A service orientated architecture and wireless sensor network approach applied to the measurement and visualisation of a micro injection moulding process. Design, development and testing of an ESB based micro injection moulding platform using Google Gadgets and business processes for the integration of disparate hardware systems on the factory shop floor
SupervisorWhiteside, Benjamin R.
Hu, Yim Fun
KeywordMicro injection moulding; Wireless sensor networks (WSN); Service orientated architecture (SOA); Business processes; Business process execution language (BPEL); Process monitoring; Web services; Enterprise service bus (ESB); Google Gadgets
The University of Bradford theses are licenced under a Creative Commons Licence.
InstitutionUniversity of Bradford
DepartmentSchool of Engineering and Informatics
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AbstractFactory shop floors of the future will see a significant increase in interconnected devices for monitoring and control. However, if a Service Orientated Architecture (SOA) is implemented on all such devices then this will result in a large number of permutations of services and composite services. These services combined with other business level components can pose a huge challenge to manage as it is often difficult to keep an overview of all the devices, equipment and services. This thesis proposes an SOA based novel assimilation architecture for integrating disparate industrial hardware based processes and business processes of an enterprise in particular the plastics machinery environment. The key benefits of the proposed architecture are the reduction of complexity when integrating disparate hardware platforms; managing the associated services as well as allowing the Micro Injection Moulding (µIM) process to be monitored on the web through service and data integration. An Enterprise Service Bus (ESB) based middleware layer integrates the Wireless Sensor Network (WSN) based environmental and simulated machine process systems with frontend Google Gadgets (GGs) based web visualisation applications. A business process framework is proposed to manage and orchestrate the resulting services from the architecture. Results from the analysis of the WSN kits in terms of their usability and reliability showed that the Jennic WSN was easy to setup and had a reliable communication link in the polymer industrial environment with the PER being below 0.5%. The prototype Jennic WSN based µIM process monitoring system had limitations when monitoring high-resolution machine data, therefore a novel hybrid integration architecture was proposed. The assimilation architecture was implemented on a distributed server based test bed. Results from test scenarios showed that the architecture was highly scalable and could potentially allow a large number of disparate sensor based hardware systems and services to be hosted, managed, visualised and linked to form a cohesive business process.
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Modelling and optimisation of oxidative desulphurization process for model sulphur compounds and heavy gas oil. Determination of Rate of Reaction and Partition Coefficient via Pilot Plant Experiment; Modelling of Oxidation and Solvent Extraction Processes; Heat Integration of Oxidation Process; Economic Evaluation of the Total Process.Mujtaba, Iqbal M.; Khalfalla, Hamza Abdulmagid (University of BradfordSchool of Engineering, Design and Technology, 2010-02-26)Heightened concerns for cleaner air and increasingly more stringent regulations on sulphur content in transportation fuels will make desulphurization more and more important. The sulphur problem is becoming more serious in general, particularly for diesel fuels as the regulated sulphur content is getting an order of magnitude lower, while the sulphur contents of crude oils are becoming higher. This thesis aimed to develop a desulphurisation process (based on oxidation followed by extraction) with high efficiency, selectivity and minimum energy consumption leading to minimum environmental impact via laboratory batch experiments, mathematical modelling and optimisation. Deep desulphurization of model sulphur compounds (di-n-butyl sulphide, dimethyl sulfoxide and dibenzothiophene) and heavy gas oils (HGO) derived from Libyan crude oil were conducted. A series of batch experiments were carried out using a small reactor operating at various temperatures (40 ¿ 100 0C) with hydrogen peroxide (H2O2) as oxidant and formic acid (HCOOH) as catalyst. Kinetic models for the oxidation process are then developed based on `total sulphur approach¿. Extraction of unoxidised and oxidised gas oils was also investigated using methanol, dimethylformamide (DMF) and N-methyl pyrolidone (NMP) as solvents. For each solvent, the `measures¿ such as: the partition coefficient (KP), effectiveness factor (Kf) and extractor factor (Ef) are used to select the best/effective solvent and to find the effective heavy gas oil/solvent ratios. A CSTR model is then developed for the process for evaluating viability of the large scale operation. It is noted that while the energy consumption and recovery issues could be ignored for batch experiments these could not be ignored for large scale operation. Large amount of heating is necessary even to carry out the reaction at 30-40 0C, the recovery of which is very important for maximising the profitability of operation and also to minimise environmental impact by reducing net CO2 release. Here the heat integration of the oxidation process is considered to recover most of the external energy input. However, this leads to putting a number of heat exchangers in the oxidation process requiring capital investment. Optimisation problem is formulated using gPROMS modelling tool to optimise some of the design and operating parameters (such as reaction temperature, residence time and splitter ratio) of integrated process while minimising an objective function which is a coupled function of capital and operating costs involving design and operating parameters. Two cases are studied: where (i) HGO and catalyst are fed as one feed stream and (ii) HGO and catalyst are treated as two feed streams. A liquid-liquid extraction model is then developed for the extraction of sulphur compounds from the oxidised heavy gas oil. With the experimentally determined KP multi stage liquid-liquid extraction process is modelled using gPROMS software and the process is simulated for three different solvents at different oil/solvent ratios to select the best solvent, and to obtain the best heavy gas oil to solvent ratio and number of extraction stages to reduce the sulphur content to less than 10 ppm. Finally, an integrated oxidation and extraction steps of ODS process is developed based on the batch experiments and modelling. The recovery of oxidant, catalyst and solvent are considered and preliminary economic analysis for the integrated ODS process is presented.
In-process monitoring of micromoulding - assessment of process variation.Whiteside, Benjamin R.; Coates, Philip D.; Martyn, Michael T. (2005)Advances in micromoulding technology are leading to complex,net-shape products having sub-milligramme masses with micro-scale surface features in a range of polymer and nano-composite materials.For such small components subjected to the extreme stress,strain-rate and temperature gradients encountered in the micromoulding process,detailed process monitoring is desirable to highlight variations in moulding conditions and assist in creating a viable manufacturing process with acceptable quality products.This paper covers the implementation of a suite of sensors on a commercial micromoulding machine and detailed computer monitoring during processing of a polyacetal component over a range of processing conditions.The results determined that cavity pressure curve integral data provides the most sensitive factor for characterisation of a moulding process of a 0.34 mm~3(0.49 mg)product.The repeatability of the process is directly compared with that of a 15.6mm~3(22.2 mg)product and shown to beinferior.DSC measurements of the whole products indicated little variation in average crystallinity of the products manufactured over a mould temperature range of 30 to 130deg C.
Neural network based hybrid modelling and MINLP based optimisation of MSF desalination process within gPROMS: Development of neural network based correlations for estimating temperature elevation due to salinity, hybrid modelling and MINLP based optimisation of design and operation parameters of MSF desalination process within gPROMSMujtaba, Iqbal M.; Sowgath, Md Tanvir (University of BradfordSchool of Engineering Design and Technology, 2007)Desalination technology provides fresh water to the arid regions around the world. Multi-Stage Flash (MSF) distillation process has been used for many years and is now the largest sector in the desalination industry. Top Brine Temperature (TBT) (boiling point temperature of the feed seawater in the first stage of the process) is one of the many important parameters that affect optimal design and operation of MSF processes. For a given pressure, TBT is a function of Boiling Point Temperature (BPT) at zero salinity and Temperature Elevation (TE) due to salinity. Modelling plays an important role in simulation, optimisation and control of MSF processes and within the model, calculation of TE is therefore important for each stages (including the first stage, which determines the TBT). Firstly, in this work, several Neural Network (NN) based correlations for predicting TE are developed. It is found that the NN based correlations can predict the experimental TE very closely. Also predictions of TE by the NN based correlations were found to be good when compared to those obtained using the existing correlations from the literature. Secondly, a hybrid steady state MSF process model is developed using gPROMS modelling tool embedding the NN based correlation. gPROMS provides an easy and flexible platform to build a process flowsheet graphically. Here a Master Model connecting (automatically) the individual unit model (brine heater, stages, etc.) equations is developed which is used repeatedly during simulation and optimisation. The model is validated against published results. Seawater is the main source raw material for MSF processes and is subject to seasonal temperature variation. With fixed design the model is then used to study the effect of a number of parameters (e.g. seawater and steam temperature) on the freshwater production rate. It is observed that, the variation in the parameters affect the rate of production of fresh water. How the design and operation are to be adjusted to maintain a fixed demand of fresh water through out the year (with changing seawater temperature) is also investigated via repetitive simulation. Thirdly, with clear understanding of the interaction of design and operating parameters, simultaneous optimisation of design and operating parameters of MSF process is considered via the application MINLP technique within gPROMS. Two types of optimisation problems are considered: (a) For a fixed fresh water demand throughout the year, the external heat input (a measure of operating cost) to the process is minimised; (b) For different fresh water demand throughout the year and with seasonal variation of seawater temperature, the total annualised cost of desalination is minimised. It is found that seasonal variation in seawater temperature results in significant variation in design and some of the operating parameters but with minimum variation in process temperatures. The results also reveal the possibility of designing stand-alone flash stages which would offer flexible scheduling in terms of the connection of various units (to build up the process) and efficient maintenance of the units throughout the year as the weather condition changes. In addition, operation at low temperatures throughout the year will reduce design and operating costs in terms of low temperature materials of construction and reduced amount of anti-scaling and anti-corrosion agents. Finally, an attempt was made to develop a hybrid dynamic MSF process model incorporating NN based correlation for TE. The model was validated at steady state condition using the data from the literature. Dynamic simulation with step changes in seawater and steam temperature was carried out to match the predictions by the steady state model. Dynamic optimisation problem is then formulated for the MSF process, subjected to seawater temperature change (up and down) over a period of six hours, to maximise a performance ratio by optimising the brine heater steam temperature while maintaining a fixed water demand.