Na colheita mecanizada de cana-de-açúcar, existem algumas peculiaridades relacionadas às interações solo-máquina-planta, que tem causado preocupações, devido às perdas de matériaprima deixada no campo e à redução da longevidade do canavial, ocasionados pela deficiência do controle de altura de corte. A melhoria da qualidade do corte e da matéria-prima é proposta na bibliografia por meio de intervenções na colheita e em outras práticas culturais existentes, e de mudanças nos projetos das colhedoras. Os fabricantes desses equipamentos têm desenvolvido dispositivos para auxiliar o operador no controle da altura de corte. Tendo em vista a importância do corte de base na qualidade e perda de matéria-prima e na longevidade da soqueira, o objetivo desse trabalho foi avaliar a influência de um dispositivo semi-automático de controle de altura do corte de base, DAC, na qualidade do corte de base e seu desempenho ao longo de uma jornada de trabalho. Para tanto, os ensaios foram realizados em duas usinas de açúcar e álcool, com colhedoras equipadas com o DAC. Para a avaliação da qualidade do corte de base, foram utilizadas duas metodologias distintas, denominadas de etapa 1 e etapa 2. A primeira procurou identificar a influência da utilização do DAC na qualidade operacional. A segunda foi voltada para a avaliação da qualidade operacional com o uso DAC em situação normal de trabalho. Nas duas etapas, utilizaram-se técnicas do controle estatístico do processo. Os resultados mostraram que, em termos gerais e nas condições do trabalho, os parâmetros qualitativos analisados do corte de base realizado por colhedoras de cana-de-açúcar não atendem aos padrões especificados pelas usinas, independente do uso do DAC. / In sugar cane mechanized harvesting, there are some peculiarities related to soil-machineplant interaction which has been causing some concern due to raw material left on the field losses and the reduction in sugar cane crop longevity caused by deficiency in cut height control. Improvement in cut quality and raw material are proposed in bibliography by means of intervention at harvest and other crop practices available and changes in harvester design. Harvester producers have developed devices to aid the operator in controlling cut height. Whit the importance of base cutting in raw material quality and losses and crop longevity in mind, this study aimed at evaluating the influence of a semi-automatic base cutting control device, DAC, on base cutting quality and its performance on a normal working day. Thus, the trials were carried out in two sugar and alcohol mills with harvesters equipped with DAC. Two different methodologies, denominated stage one and stage two, were used in order to evaluate base cutting quality. The first one tried to identify the influence of DAC utilization on operational quality. The second one evaluated the operational quality with DAC use on a normal working condition. On both stages, techniques of statistical process control were used. The results showed that, in general and under the harvester operation conditions, the analyzed qualitative parameters of base cutting done sugar cane harvesters do not meet the standard specified by sugar mills regardless the DAC use.

A operação de adubação responde por parte significativa dos custos de produção agrícola. Melhorar a qualidade dessa operação acarreta benefícios econômicos e ambientais. O processo de adubação normalmente é realizado a uma taxa média, representativa de uma área, no entanto, propriedades químicas do solo podem variar consideravelmente dentro dessa área. Desse modo, alguns locais poderão receber fertilizantes e/ou corretivos em excesso, enquanto outros poderão receber quantidades insuficientes. A alternativa à taxa média é a realizar a aplicação à taxa variada, que se caracteriza por aplicar os insumos de acordo com as necessidades específicas dentro da área. Para que essa aplicação aconteça, mecanismos dosadores controlam a aplicação. O objetivo deste estudo é avaliar os mecanismos dosadores de uma carreta adubadora de arrasto, comportas e esteiras, atendem as prescrições de doses previstas no mapa de recomendação de adubação. Para avaliar a uniformidade da operação utilizou-se o controle estatístico do processo. De acordo com os resultados obtidos pode-se afirmar que os mecanismos dosadores não atenderam a condição de realizar a aplicação à taxa variável de maneira uniforme. / The operation fertilization accounts for a significant portion of the costs of agricultural production. Improve the quality of this operation entails economic and environmental benefits. The process of fertilization is usually performed at an average rate representative of an area, however, the chemical properties of soil can vary considerably within the area. Thus, some locations may receive fertilizer and / or lime in excess, while others may receive insufficient amounts. The alternative is to average the application to perform variable rate, characterized by applying inputs according to the specific requirements within the area. For this application happens, metering mechanisms control the application. The aim of this study is to evaluate the dosing mechanisms of a truck hauling fertilizer, locks and mats, meet the requirements of the prescribed dose map fertilizer recommendation. To evaluate the uniformity of operation used the statistical process control. According to the obtained results it can be stated that the meter mechanism did not meet the condition to perform variable rate application to uniformly.

Queuing systems are important parts of our daily lives and to keep their operations at an efficient level they need to be monitored by using queuing Performance Metrics, such as average queue lengths and average waiting times. On the other hand queue lengths and waiting times are generally random variables and their distributions depend on different properties like arrival rates, service times, number of servers. We focused on detecting the change in service rates in this report. Therefore, we monitored queues by using Cumulative Sum(CUSUM) charts based on likelihood ratios and compared the Average Run Length values of different service rates.

The exchange rate market has traditionally played a key role in the financial market. The variation of the exchange rate which is called volatility is also an important feature for studying the exchange rate market because the increased volatility may have a negative effect on a nation's economy by increasing the uncertainty in the exchange market. In this paper the volatility of the exchange rate is considered by means of a Heterogeneous Autoregression Conditional Heteroskedastictity (HARCH) Model. It explains the volatility of the exchange rate market well. In addition, it is assumed that at a random time point a change of a parameter in the distribution of the random process underobservation may occur. Some methods such as the Shewhart method, the Culumative Sum Method (CUSUM) and the ExponentiallyWeighted Moving Average Method (EWMA) are investigated within the frames of this change-point problem. In order to evaluate them, Average Run Length (ARL) and Conditional Expected Delay (CED) will be used asperformance measures.

Nowadays, facing the severe pressure of globalization and strong demand of high products quality from customers, enterprises in Taiwan are forced to enhance the quality and yield rate of manufactured products in order to gain their competitive edges. An enterprise usually relies on the statistical process control (SPC) software system to achieve this goal. The SPC approach measures, understands, and controls the variation of the products manufacturing process. This study uses the structure-behavior coalescence architecture description language (SBC-ADL) to construct the architecture-oriented statistical process control model (AOSPCM). A model constructed by the SBC-ADL differs from others software model in its using six golden rules which help integrate the structure and behavior of a software system. AOSPCM constructed in this study improved substantially both training and communication endeavors within an enterprise, reduced costs due to estimation errors, requirement uncertainties, and project delays. Overall, AOSPCM benefits a great deal to both developers and users of a software project. In general, most manufacturing and high-tech industries rely heavily on the SPC software system. Therefore, AOSPCM constructed in this study provides a standard model for other software developers to follow. Following the AOSPCM, any SPC software developer shall improve lots of development efforts and cost savings within an enterprise.

Statistical process control (SPC) which includes very powerful techniques used in other mature engineering disciplines for providing process control is not used by many software organizations. In software engineering domain, SPC is currently utilized only by organizations which have high maturity levels according to the process improvement models like CMM, ISO/IEC 15504 and CMMI. Guidelines and software tools to implement SPC techniques should be developed for effective use and dissemination of SPC especially for low maturity organizations. In this thesis, a software tool (SPC-AAT) which we developed to assess the suitability of software processes and metrics for SPC and use of SPC tools is presented. With SPC-AAT, we aim to ease and enhance application of SPC especially for emergent and low maturity organizations. Control charts, histograms, bar charts and pareto charts are the supported SPC tools for this purpose. We also explained the validation of the tool over two processes of a software organization in three case studies.

Bayesian process control is a statistical process control (SPC) scheme that uses the posterior state probabilities as the control statistic. The key issue is to decide when to restore the process based on real-time observations. Such problems have been extensively studied in the framework of partially observable Markov decision processes (POMDP), with particular emphasis on the structure of optimal control policy. Almost all existing structural results on the optimal policies are limited to the two-state processes, where the class of control-limit policy is optimal. However, the two-state model is a gross simplification, as real production processes almost always involve multiple states. For example, a machine in the production system often has multiple failure modes differing in their effects; the deterioration process can often be divided into multiple stages with different degradation levels; the condition of a complex multi-unit system also requires a multi-state representation. We investigate the optimal control policies for multi-state processes with fixed sampling scheme, in which information about the process is represented by a belief vector within a high dimensional probability simplex. It is well known that obtaining structural results for such high-dimensional POMDP is challenging. Firstly, we prove that for an infinite-horizon process subject to multiple competing assignable causes, a so-called conditional control limit policy is optimal. The optimal policy divides the belief space into two individually connected regions, which have analytical bounds. Next, we address a finite-horizon process with at least one absorbing state and show that a structured optimal policy can be established by transforming the belief space into a polar coordinate system, where a so-called polar control limit policy is optimal. Our model is general enough to include many existing models in the literature as special cases. The structural results also lead to significantly efficient algorithms for computing the optimal policies. In addition, we characterize the condition for some out-of-control state to be more desirable than the in-control state. The existence of such counterintuitive situation indicates that multi-state process control is drastically different from the two-state case.

Bayesian process control is a statistical process control (SPC) scheme that uses the posterior state probabilities as the control statistic. The key issue is to decide when to restore the process based on real-time observations. Such problems have been extensively studied in the framework of partially observable Markov decision processes (POMDP), with particular emphasis on the structure of optimal control policy. Almost all existing structural results on the optimal policies are limited to the two-state processes, where the class of control-limit policy is optimal. However, the two-state model is a gross simplification, as real production processes almost always involve multiple states. For example, a machine in the production system often has multiple failure modes differing in their effects; the deterioration process can often be divided into multiple stages with different degradation levels; the condition of a complex multi-unit system also requires a multi-state representation. We investigate the optimal control policies for multi-state processes with fixed sampling scheme, in which information about the process is represented by a belief vector within a high dimensional probability simplex. It is well known that obtaining structural results for such high-dimensional POMDP is challenging. Firstly, we prove that for an infinite-horizon process subject to multiple competing assignable causes, a so-called conditional control limit policy is optimal. The optimal policy divides the belief space into two individually connected regions, which have analytical bounds. Next, we address a finite-horizon process with at least one absorbing state and show that a structured optimal policy can be established by transforming the belief space into a polar coordinate system, where a so-called polar control limit policy is optimal. Our model is general enough to include many existing models in the literature as special cases. The structural results also lead to significantly efficient algorithms for computing the optimal policies. In addition, we characterize the condition for some out-of-control state to be more desirable than the in-control state. The existence of such counterintuitive situation indicates that multi-state process control is drastically different from the two-state case.

Small and Medium Sized Enterprises (SMEs) were founded to improve the activity and effectiveness of small industries, to provide economic and social needs of the country, to increase the competitive level of the country, and to establish integration in the industry. In today&rsquo / s competition conditions, SMEs should continuously improve themselves / otherwise, they could lose their market shares. One of the major problems encountered in Turkish SMEs is poor quality activities / especially, not being able to exploit the Statistical Process Control (SPC) techniques. Production runs become shorter and shorter, and the product variety seems to be ever increasing, which cause short production runs. Using traditional control charts for short production runs can yield wrong and costly results. Instead of traditional control charts, short run charts such as Difference Charts (DNOM), Zed Charts, and Zed-Star Charts should be preferred.For this purpose, software that not only constructs short run control charts but also implements charts by tests to solve the problems of SMEs is developed. A Control Chart Selection Wizard, which is capable of emulating human expertise in finding a suitable control chart according to the user response for different cases is developed and added as a subprogram. Software was tested at Ar&ccedil / elik Dishwasher Plant in Ankara. The overall evaluation of the developed software, as regards the user, was satisfactory. The software can meet some requirements of the SMEs.

Routine pipette calibration is an essential part of any quality assurance and quality control program in the forensic sciences and beyond. Pipette calibration standards in a forensic laboratory are typically set to the limits outlined by the document ISO8655, published by the International Organization for Standardization for the general scientific community. Alternative methods exist that may be capable of monitoring pipette stability across time in a forensic setting. Statistical process control charts, or Shewhart charts, are one such form of process control, which is being investigated for its potential application to pipette calibration monitoring for forensic DNA laboratories. Indeed, the application of process control lines for monitoring the calibration of volumetric equipment is not without precedent.1 To investigate the applicability of process control charts for monitoring pipette stability, a series of X ̅ and S charts, a type of Shewhart chart, have been produced from eight years of collected calibration data. A total of 71 pipettes of the following sizes were examined: 1-10 µL, 1-10 µL multi-channel, 10-100 µL, 100-1000 µL, 1-3 µL, 30-300 µL, 5-50 µL, 5-50 µL multi-channel, and 500-5000 µL pipettes. The ISO8655 calibration recommended volume limits of these pipettes have been added to the charts for the purposes of comparison. With these charts, it is possible to assess pipette performance over time in comparison to the ISO8655 calibration standards and to the control limits imposed by the Shewhart charts. The completed charts suggest that the methodology proposed by Shewhart shows promise as a supplement to ISO8655 recommendations for monitoring pipette stability across time. To corroborate the value of using Shewhart charts to monitor pipette performance, a serial dilution study in conjunction with a series of simulations with dynamic modeling software was performed. This dilution study investigated whether the systematic biases shown by the Shewhart charts could be measured in a laboratory setting. The simulations investigated multiple hypothetical pipetting scenarios concerning various levels of systematic bias. The simulations consistently corroborated the value of Shewhart charts to enforce better compliance between a pipette’s nominal and actual volume delivery, while the serial dilution study offered partial evidence of systematic pipetting bias.