Optimization of Multifunctional Battery Structures for Mars

Multifunctional structures are a potentially disruptive technology that allows for significant mass savings on spacecraft. The specific concept addressed herein is that of a multifunctional power structure. In this paper, a parametric optimisation of the design of such a structure that uses commercially available battery cells is presented. Using numerical modelling, it was found that there exists several trade-offs aboutthe conflict between the capacity of the panel and its mechanical properties. It was found that there is no universal optimal location for the cells. Placing them close to the mechanical interfaces increases loading in the mechanically weak cells whereas placing them at the centre of the panel increases the stress inthe panel and reduces the stiffness of the structure.

Sensor Optimisation via H∞ Applied to a MAGLEV Suspension System

In this paper a systematic method via H∞ control design is proposed to select a sensor set that satisfies a number of input criteria for a MAGLEV suspension system. The proposed method recovers a number of optimised controllers for each possible sensor set that satisfies the performance and constraint criteria using evolutionary algorithms.

Introductory Design Optimisation of a Machine Tool using a Virtual Machine Concept

Designing modern machine tools is a complex task. A simulation tool to aid the design work, a virtual machine, has therefore been developed in earlier work. The virtual machine considers the interaction between the mechanics of the machine (including structural flexibility) and the control system. This paper exemplifies the usefulness of the virtual machine as a tool for product development. An optimisation study is conducted aiming at improving the existing design of a machine tool regarding weight and manufacturing accuracy at maintained manufacturing speed. The problem can be categorised as constrained multidisciplinary multiobjective multivariable optimisation. Parameters of the control and geometric quantities of the machine are used as design variables. This results in a mix of continuous and discrete variables and an optimisation approach using a genetic algorithm is therefore deployed. The accuracy objective is evaluated according to international standards. The complete systems model shows nondeterministic behaviour. A strategy to handle this based on statistical analysis is suggested. The weight of the main moving parts is reduced by more than 30 per cent and the manufacturing accuracy is improvement by more than 60 per cent compared to the original design, with no reduction in manufacturing speed. It is also shown that interaction effects exist between the mechanics and the control, i.e. this improvement would most likely not been possible with a conventional sequential design approach within the same time, cost and general resource frame. This indicates the potential of the virtual machine concept for contributing to improved efficiency of both complex products and the development process for such products. Companies incorporating such advanced simulation tools in their product development could thus improve its own competitiveness as well as contribute to improved resource efficiency of society at large.

Cost Based Warranty Optimisation Using Genetic Algorithm

Warranty is a powerful marketing tool for the manufacturer and a good protection for both the manufacturer and the customer. However, warranty always involves additional costs to the manufacturer, which depend on product reliability characteristics and warranty parameters. This paper presents an approach to optimisation of warranty parameters for known product failure distribution to reduce the warranty costs to the manufacturer while retaining the promotional function of the warranty. Combination free replacement and pro-rata warranty policy is chosen as a model and the length of free replacement period and pro-rata policy period are varied, as well as the coefficients that define the pro-rata cost function. Multiparametric warranty optimisation is done by using genetic algorithm. Obtained results are guideline for the manufacturer to choose the warranty policy that minimises the costs and maximises the profit.

Optimising Business Rules in the Services Sector

Business rules are widely used within the services sector. They provide consistency and allow relatively unskilled staff to process complex transactions correctly. But there are many examples where the rules themselves have an impact on the costs and profits of an organisation. Financial services, transport and human services are areas where the rules themselves can impact the bottom line in a predictable way. If this is the case, how can we find that set of rules that maximise profit, performance or customer service, or any other key performance indicators? The manufacturing, energy and process industries have embraced mathematical optimisation techniques to improve efficiency, increase production and so on. This paper explores several real world (but simplified) problems in the services sector and shows how business rules can be optimised. It also examines the similarities and differences between the service and other sectors, and how optimisation techniques could be used to deliver similar benefits.

Source Optimisation of Laser-Plasma Bremmstrahlung for Applications in Engineering Imaging

High Power Lasers produce an intense burst of Bremmstrahlung radiation which has potential applications in broadband x-ray radiography. Since the radiation produced is through the interaction of accelerated electrons with the remaining laser target, these bursts are extremely short – in the region of a few ps. As a result, the laser-produced x-rays are capable of imaging complex dynamic objects with zero motion blur.

A Comparison of Experimental Data with Monte Carlo Calculations for Optimisation of the Sourceto- Detector Distance in Determining the Efficiency of a LaBr3:Ce (5%) Detector

Cerium-doped lanthanum bromide LaBr3:Ce(5%) crystals are considered to be one of the most advanced scintillator materials used in PET scanning, combining a high light yield, fast decay time and excellent energy resolution. Apart from the correct choice of scintillator, it is also important to optimise the detector geometry, not least in terms of source-to-detector distance in order to obtain reliable measurements and efficiency. In this study a commercially available 25 mm x 25 mm BrilLanCeTM 380 LaBr3: Ce (5%) detector was characterised in terms of its efficiency at varying source-to-detector distances. Gamma-ray spectra of 22Na, 60Co, and 137Cs were separately acquired at distances of 5, 10, 15, and 20cm. As a result of the change in solid angle subtended by the detector, the geometric efficiency reduced in efficiency with increasing distance. High efficiencies at low distances can cause pulse pile-up when subsequent photons are detected before previously detected events have decayed. To reduce this systematic error the source-to-detector distance should be balanced between efficiency and pulse pile-up suppression as otherwise pile-up corrections would need to be necessary at short distances. In addition to the experimental measurements Monte Carlo simulations have been carried out for the same setup, allowing a comparison of results. The advantages and disadvantages of each approach have been highlighted.

Novel Hybrid Approaches For Real Coded Genetic Algorithm to Compute the Optimal Control of a Single Stage Hybrid Manufacturing Systems

This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.

Towards Medical Device Maintenance Workflow Monitoring

Concerning the inpatient care the present situation is characterized by intense charges of medical technology into the clinical daily routine and an ever stronger integration of special techniques into the clinical workflow. Medical technology is by now an integral part of health care according to consisting general accepted standards. Purchase and operation thereby represent an important economic position and both are subject of everyday optimisation attempts. For this purpose by now exists a huge number of tools which conduce more likely to a complexness of the problem by a comprehensive implementation. In this paper the advantages of an integrative information-workflow on the life-cycle-management in the region of medical technology are shown.

A Dynamic Programming Model for Maintenance of Electric Distribution System

The paper presents dynamic programming based model as a planning tool for the maintenance of electric power systems. Every distribution component has an exponential age depending reliability function to model the fault risk. In the moment of time when the fault costs exceed the investment costs of the new component the reinvestment of the component should be made. However, in some cases the overhauling of the old component may be more economical than the reinvestment. The comparison between overhauling and reinvestment is made by optimisation process. The goal of the optimisation process is to find the cost minimising maintenance program for electric power distribution system.