Function allocation theory for creative design

Function structure influences on systems architecture (or product architecture). This paper discusses a design method for creative design solutions that focuses on the allocation of functions. It first proposes a theory called “Function Allocation Theory” to allocate a function to an appropriate subsystem or component during the systems decomposition phase. By doing so, the complexity of design solutions can be reduced. The theory is applied to some examples including collaborative robots and robotics maintenance. Finally, the paper illustrates a case study of designing a reaction-free fastening system using this theory

Design citeria for applications with non-manifest loops

In the design process of high-throughput applications, design choices concerning the type of processor architecture and appropriate scheduling mechanism, have to be made. Take a reed-solomon decoder as an example, the amount of clock cycles consumed in decoding a code is dependent on the amount of errors within that code. Since this is not known in advance, and the environment in which the code is transmitted can cause a variable amount of errors within that code, a processor architecture which employs a static scheduling scheme, has to assume the worst case amount of clock cycles in order to cope with the worst case situation and provide correct results. On the other hand a processor that employs a dynamic scheduling scheme, can gain wasted clock cycles, by scheduling the exact amount of clock cycles that are needed and not the amount of clock cycles needed for the worst case situation. Since processor architectures that employ dynamic scheduling schemes have more overhead, designers have to make their choice beforehand. In this paper we address the problem of making the correct choice of whether to use a static or dynamic scheduling scheme. The strategy is to determine whether the application possess non-manifest behavior\ud and weigh out this dynamic behavior against static scheduling solutions which were quite common in the past. We provide criteria for choosing the correct scheduling architecture for a high throughput application based upon the environmental and algorithm-specification constraints. Keywords¿ Non-manifest loop scheduling, variable latency functional units, dynamic hardware scheduling, self\ud scheduling hardware units, optimized data-flow machine architecture

Visualisation of semantic architectural information within a game engine environment

Because of the importance of graphics and information within the domain of architecture, engineering and construction (AEC), an appropriate combination of visualisation technology and information management technology is of utter importance in the development of appropriately supporting design and construction applications. We therefore started an investigation of two of the newest developments in these domains, namely game engine technology and semantic web technology. This paper documents part of this research, containing a review and comparison of the most prominent game engines and documenting our architectural semantic web. A short test-case illustrates how both can be combined to enhance information visualisation for architectural design and construction

Factory modelling: data guidance for analysing production, utility and building architecture systems

Work on energy and resource reduction in factories is dependent on the availability of data. Typically, available sources are incomplete or inappropriate for direct use and manipulation is required. Identifying new improvement opportunities through simulation across factory production, utility and building architecture domains requires analysis of model feasibility, particularly in terms of system data composition, input resolution and simulation result fidelity. This paper reviews literature on developing appropriate model data for assessing energy and material flows at factory level. Gaps are found in guidance for analysis and integration of resource-flows across system boundaries. The process for how data was prepared, input and iteratively developed alongside conceptual and simulation models is described. The case of a large-scale UK manufacturer is presented alongside discussions on challenges associated with factory level modelling, and the insights gained from understanding the effect of data clarity on system performance

Applications of recurrent neural networks in batch reactors. Part I: NARMA modelling of the dynamic behaviour of the heat transfer fluid

This paper is focused on the development of nonlinear models, using artificial neural networks, able to provide appropriate predictions when acting as process simulators. The dynamic behaviour of the heat transfer fluid temperature in a jacketed chemical reactor has been selected as a case study. Different structures of NARMA (Non-linear ARMA) models have been studied. The experimental results have allowed to carry out a comparison between the different neural approaches and a first-principles model. The best neural results are obtained using a parallel model structure based on a recurrent neural network architecture, which guarantees better dynamic approximations than currently employed neural models. The results suggest that parallel models built up with recurrent networks can be seen as an alternative to phenomenological models for simulating the dynamic behaviour of the heating/cooling circuits which change from batch installation to installation.Publicad