A systemic approach to the design of cellular manufacturing systems

Cellular manufacturing is widely acknowledged as one of the key approaches to achieving world-class performance in batch manufacturing operations. The design of cellular manufacturing systems (CMS) is therefore crucial in determining a company's competitiveness. This thesis postulated that, in order to be effective the design of CMS should not only be systematic but also systemic. A systemic design uses the concepts of the body of work known as the 'systems approach' to ensure that a truly effective CMS is defined. The thesis examined the systems approach and created a systemic framework against which existing approaches to the design of CMS were evaluated. The most promising of these, Manufacturing Systems Engineering (MSE), was further investigated using a series of cross-sectional case-studies. Although, in practice, MSE proved to be less than systemic, it appeared to produce significant benefits. This seemed to suggest that CMS design did not need to be systemic to be effective. However, further longitudinal case-studies showed that the benefits claimed were at an operational level not at a business level and also that the performance of the whole system had not been evaluated. The deficiencies identified in the existing approaches to designing CMS were then addressed by the development of a novel CMS design methodology that fully utilised systems concepts. A key aspect of the methodology was the use of the Whole Business Simulator (WBS), a modelling and simulation tool that enabled the evaluation of CMS at operational and business levels. The most contentious aspects of the methodology were tested on a significant and complex case-study. The results of the exercise indicated that the systemic methodology was feasible.

Simulating the value of collaboration in multi-actor conservation planning

The loss of habitat and biodiversity worldwide has led to considerable resources being spent for conservation purposes on actions such as the acquisition and management of land, the rehabilitation of degraded habitats, and the purchase of easements from private landowners. Prioritising these actions is challenging due to the complexity of the problem and because there can be multiple actors undertaking conservation actions, often with divergent or partially overlapping objectives. We use a modelling framework to explore this issue with a study involving two agents sequentially purchasing land for conservation. We apply our model to simulated data using distributions taken from real data to simulate the cost of patches and the rarity and co-occurence of species. In our model each agent attempted to implement a conservation network that met its target for the minimum cost using the conservation planning software Marxan. We examine three scenarios where the conservation targets of the agents differ. The first scenario (called NGO-NGO) models the situation where two NGOs are both are targeting different sets of threatened species. The second and third scenarios (called NGO-Gov and Gov-NGO, respectively) represent a case where a government agency attempts to implement a complementary conservation network representing all species, while an NGO is focused on achieving additional protection for the most endangered species. For each of these scenarios we examined three types of interactions between agents: i) acting in isolation where the agents are attempting to achieve their targets solely though their own actions ii) sharing information where each agent is aware of the species representation achieved within the other agent’s conservation network and, iii) pooling resources where agents combine their resources and undertake conservation actions as a single entity. The latter two interactions represent different types of collaborations and in each scenario we determine the cost savings from sharing information or pooling resources. In each case we examined the utility of these interactions from the viewpoint of the combined conservation network resulting from both agents' actions, as well as from each agent’s individual perspective. The costs for each agent to achieve their objectives varied depending on the order in which the agents acted, the type of interaction between agents, and the specific goals of each agent. There were significant cost savings from increased collaboration via sharing information in the NGO-NGO scenario were the agent’s representation goals were mutually exclusive (in terms of specie targeted). In the NGO-Gov and Gov-NGO scenarios, collaboration generated much smaller savings. If the two agents collaborate by pooling resources there are multiple ways the total cost could be shared between both agents. For each scenario we investigate the costs and benefits for all possible cost sharing proportions. We find that there are a range of cost sharing proportions where both agents can benefit in the NGO-NGO scenarios while the NGO-Gov and Gov-NGO scenarios again showed little benefit. Although the model presented here has a range of simplifying assumptions, it demonstrates that the value of collaboration can vary significantly in different situations. In most cases, collaborating would have associated costs and these costs need to be weighed against the potential benefits from collaboration. The model demonstrates a method for determining the range of collaboration costs that would result in collaboration providing an efficient use of scarce conservation resources.

Mass transfer in fluidized bed drying of moist particulate

Bubbling fluidized bed technology is one of the most effective mean for interaction between solid and gas flow, mainly due to its good mixing and high heat and mass transfer rate. It has been widely used at a commercial scale for drying of grains such as in pharmaceutical, fertilizers and food industries. When applied to drying of non-pours moist solid particles, the water is drawn-off driven by the difference in water concentration between the solid phase and the fluidizing gas. In most cases, the fluidizing gas or drying agent is air. Despite of the simplicity of its operation, the design of a bubbling fluidized bed dryer requires an understanding of the combined complexity in hydrodynamics and the mass transfer mechanism. On the other hand, reliable mass transfer coefficient equations are also required to satisfy the growing interest in mathematical modelling and simulation, for accurate prediction of the process kinetics. This chapter presents an overview of the various mechanisms contributing to particulate drying in a bubbling fluidized bed and the mass transfer coefficient corresponding to each mechanism. In addition, a case study on measuring the overall mass transfer coefficient is discussed. These measurements are then used for the validation of mass transfer coefficient correlations and for assessing the various assumptions used in developing these correlations.

Analyze impact of context information on rate adaptation algorithm in vehicular communication

Nowadays, road safety and traffic congestion are major concerns worldwide. This is why research on vehicular communication is very vital. In static scenarios vehicles behave typically like in an office network where nodes transmit without moving and with no defined position. This paper analyses the impact of context information on existing popular rate adaptation algorithms. Our simulation was done in MATLAB by observing the impact of context information on these algorithms. Simulation was performed for both static and mobile cases.Our simulations are based on IEEE 802.11p wireless standard. For static scenarios vehicles do not move and without defined positions, while for the mobile case, vehicles are mobile with uniformly selected speed and randomized positions. Network performance are analysed using context information. Our results show that in mobility when context information is used, the system performance can be improved for all three rate adaptation algorithms. That can be explained by that with range checking, when many vehicles are out of communication range, less vehicles contend for network resources, thereby increasing the network performances. © 2013 IEEE.

Hypoxia-inducible factor (HIF) network:insights from mathematical models

Oxygen is a crucial molecule for cellular function. When oxygen demand exceeds supply, the oxygen sensing pathway centred on the hypoxia inducible factor (HIF) is switched on and promotes adaptation to hypoxia by up-regulating genes involved in angiogenesis, erythropoiesis and glycolysis. The regulation of HIF is tightly modulated through intricate regulatory mechanisms. Notably, its protein stability is controlled by the oxygen sensing prolyl hydroxylase domain (PHD) enzymes and its transcriptional activity is controlled by the asparaginyl hydroxylase FIH (factor inhibiting HIF-1).To probe the complexity of hypoxia-induced HIF signalling, efforts in mathematical modelling of the pathway have been underway for around a decade. In this paper, we review the existing mathematical models developed to describe and explain specific behaviours of the HIF pathway and how they have contributed new insights into our understanding of the network. Topics for modelling included the switch-like response to decreased oxygen gradient, the role of micro environmental factors, the regulation by FIH and the temporal dynamics of the HIF response. We will also discuss the technical aspects, extent and limitations of these models. Recently, HIF pathway has been implicated in other disease contexts such as hypoxic inflammation and cancer through crosstalking with pathways like NF?B and mTOR. We will examine how future mathematical modelling and simulation of interlinked networks can aid in understanding HIF behaviour in complex pathophysiological situations. Ultimately this would allow the identification of new pharmacological targets in different disease settings.