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
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PhD Thesis (19.36Mb)
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Publication date
2014Supervisor
Whiteside, Benjamin R.Hu, Yim Fun
Institution
University of BradfordDepartment
School of Engineering and InformaticsAwarded
2014Metadata
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Factory 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.Type
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In-process monitoring of micromoulding - assessment of process variation.(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.
