A demonstration of the utility of fractional experimental design for finding optimal genetic algorithm parameter settings

This paper demonstrates that the use of sparse experimental design in the development of the structure for genetic algorithms, and hence other computer programs, is a particularly effective and efficient strategy. Despite widespread knowledge of the existence of these systematic experimental plans, they have seen limited application in the investigation of advanced computer programs. This paper attempts to address this missed opportunity and encourage others to take advantage of the power of these plans. Using data generated from a full factorial experimental design, involving 27 experimental runs that was used to assess the optimum operating settings of the parameters of a special genetic algorithm (GA), we show that similar results could have been obtained using as few as nine runs. The GA was used to find minimum cost schedules for a complex component assembly operation with many sub-processes

Towards the realisation of an integratated decision support environment for organisational decision making

Traditional decision support systems are based on the paradigm of a single decision maker working at a stand‐alone computer or terminal who has a specific decision to make with a specific goal in mind. Organizational decision support systems aim to support decision makers at all levels of an organization (from executive, middle management managers to operators), who have a variety of decisions to make, with different priorities, often in a distributed and dynamic environment. Such systems need to be designed and developed with extra functionality to meet the challenges such as collaborative working. This paper proposes an Integrated Decision Support Environment (IDSE) for organizational decision making. The IDSE distinguishes itself from traditional decision support systems in that it can flexibly configure and re‐configure its functions to support various decision applications. IDSE is an open software platform which allows its users to define their own decision processes and choose their own exiting decision tools to be integrated into the platform. The IDSE is designed and developed based on distributed client/server networking, with a multi‐tier integration framework for consistent information exchange and sharing, seamless process co‐ordination and synchronisation, and quick access to packaged and legacy systems. The prototype of the IDSE demonstrates good performance in agile response to fast changing decision situations

Virtual integration platform for computational fluid dynamics

Computational Fluid Dynamics (CFD) tools used in shipbuilding industry involve multiple disciplines, such as resistance, manoeuvring, and cavitation. Traditionally, the analysis was performed separately and sequentially in each discipline, which often resulted in conflict and inconsistency of hydrodynamic prediction. In an effort to solve such problems for future CFD computations, a Virtual Integration Platform (VIP) has been developed in the University of Strathclyde within two EU FP6 projects - VIRTUE and SAFEDOR1. The VIP provides a holistic collaborative environment for designers with features such as Project/Process Management, Distributed Tools Integration, Global Optimisation, Version Management, and Knowledge Management. These features enhance collaboration among customers, ship design companies, shipyards, and consultancies not least because they bring together the best expertise and resources around the world. The platform has been tested in seven European ship design companies including consultancies. Its main functionalities along with advances are presented in this paper with two industrial applications

A robust design methodology suitable for application to one-off products

Robust design is an activity of fundamental importance when designing large, complex, one-off engineering products. Work is described which is concerned with the application of the theory of design of experiments and stochastic optimization methods to explore and optimize at the concept design stage. The discussion begins with a description of state-of-the-art stochastic techniques and their application to robust design. The content then focuses on a generic methodology which is capable of manipulating design algorithms that can be used to describe a design concept. An example is presented, demonstrating the use of the system for the robust design of a catamaran with respect to seakeeping

NAVY RETENTION: A CROSS-COMPARISON OF ALL NAVY MEDICINE AND SURFACE WARFARE OFFICER COMMUNITIES

Includes supplementary materialThis thesis examines retention in the Navy Medicine and Surface Warfare communities using an administrative dataset from Defense Manpower Data Center and the Milestone Survey from the Office of the Deputy Chief of Naval Operations (Manpower, Personnel, Training, and Education) (OPNAV N1). Through a combination of descriptive and multivariate logistic models, we find that being a female, having dependents, and being Hispanic are most correlated with separation outcomes in the administrative data. Our survey results indicate that the top reasons for leaving are impact on family, civilian job opportunities, and work-life balance. The top reasons for staying are medical and dental benefits, monetary compensation and retirement, and current job satisfaction. We find that while there is a considerable variation in the intent to leave percentage across communities in the survey, the percent of service members who actually left the Navy voluntarily in the administrative data are similar across the communities. We recommend that the Navy focus on improving the quality of life for members and their families. An additional consideration includes shifting the timeline for assignment of Navy Medicine junior officers to their first sea duty tours and deployments.Lieutenant, United States NavyLieutenant Commander, United States NavyApproved for public release; distribution is unlimited

Developing and applying an integrated modular design methodology within a SME

Modularity within a product can bring advantages to the design process by facilitating enhanced design reuse, reduced lead times, decreased cost and higher levels of quality. While the benefits of modularity are becoming increasingly better known, at present it is usually left to the designers themselves to introduce modularity into products. Studies into modularity have shown that byimplementing 'formal' methods, further benefits can be made in terms of time, cost, quality and performance. Current approaches that have been proposed for the formal development of modular design methodologies fail to accurately represent knowledge that is inherently produced during design projects and fail to consider design from the different viewpoints of the development process. This work, built on previous work on modularity and design for reuse, aims to develop an integrated design methodology that will optimise the modules created through the design process and allow for modularity to be 'built-in' to product development from the initial stages. The methodology andassociated tools have been developed to provide an easy-to-use approach to modularity that has support for design rationales and company knowledge that aid in effective design decision making. The methodology, named GeMoCURE, provides an integrated total solution to modular design based on reuse of proven physical and knowledge modules. Its incremental nature allows for the optimalstructure to be maintained as the design progresses. A special focus has been on the application of this approach for Small to Medium Enterprises (SMEs), which are typically challenged by a lack of design human resources and expertise

Integrated engineering environments for large complex products

An introduction is given to the Engineering Design Centre at the University of Newcastle upon Tyne, along with a brief explanation of the main focus towards large made-to-order products. Three key areas of research at the Centre, which have evolved as a result of collaboration with industrial partners from various sectors of industry, are identified as (1) decision support and optimisation, (2) design for lifecycle, and (3) design integration and co-ordination. A summary of the unique features of large made-to-order products is then presented, which includes the need for integration and co-ordination technologies. Thus, an overview of the existing integration and co-ordination technologies is presented followed by a brief explanation of research in these areas at the Engineering Design Centre. A more detailed description is then presented regarding the co-ordination aspect of research being conducted at the Engineering Design Centre, in collaboration with the CAD Centre at the University of Strathclyde. Concurrent Engineering is acknowledged as a strategy for improving the design process, however design coordination is viewed as a principal requirement for its successful implementation. That is, design co-ordination is proposed as being the key to a mechanism that is able to maximise and realise any potential opportunity of concurrency. Thus, an agentoriented approach to co-ordination is presented, which incorporates various types of agents responsible for managing their respective activities. The co-ordinated approach, which is implemented within the Design Co-ordination System, includes features such as resource management and monitoring, dynamic scheduling, activity direction, task enactment, and information management. An application of the Design Co-ordination System, in conjunction with a robust concept exploration tool, shows that the computational design analysis involved in evaluating many design concepts can be performed more efficiently through a co-ordinated approach

The S-Cycle performance matrix : supporting comprehensive sustainability performance evaluation of technical systems

The work reported in this paper consolidates and rationalises disparate evaluation methods in a novel, generic framework to support the selection of comprehensive material/energetic sustainability performance indicators (SPIs) for technical systems. The S-Cycle Performance Matrix (S-CPMatrix) is comprised of 6 generic sustainability goals, 11 SPI archetypes, and 23 corresponding metrics identified from a model of technical system sustainability (the S-Cycle). The matrix was evaluated by interpreting and classifying 324 indicators currently applied to evaluate technical system sustainability performance in the literature, with 94.1% found to be fully classifiable with respect to the matrix following several refinements. The remaining 5.9% suggested additional SPI archetypes and a goal that were not initially identified. The matrix is intended to support decision makers in meeting three criteria for comprehensiveness identified from the literature: (C1) inclusion of indicators measuring performance at all relevant scales; (C2) inclusion of efficiency and effectiveness indicators; and (C3) coverage of all system sustainability goals. It may be applied to different systems in conjunction with different evaluation methods, thereby contributing to more consistent guidance on the selection of comprehensive SPIs for technical systems. In addition to industrial evaluation and comparison with existing evaluation methods, four avenues for future research were identified: (i) use of the S-CPMatrix to support systems comparison/benchmarking; (ii) further investigation of unsupported metrics; (iii) the nature and measurement of contaminants; and (iv) the comprehensiveness of SPI sets currently used in sustainability performance evaluation of technical systems

Intelligent integrated maintenance for wind power generation

A novel architecture and system for the provision of Reliability Centred Maintenance (RCM) for offshore wind power generation is presented. The architecture was developed by conducting a bottom-up analysis of the data required to support RCM within this specific industry, combined with a top-down analysis of the required maintenance functionality. The architecture and system consists of three integrated modules for Intelligent Condition Monitoring, Reliability and Maintenance Modelling, and Maintenance Scheduling that provide a scalable solution for performing dynamic, efficient and cost effective preventative maintenance management within this extremely demanding renewable energy generation sector. The system demonstrates for the first time, the integration of state-of-the-art advanced mathematical techniques: Random Forests, Dynamic Bayesian Networks, and Memetic Algorithms in the development of an intelligent autonomous solution. The results from the application of the intelligent integrated system illustrated the automated detection of faults within a wind farm consisting of over 100 turbines, the modelling and updating of the turbines’ survivability and creation of a hierarchy of maintenance actions, and the optimising of the maintenance schedule with a view to maximising the availability and revenue generation of the turbines

Population Effect Model Identifies Gene Expression Predictors of Survival Outcomes in Lung Adenocarcinoma for Both Caucasian and Asian Patients

Background: We analyzed and integrated transcriptome data from two large studies of lung adenocarcinomas on distinct populations. Our goal was to investigate the variable gene expression alterations between paired tumor-normal tissues and prospectively identify those alterations that can reliably predict lung disease related outcomes across populations. Methods: We developed a mixed model that combined the paired tumor-normal RNA-seq from two populations. Alterations in gene expression common to both populations were detected and validated in two independent DNA microarray datasets. A 10-gene prognosis signature was developed through a l1 penalized regression approach and its prognostic value was evaluated in a third independent microarray cohort. Results: Deregulation of apoptosis pathways and increased expression of cell cycle pathways were identified in tumors of both Caucasian and Asian lung adenocarcinoma patients. We demonstrate that a 10-gene biomarker panel can predict prognosis of lung adenocarcinoma in both Caucasians and Asians. Compared to low risk groups, high risk groups showed significantly shorter overall survival time (Caucasian patients data: HR = 3.63, p-value = 0.007; Asian patients data: HR = 3.25, p-value = 0.001). Conclusions: This study uses a statistical framework to detect DEGs between paired tumor and normal tissues that considers variances among patients and ethnicities, which will aid in understanding the common genes and signalling pathways with the largest effect sizes in ethnically diverse cohorts. We propose multifunctional markers for distinguishing tumor from normal tissue and prognosis for both populations studied