Artigos - Produção - FEG
http://hdl.handle.net/11449/9491
2019-06-17T22:46:49ZThe Shewhart attribute chart with alternated charting statistics to monitor bivariate and trivariate mean vectors
http://hdl.handle.net/11449/179932
The Shewhart attribute chart with alternated charting statistics to monitor bivariate and trivariate mean vectors
Leoni, Roberto Campos; Costa, Antonio Fernando Branco [UNESP]
In this article, we combined the Alternated Charting Statistic (ACS) scheme with the traditional attribute np chart to control mean vectors of bivariate and trivariate normal processes. With the bivariate ACS scheme in use (the trivariate scheme is similar), the two quality characteristics (X, Y) are controlled in an alternating fashion. If the current sample point is the number of disapproved items with respect to the X discriminating limits, then the next sample point will be the number of disapproved items with respect to the Y discriminating limits. The strategy of using the X discriminating limits to classify the items of one sample and the Y discriminating limits to classify the items of the next sample instead of using jointly the X and Y discriminating limits to classify the items of all samples might be compensated with the adoption of larger samples. In other words, the proposed bivariate (trivariate) ACS chart might work with samples as large as 2n (3n); n is the sample size of the competing Hotelling and Max D charts. The proposed chart resembles an np chart with alternated charting statistic; because of that, it is called the ACS mp chart. The ACS mp chart always outperforms the Max D chart and, in comparison with the standard T2 chart and with the combined Max D − T2 chart, it has a better overall performance. With the ACS scheme, the items are classified as approved or disapproved regarding only one of the two quality characteristic, X or Y; with the Max D chart the complexity increases, once the items are classified into four different categories: approved (disapproved) regarding both, the X and Y discriminating limits, or approved (disapproved) regarding the X discriminate limits and disapproved (approved) regarding the Y discriminate limits. The T2 chart always requires the measurement of the two quality characteristics. The additional advantage of inspecting only one quality characteristic of the sample items lies in the fact that the XY-correlation doesn't need to be estimated.
2018-08-01T00:00:00ZUse of Factorial Designs and the Response Surface Methodology to Optimize a Heat Staking Process
http://hdl.handle.net/11449/179843
Use of Factorial Designs and the Response Surface Methodology to Optimize a Heat Staking Process
Faria Neto, Antonio [UNESP]; Costa, Antonio Fernando Branco [UNESP]; de Lima, Michel Floriano
The demand from the automotive industry for lighter and more resistant structures produced at lower costs has shifted the development focus of production processes toward hybrid components. A problem that arises from hybrid components is the necessity to join dissimilar materials, e.g., polymers and metals. A method to achieve this joining involves a process known as heat staking, in which a metal insert is heated and pushed against a thermoplastic surface. At the end of this process, the metal component may not be level with the thermoplastic surface; rather, it may be over flushed, and this discrepancy is known as the Insertion Height. This paper aims to apply the design of experiments and the response surface methodology to develop a model for the Insertion Height, considering the Heating Temperature and the Insertion Time as independent variables. The experiments revealed that the Insertion Height is most affected by the Heating Temperature. There are several combinations of the factors that can keep the Insertion Height within the specifications; therefore, it is possible to increase productivity by decreasing the Insertion Time and to save energy by reducing the Heating Temperature while considering the process constraints and specifications.
2018-06-01T00:00:00ZFuzzy Goal Programming applied to the process of capital budget in an economic environment under uncertainty
http://hdl.handle.net/11449/179776
Fuzzy Goal Programming applied to the process of capital budget in an economic environment under uncertainty
Da Silva, Aneirson Francisco [UNESP]; Marins, Fernando Augusto Silva [UNESP]; Dias, Erica Ximenes [UNESP]; De Carvalho Miranda, Rafael
The Goal Programming (GP) is a multi-criteria approach of Operational Research that has been used for solving complex decision problems. This paper proposes a new Fuzzy Goal Programming (FGP) model to handle the process of capital budget of companies in an economic environment under uncertainty. For performance comparison purposes, the FGP and another recently published model developed for the same purposes were applied to data from a company that was the object of the study. The modeling and optimization were made with the GAMS software - 23.6.5 and using the CPLEX solver. The results obtained from the FGP model provided higher improvements than those obtained with the alternative model, as for example: increased profitability index, reduced payback and better application of the capital available in the budget. Furthermore, the FGP model has flexibility features that allow the manager to simulate, quickly and easily obtaining results about scenarios under uncertainty.
2018-01-01T00:00:00ZEnergy efficiency in buildings: analysis of scientific literature and identification of data analysis techniques from a bibliometric study
http://hdl.handle.net/11449/179437
Energy efficiency in buildings: analysis of scientific literature and identification of data analysis techniques from a bibliometric study
Cristino, Talita Mariane [UNESP]; Faria Neto, Antonio [UNESP]; Costa, Antonio Fernando Branco [UNESP]
This study uses bibliometrics methods to analyze the specialized literature of energy efficiency in buildings, including the Scopus database during the period of time ranging from 1980 to 2016, to identify the most relevant publications, authors, researcher groups, the evolution of the theme over the years, journals, geographical areas and eventually data analysis techniques employed. The countries with the most contributions have been the USA, China and the UK, where the Lawrence Berkeley National Labor, Hong Kong Polytechnic University and City University of Hong Kong were the three institutions with the most publications in this area. The publications have been concentrated primarily in thirty-three journals. The three most important journals are Energy and Buildings, Applied Energy, and Energy and are categorized primarily in engineering, energy and environmental sciences. The key terms may be divided into seven clusters: Buildings and Energy Uses; Building Energy Conservation; Energy Consumption; Energy Consumption Forecasting and Computational Intelligence; Energy Efficiency and Climate Effects; Building Energy Efficiency and Multivariate Statistics; and Building Energy Analysis and Stochastic Processes. The Data Analysis Techniques contained seven groups: Regression Analysis, Descriptive Statistics, Multivariate Analysis, Computational Intelligence, Stochastic Processes, Inferential Statistics and Design of Experiments. The data analysis techniques identified in this article raise the possibility of reformulation and adequacy of the curricula of the undergraduate and graduate courses in the area of energy and smart buildings. The results of this research have shown a general perspective regarding the energy efficiency in buildings, which can be useful in showing relevant themes for further research.
2018-03-01T00:00:00Z