397 resultados para Machinery -- Manufacturing processes


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This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system

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The Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) is the largest study of new firm formation that has ever been undertaken in Australia. CAUSEE follows the development of several samples of new and emerging firms over time. In this report we focus on the drivers of outcomes – in terms of reaching an operational stage vs. terminating the effort – of 493 randomly selected nascent firms whose founders have been comprehensively interviewed on two occasions, 12 months apart. We investigate the outcome effects of three groups of variables: Characteristics of the Venture; Resources Used in the Start-Up Process and Characteristics of the Start-Up Process Itself.

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The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

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The current understanding of students’ group metacognition is limited. The research on metacognition has focused mainly on the individual student. The aim of this study was to address the void by developing a conceptual model to inform the use of scaffolds to facilitate group metacognition during mathematical problem solving in computer supported collaborative learning (CSCL) environments. An initial conceptual framework based on the literature from metacognition, cooperative learning, cooperative group metacognition, and computer supported collaborative learning was used to inform the study. In order to achieve the study aim, a design research methodology incorporating two cycles was used. The first cycle focused on the within-group metacognition for sixteen groups of primary school students working together around the computer; the second cycle included between-group metacognition for six groups of primary school students working together on the Knowledge Forum® CSCL environment. The study found that providing groups with group metacognitive scaffolds resulted in groups planning, monitoring, and evaluating the task and team aspects of their group work. The metacognitive scaffolds allowed students to focus on how their group was completing the problem-solving task and working together as a team. From these findings, a revised conceptual model to inform the use of scaffolds to facilitate group metacognition during mathematical problem solving in computer supported collaborative learning (CSCL) environments was generated.

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Youth population is increasing explosively particularly in developing countries as a result of rapid urbanization. This increase is bringing large number of social and economic problems. For instance the impacts of job and training availability, and the physical, social and cultural quality of urban environment on young people are enormous, and affect their health, lifestyles, and well-being (Gleeson and Sipe 2006). Besides this, globalization and technological developments are affecting youth in urban areas in all parts of the world, both positively and negatively (Robertson 1995). The rapidly advancing information and communications technologies (ICTs) helps in addressing social and economic problems caused by the rapid growth of urban youth populations in developing countries. ICTs offer opportunities to young people for learning, skill development and employment. But there are downsides: young people in many developing countries lack of having broad access to these new technologies, they are vulnerable to global market changes, and ICTs link them into global cultures which promote consumer goods, potentially eroding local cultures and community values (Manacorda and Petrongolo 1999). However we believe that the positives outweigh such negatives. At the beginning of the twenty-first century, the world’s young population number more than they ever have. There are over a billion young people between the ages of 15 and 24, which 85 per cent of them live in developing countries and mainly in urban environments. Many of these young people are in the process of making, or have already made, the transition from school to work. During the last two decades all around the world, these young people, as new workers, have faced a number of challenges associated with globalization and technological advances on labour markets (United Nations 2004). The continuous decrease in the manufacturing employment is made many of the young people facing three options: getting jobs in the informal economy with insecurity and poor wages and working conditions, or getting jobs in the low-tier service industries, or developing their vocational skills to benefit from new opportunities in the professional and advanced technical/knowledge sectors. Moreover in developing countries a large portion of young people are not even lucky enough to choose among any of these options, and consequently facing long-term unemployment, which makes them highly vulnerable. The United Nations’ World Youth Employment report (2004) indicates that in almost all countries, females tend to be far more vulnerable than males in terms of long-term unemployment, and young people who have advanced qualifications are far less likely to experience long-term unemployment than others. In the limited opportunities of the formal labour market, those with limited vocational skills resort to forced entrepreneurship and selfemployment in the informal economy, often working for low pay under hazardous conditions, with only few prospects for the future (United Nations 2005a). The International Labour Organization’s research (2004) revealed that the labour force participation rates for young people decreased by almost four per cent (which is equivalent of 88 million young people) between 1993 and 2003. This is largely as a result of the increased number of young people attending school, high overall unemployment rates, and the fact that some young people gave up any hope of finding work and dropped out of the labour market. At the regional level, youth unemployment was highest in Middle East and North Africa (MENA) (25.6%) and sub-Saharan Africa (21%) and lowest in East Asia (7%) and the industrialized economies(13.4%) (International Labour Organization 2004). The youth in economically disadvantaged regions (e.g. the MENA region) face many challenges in education and training that delivers them the right set of skills and knowledge demanded by the labour market. As a consequence, the transition from school to work is mostly unsuccessful and young population end up either unemployed or underemployed in the informal sectors (United Nations 2005b). Unemployment and lack of economic prospects of the urban youth are pushing many of them into criminal acts, excessive alcohol use, substance addiction, and also in many cases resulting in processes of social or political violence (Fernandez-Maldonado 2004; United Nations 2005a). Long-term unemployment leads young people in a process of marginalisation and social exclusion (United Nations 2004). The sustained high rates of long-term youth unemployment have a number of negative effects on societies. First, it results in countries failing to take advantage of the human resources to increase their productive potential, at a time of transition to a globalized world that inexorably demands such leaps in productive capacity. Second, it reinforces the intergenerational transmission of poverty. Third, owing to the discrepancy between more education and exposure to the mass media and fewer employment opportunities, it may encourage the spread of disruptive behaviours, recourse to illegal alternatives for generating income and the loss of basic societal values, all of which erode public safety and social capital. Fourth, it may trigger violent and intractable political conflicts. And lastly, it may exacerbate intergenerational conflicts when young people perceive a lack of opportunity and meritocracy in a system that favours adults who have less formal education and training but more wealth, power and job stability (Hopenhayn 2002). To assist in addressing youth’s skill training and employment problems this paper scrutinises useful international practices, policies, initiatives and programs targeting youth skill training, particularly in ICTs. The MENA national governments and local authorities could consider implementing similar initiative and strategies to address some of the youth employment issues. The broader aim of this paper is to investigate the successful practice and strategies for the information and communication related income generation opportunities for young people to: promote youth entrepreneurship; promote public-private partnerships; target vulnerable groups of young people; narrow digital divide; and put young people in charge. The rest of this paper is organised in five parts. First, the paper provides an overview of the literature on the knowledge economy, skill, education and training issues. Secondly, it reviews the role of ICTs for vocational skill development and employability. Thirdly, it discusses the issues surrounding the development of the digital divide. Fourthly, the paper underlines types and the importance of developing ICT initiatives targeting young people, and reviews some of the successful policy implementations on ICT-based initiatives from both developed and developing countries that offer opportunities to young people for learning, skill development and employment. Then the paper concludes by providing useful generalised recommendations for the MENA region countries and cities in: advocating possible opportunities for ICT generated employment for young people; and discussing how ICT policies could be modified and adopted to meet young people’s needs.

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The emergence of Enterprise Resource Planning systems and Business Process Management have led to improvements in the design, implementation, and overall management of business processes. However, the typical focus of these initiatives has been on internal business operations, assuming a defined and stable context in which the processes are designed to operate. Yet, a lack of context-awareness for external change leads to processes and supporting information systems that are unable to react appropriately and timely enough to change. To increase the alignment of processes with environmental change, we propose a conceptual framework that facilitates the identification of context change. Based on a secondary data analysis of published case studies about process adaptation, we exemplify the framework and identify four general archetypes of context-awareness. The framework, in combination with the learning from the case analysis, provides a first understanding of what, where, how, and when processes are subjected to change.

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This thesis aims at developing a better understanding of unstructured strategic decision making processes and the conditions for achieving successful decision outcomes. Specifically it focuses on the processes used to make CRE (Corporate Real Estate) decisions. The starting point for this thesis is that our knowledge of such processes is incomplete. A comprehensive study of the most recent CRE literature together with Behavioural Organization Theory has provided a research framework for the exploration of CRE recommended =best practice‘, and of how organizational variables impact on and shape these practices. To reveal the fundamental differences between CRE decision-making in practice and the prescriptive =best practice‘ advocated in the CRE literature, a study of seven Italian management consulting firms was undertaken addressing the aspects of content and process of decisions. This thesis makes its primary contribution by identifying the importance and difficulty of finding the right balance between problem complexity, process richness and cohesion to ensure a decision-making process that is sufficiently rich and yet quick enough to deliver a prompt outcome. While doing so, this research also provides more empirical evidence to some of the most established theories of decision-making while reinterpreting their mono-dimensional arguments in a multi-dimensional model of successful decision-making.