32 resultados para Pattern Mining
Resumo:
Environmental accountability has become a major source of competitive advantage for industrial companies, because customers consider it as relevant buying criterion. However, in order to leverage their environmental responsibility, industrial suppliers have to be able to demonstrate the environmental value of their products and services, which is also the aim of Kemira, a global water chemistry company considered in this study. The aim of this thesis is to develop a tool which Kemira can use to assess the environmental value of their solutions for the customer companies in mining industry. This study answers to questions on what kinds of methods to assess environmental impacts exist, and what kind of tool could be used to assess the environmental value of Kemira’s water treatment solutions. The environmental impacts of mining activities vary greatly between different mines. Generally the major impacts include the water related issues and wastes. Energy consumption is also a significant environmental aspect. Water related issues include water consumption and impacts in water quality. There are several methods to assess environmental impacts, for example life cycle assessment, eco-efficiency tools, footprint calculations and process simulation. In addition the corresponding financial value may be estimated utilizing monetary assessment methods. Some of the industrial companies considered in the analysis of industry best practices use environmental and sustainability assessments. Based on the theoretical research and conducted interviews, an Excel based tool utilizing reference data on previous customer cases and customer specific test results was considered to be most suitable to assess the environmental value of Kemira’s solutions. The tool can be used to demonstrate the functionality of Kemira’s solutions in customers’ processes, their impacts in other process parameters and their environmental and financial aspects. In the future, the tool may be applied to fit also Kemira’s other segments, not only mining industry.
Resumo:
During a possible loss of coolant accident in BWRs, a large amount of steam will be released from the reactor pressure vessel to the suppression pool. Steam will be condensed into the suppression pool causing dynamic and structural loads to the pool. The formation and break up of bubbles can be measured by visual observation using a suitable pattern recognition algorithm. The aim of this study was to improve the preliminary pattern recognition algorithm, developed by Vesa Tanskanen in his doctoral dissertation, by using MATLAB. Video material from the PPOOLEX test facility, recorded during thermal stratification and mixing experiments, was used as a reference in the development of the algorithm. The developed algorithm consists of two parts: the pattern recognition of the bubbles and the analysis of recognized bubble images. The bubble recognition works well, but some errors will appear due to the complex structure of the pool. The results of the image analysis were reasonable. The volume and the surface area of the bubbles were not evaluated. Chugging frequencies calculated by using FFT fitted well into the results of oscillation frequencies measured in the experiments. The pattern recognition algorithm works in the conditions it is designed for. If the measurement configuration will be changed, some modifications have to be done. Numerous improvements are proposed for the future 3D equipment.
Resumo:
The aim of this master’s thesis is to analyze the mining industry customers' current and future needs for the water treatment services and discover new business development opportunities in the context of mine water treatment. In addition, the study focuses on specifying service offerings needed and evaluate suitable revenue generation models for them. The main research question of the study is: What kind of service needs related to water treatment can be identified in the Finnish mining industry? The literature examined in the study focused on industrial service classification and new service development process as well as the revenue generation of services. A qualitative research approach employing a case study method was chosen for the study. The present study uses customer and expert interviews as primary data source, complemented by archival data. The primary data was gathered by organizing total of 13 interviews, and the interviews were analyzed by using qualitative content analysis. The abductive-logic was chosen as the way of conducting scientific reasoning in this study. As a result, new service proposals were developed for Finnish mine industry suppliers. The main areas of development were on asset efficiency services and process support services. The service needs were strongly associated with suppliers’ know-how of water treatment process optimization, cost-effectiveness as well as on alternative technologies. The study provides an insight for managers that wish to pursue a water treatment services as a part of their business offering.
Model-View-Controller architectural pattern and its evolution in graphical user interface frameworks
Resumo:
Model-View-Controller (MVC) is an architectural pattern used in software development for graphical user interfaces. It was one of the first proposed solutions in the late 1970s to the Smart UI anti-pattern, which refers to the act of writing all domain logic into a user interface. The original MVC pattern has since evolved in multiple directions, with various names and may confuse many. The goal of this thesis is to present the origin of the MVC pattern and how it has changed over time. Software architecture in general and the MVC’s evolution within web applications are not the primary focus. Fundamen- tal designs are abstracted, and then used to examine the more recent versions. Prob- lems with the subject and its terminology are also presented.
Resumo:
Choice of industrial development options and the relevant allocation of the research funds become more and more difficult because of the increasing R&D costs and pressure for shorter development period. Forecast of the research progress is based on the analysis of the publications activity in the field of interest as well as on the dynamics of its change. Moreover, allocation of funds is hindered by exponential growth in the number of publications and patents. Thematic clusters become more and more difficult to identify, and their evolution hard to follow. The existing approaches of research field structuring and identification of its development are very limited. They do not identify the thematic clusters with adequate precision while the identified trends are often ambiguous. Therefore, there is a clear need to develop methods and tools, which are able to identify developing fields of research. The main objective of this Thesis is to develop tools and methods helping in the identification of the promising research topics in the field of separation processes. Two structuring methods as well as three approaches for identification of the development trends have been proposed. The proposed methods have been applied to the analysis of the research on distillation and filtration. The results show that the developed methods are universal and could be used to study of the various fields of research. The identified thematic clusters and the forecasted trends of their development have been confirmed in almost all tested cases. It proves the universality of the proposed methods. The results allow for identification of the fast-growing scientific fields as well as the topics characterized by stagnant or diminishing research activity.
Resumo:
The global concern about sustainability has been growing and the mining industry is questioned about its environmental and social performance. Corporate social responsibility (CSR) is an important issue for the extractive industries. The main objective of this study was to investigate the relationship between CSR performance and financial performance of selected mining companies. The study was conducted by identifying and comparing a selection of available CSR performance indicators with financial performance indicators. Based on the result of the study, the relationship between CSR performance and financial performance is unclear for the selected group of companies. The result is mixed and no industry specific realistic way to measure CSR performance uniformly is available. The result as a whole is contradictory and varies at company level as well as based on the selected indicators. The result of this study confirms that the relationship between CSR performance and financial performance is complicated and difficult to determine. As an outcome, evaluation of benefits of CSR in the mining sector could better be analyzed based on different attributes.
Resumo:
With the increasing concern of the sustainable approach of gold mining, thiosulphate has been researched as an alternative lixiviant to cyanide since cyanide is toxic to the environment. In order to investigate the possibility of thiosulphate leaching application in the coming future, life cycle assessment, is conducted to compare the environmental footprint of cyanidation and thiosulphate leaching. The result showed the most significant environmental impact of cyanidation is toxicity to human, while the ammonia of thiosulphate leaching is also a major concern of acidification. In addition, an ecosystem evaluation is also performed to indicate the potential damages caused by an example of cyanide spill at Kittilä mine, resulting in significant environmental risk cost that has to be taken into account for decision making. From the opinion collected from an online LinkedIn discussion forum, the anxiety of sustainability alone would not be enough to contribute a significant change of conventional cyanidation, until the tighten policy of cyanide use. International Cyanide Code, therefore, is crucial for safe gold production. Nevertheless, it is still thoughtful to consider the values of healthy ecosystem and the gold for long-term benefit.
Resumo:
The objective of this research is to observe the state of customer value management in Outotec Oyj, determine the key development areas and develop a phase model with which to guide the development of a customer value based sales tool. The study was conducted with a constructive research approach with the focus of identifying a problem and developing a solution for the problem. As a basis for the study, the current literature involving customer value assessment and solution and customer value selling was studied. The data was collected by conducting 16 interviews in two rounds within the company and it was analyzed by coding openly. First, seven important development areas were identified, out of which the most critical were “Customer value mindset inside the company” and “Coordination of customer value management activities”. Utilizing these seven areas three functionality requirements, “Preparation”, “Outotec’s value creation and communication” and “Documentation” and three development requirements for a customer value sales tool were identified. The study concluded with the formulation of a phase model for building a customer value based sales tool. The model included five steps that were defined as 1) Enable customer value utilization, 2) Connect with the customer, 3) Create customer value, 4) Define tool to facilitate value selling and 5) Develop sales tool. Further practical activities were also recommended as a guide for executing the phase model.
Resumo:
The aim of this thesis is to search how to match the demand and supply effectively in industrial and project-oriented business environment. The demand-supply balancing process is searched through three different phases: the demand planning and forecasting, synchronization of demand and supply and measurement of the results. The thesis contains a single case study that has been implemented in a company called Outotec. In the case study the demand is planned and forecasted with qualitative (judgmental) forecasting method. The quantitative forecasting methods are searched further to support the demand forecast and long term planning. The sales and operations planning process is used in the synchronization of the demand and supply. The demand forecast is applied in the management of a supply chain of critical unit of elemental analyzer. Different meters on operational and strategic level are proposed for the measurement of performance.
Resumo:
This master’s thesis investigates the significant macroeconomic and firm level determinants of CAPEX in Russian oil and mining sectors. It also studies the Russian oil and mining sectors, its development, characteristics and current situation. The panel data methodology was implemented to identify the determinants of CAPEX in Russian oil and mining sectors and to test derived hypotheses. The core sample consists of annual financial data of 45 publicly listed Russian oil and mining sector companies. The timeframe of the thesis research is a six year period from 2007 to 2013. The findings of the master’s thesis have shown that Gross Sales, Return On Assets, Free Cash Flow and Long Term Debt are firm level performance variables along with Russian GDP, Export, Urals and the Reserve Fund are macroeconomic variables that determine the magnitude of new capital expenditures reported by publicly listed Russian oil and mining sector companies. These results are not controversial to the previous research paper, indeed they confirm them. Furthermore, the findings from the emerging countries, such as Malaysia, India and Portugal, are analogous to Russia. The empirical research is edifying and novel. Findings from this master’s thesis are highly valuable for the scientific community, especially, for researchers who investigate the determinant of CAPEX in developing countries. Moreover, the results can be utilized as a cogent argument, when companies and investors are doing strategic decisions, considering the Russian oil and mining sectors.
Resumo:
This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.