Multivariate Statistical Process Control Charts: An Overview

In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as principal components analysis (PCA) and partial lest squares (PLS). Finally, we describe the most significant methods for the interpretation of an out-of-control signal.quality control, process control, multivariate statistical process control, Hotelling's T-square, CUSUM, EWMA, PCA, PLS

An optimization of on-line monitoring of simple linear and polynomial quality functions

This research aims to introduce a number of contributions for enhancing the statistical performance of some of Phase II linear and polynomial profile monitoring techniques. For linear profiles the idea of variable sampling size (VSS) and variable sampling interval (VSI) have been extended from multivariate control charts to the profile monitoring framework to enhance the power of the traditional T^2 chart in detecting shifts in linear quality models. Finding the optimal settings of the proposed schemes has been formulated as an optimization problem solved by using a Genetic Approach (GA). Here the average time to signal (ATS) and the average run length (ARL) are regarded as the objective functions, and ATS and ARL approximations, based on Markov Chain Principals, are extended and modified to capture the special structure of the profile monitoring. Furthermore,the performances of the proposed control schemes are compared with their fixed sampling counterparts for different shift levels in the parameters. The extensive comparison studies reveal the potentials of the proposed schemes in enhancing the performance of T^2 control chart when a process yields a simple linear profile. For polynomial profiles, where the linear regression model is not sufficient, the relationship between the parameters of the original and orthogonal polynomial quality profiles is considered and utilized to enhance the power of the orthogonal polynomial method (EWMA4). The problem of finding the optimal set of explanatory variable minimizing the average run length is described by a mathematical model and solved using the Genetic Approach. In the case that the shift in the second or the third parameter is the only shift of interest, the simulation results show a significant reduction in the mean of the run length distribution of the EWMA4 technique

Distributed model predictive control of steam/water loop in large scale ships

In modern steam power plants, the ever-increasing complexity requires great reliability and flexibility of the control system. Hence, in this paper, the feasibility of a distributed model predictive control (DiMPC) strategy with an extended prediction self-adaptive control (EPSAC) framework is studied, in which the multiple controllers allow each sub-loop to have its own requirement flexibility. Meanwhile, the model predictive control can guarantee a good performance for the system with constraints. The performance is compared against a decentralized model predictive control (DeMPC) and a centralized model predictive control (CMPC). In order to improve the computing speed, a multiple objective model predictive control (MOMPC) is proposed. For the stability of the control system, the convergence of the DiMPC is discussed. Simulation tests are performed on the five different sub-loops of steam/water loop. The results indicate that the DiMPC may achieve similar performance as CMPC while outperforming the DeMPC method

Risk-Informed Interference Assessment for Shared Spectrum Bands: A Wi-Fi/LTE Coexistence Case Study

Interference evaluation is crucial when deciding whether and how wireless technologies should operate. In this paper we demonstrate the benefit of risk-informed interference assessment to aid spectrum regulators in making decisions, and to readily convey engineering insight. Our contributions are: we apply, for the first time, risk assessment to a problem of inter-technology spectrum sharing, i.e. Wi-Fi/LTE in the 5 GHz unlicensed band, and we demonstrate that this method comprehensively quantifies the interference impact. We perform simulations with our newly publicly-available tool and we consider throughput degradation and fairness metrics to assess the risk for different network densities, numbers of channels, and deployment scenarios. Our results show that no regulatory intervention is needed to ensure harmonious technical Wi-Fi/LTE coexistence: for the typically large number of channels available in the 5 GHz band, the risk for Wi-Fi from LTE is negligible, rendering policy and engineering concerns largely moot. As an engineering insight, Wi-Fi coexists better with itself in dense, but better with LTE, in sparse deployments. Also, both main LTE-in-unlicensed variants coexist well with Wi-Fi in general. For LTE intra-technology inter-operator coexistence, both variants typically coexist well in the 5 GHz band, but for dense deployments, implementing listen-before-talk causes less interference

Novel metaheuristic hybrid spiral-dynamic bacteria-chemotaxis algorithms for global optimisation

© 2014 Elsevier B.V. All rights reserved. This paper presents hybrid spiral-dynamic bacteria-chemotaxis algorithms for global optimisation and their application to control of a flexible manipulator system. Spiral dynamic algorithm (SDA) has faster convergence speed and good exploitation strategy. However, the incorporation of constant radius and angular displacement in its spiral model causes the exploration strategy to be less effective hence resulting in low accurate solution. Bacteria chemotaxis on the other hand, is the most prominent strategy in bacterial foraging algorithm. However, the incorporation of a constant step-size for the bacteria movement affects the algorithm performance. Defining a large step-size results in faster convergence speed but produces low accuracy while de.ning a small step-size gives high accuracy but produces slower convergence speed. The hybrid algorithms proposed in this paper synergise SDA and bacteria chemotaxis and thus introduce more effective exploration strategy leading to higher accuracy, faster convergence speed and low computation time. The proposed algorithms are tested with several benchmark functions and statistically analysed via nonparametric Friedman and Wilcoxon signed rank tests as well as parametric t-test in comparison to their predecessor algorithms. Moreover, they are used to optimise hybrid Proportional-Derivative-like fuzzy-logic controller for position tracking of a flexible manipulator system. The results show that the proposed algorithms significantly improve both convergence speed as well as fitness accuracy and result in better system response in controlling the flexible manipulator

Multimodal optical diagnostics of the microhaemodynamics in upper and lower limbs

The introduction of optical non-invasive diagnostic methods into clinical practice can substantially advance in the detection of early microcirculatory disorders in patients with different diseases. This paper is devoted to the development and application of the optical non-invasive diagnostic approach for the detection and evaluation of the severity of microcirculatory and metabolic disorders in rheumatic diseases and diabetes mellitus. The proposed methods include the joint use of laser Doppler flowmetry, absorption spectroscopy and fluorescence spectroscopy in combination with functional tests. This technique showed the high diagnostic importance for the detection of disturbances in peripheral microhaemodynamics. These methods have been successfully tested as additional diagnostic techniques in the field of rheumatology and endocrinology. The sensitivity and specificity of the proposed diagnostic procedures have been evaluated.<br/

Scaling Success: Lessons from Adaptation Pilots in the Rainfed Regions of India

"Scaling Success" examines how agricultural communities are adapting to the challenges posed by climate change through the lens of India's rainfed agriculture regions. Rainfed agriculture currently occupies 58 percent of India's cultivated land and accounts for up to 40 percent of its total food production. However, these regions face potential production losses of more than $200 billion USD in rice, wheat, and maize by 2050 due to the effects of climate change. Unless action is taken soon at a large scale, farmers will see sharp decreases in revenue and yields.Rainfed regions across the globe have been an important focus for the first generation of adaptation projects, but to date, few have achieved a scale that can be truly transformational. Drawing on lessons learnt from 21 case studies of rainfed agriculture interventions, the report provides guidance on how to design, fund and support adaptation projects that can achieve scale

An Analysis of the Development of Modular Building Design Elements to Improve Thermal Performance of a Representative High Rise Residential Estate in the Coastline City of Famagusta, Cyprus

Passive design strategies can reduce heating and cooling demands with integration of more efficient building systems as well as the potential to integrate modular off-site construction technology and its technical systems to offset overall energy consumption. This study evaluates the energy performance of the nationally representative post-war social housing estate in the southeastern Mediterranean island of Cyprus where the weather is subtropical (Csa) and partly semi-arid (Bsh). This study employed a mixed methods research design approach which was based on a thorough field study that consisted of a questionnaire survey conducted with residents of the social housing estate in the hottest summer month of August, to explore the occupants’ thermal sensation votes (TSVs), their habitual adaptive behaviour, and home energy performance concurrently. On-site environmental monitoring was performed, and in-situ measurements of each occupied space were recorded to identify ‘neutral’ adaptive thermal comfort. The selected representative high-rise residential development was modelled using Integrated Environmental Solutions’ Virtual Environment (IES-VE) software, where extensive dynamic thermal simulations have been produced to assess existing energy performance and energy effectiveness of retrofitting strategies. The results demonstrated that a moderate–strong relationship was found between orientation and reasons for thermal discomfort (χ2 = 49,327, p < 0.001, Cramer’s V = 0.405). Individual levels of thermal comfort were not limited to household socio-demographic characteristics, however; environmental factors were also determinants in the development of adaptive thermal-comfort theory. Furthermore, the occupants’ TSVs indicated that in a southeastern Mediterranean climate, 28.5 °C is considered a neutral temperature, and the upper limit of the indoor-air thermal-comfort range is 31.5 °C