Yes / Polymer extrusion is an important but an energy intensive method of processing polymeric materials. The rapid increase in demand of polymeric products has forced manufactures to rethink their processing efficiencies to manufacture good quality products with low-unit-cost. Here, analyzing the operational conditions has become a key strategy to achieve both energy and thermal efficiencies simultaneously. This study aims to explore the effects of polymers' rheology on the energy consumption and melt thermal quality (ie, a thermally homogeneous melt flow in both radial and axil directions) of extruders. Six commodity grades of polymers (LDPE, LLDPE, PP, PET, PS, and PMMA) were processed at different conditions in two types of continuous screw extruders. Total power, motor power, and melt temperature profiles were analyzed in an industrial scale single-screw extruder. Moreover, the active power (AP), mass throughput, torque, and power factor were measured in a laboratory scale twin-screw extruder. The results confirmed that the specific energy consumption for both single and twin screw extruders tends to decrease with the processing speed. However, this action deteriorates the thermal stability of the melt regardless the nature of the polymer. Rheological characterization results showed that the viscosity of LDPE and PS exhibited a normal shear thinning behavior. However, PMMA presented a shear thickening behavior at moderate-to-high shear rates, indicating the possible formation of entanglements. Overall, the findings of this work confirm that the materials' rheology has an appreciable correlation with the energy consumption in polymer extrusion and also most of the findings are in agreement with the previously reported investigations. Therefore, further research should be useful for identifying possible correlations between key process parameters and hence to further understand the processing behavior for wide range of machines, polymers, and operating conditions.

Yes / Extrusion is one of the fundamental production methods in the polymer processing industry and is used in the production of a large number of commodities in a diverse industrial sector. Being an energy intensive production method, process energy efficiency is one of the major concerns and the selection of the most energy efficient processing conditions is a key to reducing operating costs. Usually, extruders consume energy through the drive motor, barrel heaters, cooling fans, cooling water pumps, gear pumps, etc. Typically the drive motor is the largest energy consuming device in an extruder while barrel/die heaters are responsible for the second largest energy demand. This study is focused on investigating the total energy demand of an extrusion plant under various processing conditions while identifying ways to optimise the energy efficiency. Initially, a review was carried out on the monitoring and modelling of the energy consumption in polymer extrusion. Also, the power factor, energy demand and losses of a typical extrusion plant were discussed in detail. The mass throughput, total energy consumption and power factor of an extruder were experimentally observed over different processing conditions and the total extruder energy demand was modelled empirically and also using a commercially available extrusion simulation software. The experimental results show that extruder energy demand is heavily coupled between the machine, material and process parameters. The total power predicted by the simulation software exhibits a lagging offset compared with the experimental measurements. Empirical models are in good agreement with the experimental measurements and hence these can be used in studying process energy behaviour in detail and to identify ways to optimise the process energy efficiency.

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Yes / Polymer extrusion is an energy intensive production process and process energy e ciency has become a key concern in the current industry with the pressure of reducing the global carbon footprint. Here, knowledge of the pattern of energy usage and losses of each component in the plant is highly useful in the process energy optimization. Moreover, it is essential to maintain the melt quality while improving the energy e ciency in polymer processing. In this work, an investigation was made on the total energy consumption, drive motor energy consumption, power factor and the melt temperature profile across the die melt flow (as an indication of the melt thermal quality) of an industrial scale extruder with three di erent screw geometries, three polymer types and wide range of processing conditions (altogether 135 di erent processing situations were observed). This aims to widen the knowledge on process energy and thermal behaviors while exploring possible correlation/s between energy demand and melt quality (in terms of melt temperature fluctuations across the melt flow). The results showed that the level and fluctuations of the extruder’s power factor is particularly dependent upon the material being processed. Moreover, it seems that there is a relation between the level of energy demand of the heaters and the level of melt temperature fluctuations. While the extruder specific energy consumption decreases with increasing screw speed, specific energy consumption of the drive motor may have either increasing or decreasing behavior. Overall, this study provides new insights in a wide range on process energy demand and melt thermal quality in polymer extrusion. Moreover, further research is recommended to establish strong correlation/s between process energy consumption and melt thermal quality which should help to enhance process control and hence the product quality in single screw polymer extrusion.

Yes / 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. / This work was funded through an inter-disciplinary research programme (Grant No. EP/G059330/1) by the EPSRC-UK. The technical assistance provided by Ken Howell, Roy Dixon and John Wyborn is greatly appreciated.

Yes / High-throughput manufacturing of transdermal microneedle arrays poses a significant challenge due to the high precision and number of features that need to be produced and the requirement of multi-step processing methods for achieving challenging micro-features. To address this challenge, we report a flexible and cost-effective process chain for transdermal microneedle array manufacture that includes mould production using laser machining and replication of thermoplastic microneedles via micro-injection moulding (micromoulding). The process chain also incorporates an in-line manufacturing data monitoring capability where the variability in the quality of microneedle arrays can be determined in a production run using captured data. Optical imaging and machine vision technologies are also implemented to create a quality inspection system that allows rapid evaluation of key quality indicators. The work presents the capability of laser machining as a cost-effective method for making microneedle moulds and micro-injection moulding of thermoplastic microneedle arrays as a highly-suitable manufacturing technique for large-scale production with low marginal cost. / This research work was undertaken in the context of MICRO-MAN project (“Process Fingerprint for Zero-defect Net-shapeMICROMANufacturing”, http://www.microman.mek.dtu.dk/).MICROMAN is a European Training Network supported byHorizon 2020, the EU Framework Programme for Research andInnovation (Project ID: 674801). This research has also receivedfunding and support from two other Horizon 2020 projects:HIMALAIA (Grant agreement No. 766871) and Laser4Fun (GA no.675063).

Statistical process monitoring and hierarchical Bayesian modeling are two ways to learn more about processes of interest. In this work, we consider two main components: risk-adjusted monitoring and Bayesian hierarchical models for spatial data. Usually, if prior information about a process is known, it is important to incorporate this into the monitoring scheme. For example, when monitoring 30-day mortality rates after surgery, the pre-operative risk of patients based on health characteristics is often an indicator of how likely the surgery is to succeed. In these cases, risk-adjusted monitoring techniques are used. In this work, the practical limitations of the traditional implementation of risk-adjusted monitoring methods are discussed and an improved implementation is proposed. A method to perform spatial risk-adjustment based on exact locations of concurrent observations to account for spatial dependence is also described. Furthermore, the development of objective priors for fully Bayesian hierarchical models for areal data is explored for Gaussian responses. Collectively, these statistical methods serve as analytic tools to better monitor and model spatial processes. / Ph. D.