at the extruder die. Time response and energy consumption of the control methods in real-time experiments are also investigated and reported this paper.

Process efficiency in polymer extrusion: Correlation between the energy demand and melt thermal stability

Thermal stability is of major importance in polymer extrusion, where product quality is dependent upon the level of melt homogeneity achieved by the extruder screw. Extrusion is an energy intensive process and optimisation of process energy usage while maintaining melt stability is necessary in order to produce good quality product at low unit cost. Optimisation of process energy usage is timely as world energy prices have increased rapidly over the last few years. In the first part of this study, a general discussion was made on the efficiency of an extruder. Then, an attempt was made to explore correlations between melt thermal stability and energy demand in polymer extrusion under different process settings and screw geometries. A commodity grade of polystyrene was extruded using a highly instrumented single screw extruder, equipped with energy consumption and melt temperature field measurement. Moreover, the melt viscosity of the experimental material was observed by using an off-line rheometer. Results showed that specific energy demand of the extruder (i.e. energy for processing of unit mass of polymer) decreased with increasing throughput whilst fluctuation in energy demand also reduced. However, the relationship between melt temperature and extruder throughput was found to be complex, with temperature varying with radial position across the melt flow. Moreover, the melt thermal stability deteriorated as throughput was increased, meaning that a greater efficiency was achieved at the detriment of melt consistency. Extruder screw design also had a significant effect on the relationship between energy consumption and melt consistency. Overall, the relationship between the process energy demand and thermal stability seemed to be negatively correlated and also it was shown to be highly complex in nature. Moreover, the level of process understanding achieved here can help to inform selection of equipment and setting of operating conditions to optimise both energy and thermal efficiencies in parallel. 

Application of Nonlinear PCA for Fault Detection in Polymer Extrusion Processes

This paper describes the application of an improved nonlinear principal component analysis (PCA) to the detection of faults in polymer extrusion processes. Since the processes are complex in nature and nonlinear relationships exist between the recorded variables, an improved nonlinear PCA, which incorporates the radial basis function (RBF) networks and principal curves, is proposed. This algorithm comprises two stages. The first stage involves the use of the serial principal curve to obtain the nonlinear scores and approximated data. The second stage is to construct two RBF networks using a fast recursive algorithm to solve the topology problem in traditional nonlinear PCA. The benefits of this improvement are demonstrated in the practical application to a polymer extrusion process.

The effect of melt viscosity on thermal efficiency for single screw extrusion of HDPE

In this work, a highly instrumented single screw extruder has been used to study the effect of polymer rheology on the thermal efficiency of the extrusion process. Three different molecular weight grades of high density polyethylene (HDPE) were extruded at a range of conditions. Three geometries of extruder screws were used at several set temperatures and screw rotation speeds. The extruder was equipped with real-time quantification of energy consumption; thermal dynamics of the process were examined using thermocouple grid sensors at the entrance to the die. Results showed that polymer rheology had a significant effect on process energy consumption and thermal homogeneity of the melt. Highest specific energy consumption and poorest homogeneity was observed for the highest viscosity grade of HDPE. Extruder screw geometry, set extrusion temperature and screw rotation speed were also found to have a direct effect on energy consumption and melt consistency. In particular, specific energy consumption was lower using a barrier flighted screw compared to single flighted screws at the same set conditions. These results highlight the complex nature of extrusion thermal dynamics and provide evidence that rheological properties of the polymer can significantly influence the thermal efficiency of the process.

The manufacture and characterisation of hot-melt extruded enteric tablets

The aim of this highly novel study was to use hot-melt extrusion technology as an alternative process to enteric coating. In so doing, oral dosage forms displaying enteric properties may be produced in a continuous, rapid process, providing significant advantages over traditional pharmaceutical coating technology. Eudragit (R) L100-55, an enteric polymer, was pre-plasticized with triethyl citrate (TEC) and citric acid and subsequently dry-mixed with 5-aminosalicylic acid, a model active pharmaceutical ingredient (API), and an optional gelling agent (PVP (R) K30 or Carbopol (R) 971P). Powder blends were hot-melt extruded as cylinders, cut into tablets and characterised using powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC) and dissolution testing conducted in both pH 1.2 and pH 6.8 buffers. Increasing the concentration of TEC significantly lowered the glass transition temperature (T,) of Eudragit (R) L100-55 and reduced temperatures necessary for extrusion as well as the die pressure. Moreover, citric acid (17% w/w) was shown to act as a solid-state plasticizer. HME tablets showed excellent gastro-resistance, whereas milled extrudates compressed into tablets released more than 10% w/w of the API in acidic media. Drug release from HME tablets was dependent upon the concentration of TEC, the presence of citric acid, PVP K30, and Carbopol (R) 971P in the matrix, and pH of the dissolution media. The inclusion of an optional gelling agent significantly reduced the erosion of the matrix and drug release rate at pH 6.8; however, the enteric properties of the matrix were lost due to the formation of channels within the tablet. Consequently this work is both timely and highly innovative and identifies for the first time a method of producing an enteric matrix tablet using a continuous hot-melt extrusion process.

A novel approach to dynamic modelling of polymer extrusion for improved process control

Polymer extrusion is a complex process and the availability of good dynamic models is key for improved system operation. Previous modelling attempts have failed adequately to capture the non-linearities of the process or prove too complex for control applications. This work presents a novel approach to the problem by the modelling of extrusion viscosity and pressure, adopting a grey box modelling technique that combines mechanistic knowledge with empirical data using a genetic algorithm approach. The models are shown to outperform those of a much higher order generated by a conventional black box technique while providing insight into the underlying processes at work within the extruder.

Enhancing process insight in polymer extrusion by grey box modelling

Due to the complexity and inherent instability in polymer extrusion there is a need for process models which can be run on-line to optimise settings and control disturbances. First-principle models demand computationally intensive solution, while ‘black box’ models lack generalisation ability and physical process insight. This work examines a novel ‘grey box’ modelling technique which incorporates both prior physical knowledge and empirical data in generating intuitive models of the process. The models can be related to the underlying physical mechanisms in the extruder and have been shown to capture unpredictable effects of the operating conditions on process instability. Furthermore, model parameters can be related to material properties available from laboratory analysis and as such, lend themselves to re-tuning for different materials without extensive remodelling work.

The inferential monitoring of the screw disturbance torque to predict process fluctuations in polymer extrusion

Polymer extrusion is one of the major methods of processing polymer materials and advanced process monitoring is important to ensure good product quality. However, commonly used process monitoring devices, e.g. temperature and pressure sensors, are limited in providing information on process dynamics inside an extruder barrel. Screw load torque dynamics, which may occur due to changes in solids conveying, melting, mixing, melt conveying, etc., are believed to be a useful indicator of process fluctuations inside the extruder barrel. However, practical measurement of the screw load torque is difficult to achieve. In this work, inferential monitoring of the screw load torque signal in an extruder was shown to be possible by monitoring the motor current (armature and/or field) and simulation studies were used to check the accuracy of the proposed method. The ability of this signal to aid identification and diagnosis of process issues was explored through an experimental investigation. Power spectral density and wavelet frequency analysis were implemented together with a covariance analysis. It was shown that the torque signal is dominated by the solid friction in the extruder and hence it did not correlate well with melting fluctuations. However, it is useful for online identification of solids conveying issues.