Development of a multivariable online monitoring system for the thermoforming process

The thermoforming industry has been relatively slow to embrace modern measurement technologies. As a result researchers have struggled to develop accurate thermoforming simulations as some of the key aspects of the process remain poorly understood. For the first time, this work reports the development of a prototype multivariable instrumentation system for use in thermoforming. The system contains sensors for plug force, plug displacement, air pressure and temperature, plug temperature, and sheet temperature. Initially, it was developed to fit the tooling on a laboratory thermoforming machine, but later its performance was validated by installing it on a similar industrial tool. Throughout its development, providing access for the various sensors and their cabling was the most challenging task. In testing, all of the sensors performed well and the data collected has given a powerful insight into the operation of the process. In particular, it has shown that both the air and plug temperatures stabilize at more than 80C during the continuous thermoforming of amorphous polyethylene terephthalate (aPET) sheet at 110C. The work also highlighted significant differences in the timing and magnitude of the cavity pressures reached in the two thermoforming machines. The prototype system has considerable potential for further development. 

Advanced Business Simulations-Incorporating business and process execution data

Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.

GiveMe Shelter: a people-centred design process for promoting independent inquiry-led learning in engineering

It has become increasingly common for tasks traditionally carried out by engineers to be undertaken by technicians and technologist with access to sophisticated computers and software that can often perform complex calculations that were previously the responsibility of engineers. Not surprisingly, this development raises serious questions about the future role of engineers and the education needed to address these changes in technology as well as emerging priorities from societal to environmental challenges. In response to these challenges, a new design module was created for undergraduate engineering students to design and build temporary shelters for a wide variety of end users from refugees, to the homeless and children. Even though the module provided guidance on principles of design thinking and methods for observing users needs through field studies, the students found it difficult to respond to needs of specific end users but instead focused more on purely technical issues.