A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes

A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained. (C) 2012 Elsevier B.V. All rights reserved.

An analysis of Taguchi's on-line quality monitoring procedure for variables based on the results of a sequence of inspections

In this paper, a procedure for the on-line process control of variables is proposed. This procedure consists of inspecting the m-th item from every m produced items and deciding, at each inspection, whether the process is out-of-control. Two sets of limits, warning (µ0 ± W) and control (µ0 ± C), are used. If the value of the monitored statistic falls beyond the control limits or if a sequence of h observations falls between the warning limits and the control limits, the production is stopped for adjustment; otherwise, production goes on. The properties of an ergodic Markov chain are used to obtain an expression for the average cost per item. The parameters (the sampling interval m, the widths of the warning, the control limits W and C(W < C), and the sequence length (h) are optimized by minimizing the cost function. A numerical example illustrates the proposed procedure.

Finite element simulation of a local scale air quality model over complex terrain

[EN]In this paper we propose a finite element method approach for modelling the air quality in a local scale over complex terrain. The area of interest is up to tens of kilometres and it includes pollutant sources. The proposed methodology involves the generation of an adaptive tetrahedral mesh, the computation of an ambient wind field, the inclusion of the plume rise effect in the wind field, and the simulation of transport and reaction of pollutants. We apply our methodology to simulate a fictitious pollution episode in La Palma island (Canary Island, Spain)...

Calibration and validation of an air quality finite element model around an electric power plant in Gran Canaria island

[EN]This work presents the calibration and validation of an air quality finite element model applied to the surroundings of Jinamar electric power plant in Gran Canaria island (Spain). The model involves the generation of an adaptive tetrahedral mesh, the computation of an ambient wind field, the inclusion of the plume rise effect in the wind field, and the simulation of transport and reaction of pollutants. The main advantage of the model is the treatment of complex terrains that introduces an alternative to the standard implementation of current models. In addition, it improves the computational cost through the use of unstructured meshes...

Local scale air quality model with several pollutant sources

[EN]This paper shows a finite element method for pollutant transport with several pollutant sources. An Eulerian convection–diffusion–reaction model to simulate the pollutant dispersion is used. The discretization of the different sources allows to impose the emissions as boundary conditions. The Eulerian description can deal with the coupling of several plumes. An adaptive stabilized finite element formulation, specifically Least-Squares, with a Crank-Nicolson temporal integration is proposed to solve the problem. An splitting scheme has been used to treat separately the transport and the reaction. A mass-consistent model has been used to compute the wind field of the problem…

Future water quality monitoring--adapting tools to deal with mixtures of pollutants in water resource management.

Environmental quality monitoring of water resources is challenged with providing the basis for safeguarding the environment against adverse biological effects of anthropogenic chemical contamination from diffuse and point sources. While current regulatory efforts focus on monitoring and assessing a few legacy chemicals, many more anthropogenic chemicals can be detected simultaneously in our aquatic resources. However, exposure to chemical mixtures does not necessarily translate into adverse biological effects nor clearly shows whether mitigation measures are needed. Thus, the question which mixtures are present and which have associated combined effects becomes central for defining adequate monitoring and assessment strategies. Here we describe the vision of the international, EU-funded project SOLUTIONS, where three routes are explored to link the occurrence of chemical mixtures at specific sites to the assessment of adverse biological combination effects. First of all, multi-residue target and non-target screening techniques covering a broader range of anticipated chemicals co-occurring in the environment are being developed. By improving sensitivity and detection limits for known bioactive compounds of concern, new analytical chemistry data for multiple components can be obtained and used to characterise priority mixtures. This information on chemical occurrence will be used to predict mixture toxicity and to derive combined effect estimates suitable for advancing environmental quality standards. Secondly, bioanalytical tools will be explored to provide aggregate bioactivity measures integrating all components that produce common (adverse) outcomes even for mixtures of varying compositions. The ambition is to provide comprehensive arrays of effect-based tools and trait-based field observations that link multiple chemical exposures to various environmental protection goals more directly and to provide improved in situ observations for impact assessment of mixtures. Thirdly, effect-directed analysis (EDA) will be applied to identify major drivers of mixture toxicity. Refinements of EDA include the use of statistical approaches with monitoring information for guidance of experimental EDA studies. These three approaches will be explored using case studies at the Danube and Rhine river basins as well as rivers of the Iberian Peninsula. The synthesis of findings will be organised to provide guidance for future solution-oriented environmental monitoring and explore more systematic ways to assess mixture exposures and combination effects in future water quality monitoring.

Airliner cabin air quality exposure assessment

The airliner cabin environment and its effects on occupant health have not been fully characterized. This dissertation is: (1) A review of airliner environmental control systems (ECSs) that modulate the ventilation, temperature, relative humidity (RH), and barometric pressure (PB) of the cabin environment---variables related to occupant comfort and health. (2) A review and assessment of the methods and findings of key cabin air quality (CAQ) investigations. Several significant deficiencies impede the drawing of inferences about CAQ, e.g., lack of detail about investigative methods, differences in methods between investigations, limited assessment of CAQ variables, small sample sizes, and technological deficiencies of data collection. (3) A comprehensive evaluation of the methods used in the subsequent NIOSH-FAA Airliner CAQ Exposure Assessment Feasibility Study (STUDY) in which this author participated. A number of problems were identified which limit the usefulness of the data. (4) An analysis of the reliable 10-flight STUDY data. Univariate and multivariate methods applied to CO2 (a surrogate for air contaminants), temperature, RH, and PB, in association with percent passenger load, ventilation system, flight duration, airliner body type, and measurement location within the cabin, revealed neither the measured values nor their variability exceeded established health-based exposure limits. Regression analyses suggest CO2, temperature, and RH were affected by percent passenger load. In-flight measurements of CO2 and RH were relatively independent of ventilation system type or flight duration. Cabin temperature was associated with percent passenger load, ventilation system type, and flight duration. (5) A synthesis of the implications of the airliner ECS and cabin O2 environment on occupant health. A model was developed to predict consequences of the airliner cabin pressure altitude 8,000 ft limit and resulting model-estimated PO2 on cardiopulmonary status. Based on the PB, altitude, and environmental data derived from the 10 STUDY flights, the predicted PaO2 of adults with COPD, or elderly adults with or without COPD, breathing ambient cabin air could be < 55 mm Hg (SaO2 < 88%). Reduction in cabin PB found in the STUDY flights could aggravate various medical conditions and require the use of in-flight supplemental O2. ^

Revising the National Ambient Air Quality Standards: The integration of science and policy

Under the Clean Air Act, Congress granted discretionary decision making authority to the Administrator of the Environmental Protection Agency (EPA). This discretionary authority involves setting standards to protect the public's health with an "adequate margin of safety" based on current scientific knowledge. The Administrator of the EPA is usually not a scientist, and for the National Ambient Air Quality Standard (NAAQS) for particulate matter (PM), the Administrator faced the task of revising a standard when several scientific factors were ambiguous. These factors included: (1) no identifiable threshold below which health effects are not manifested, (2) no biological basis to explain the reported associations between particulate matter and adverse health effects, and (3) no consensus among the members of the Clean Air Scientific Advisory Committee (CASAC) as to what an appropriate PM indicator, averaging period, or value would be for the revised standard. ^ This project recommends and demonstrates a tool, integrated assessment (IA), to aid the Administrator in making a public health policy decision in the face of ambiguous scientific factors. IA is an interdisciplinary approach to decision making that has been used to deal with complex issues involving many uncertainties, particularly climate change analyses. Two IA approaches are presented; a rough set analysis by which the expertise of CASAC members can be better utilized, and a flag model for incorporating the views of stakeholders into the standard setting process. ^ The rough set analysis can describe minimal and maximal conditions about the current science pertaining to PM and health effects. Similarly, a flag model can evaluate agreement or lack of agreement by various stakeholder groups to the proposed standard in the PM review process. ^ The use of these IA tools will enable the Administrator to (1) complete the NAAQS review in a manner that is in closer compliance with the Clean Air Act, (2) expand the input from CASAC, (3) take into consideration the views of the stakeholders, and (4) retain discretionary decision making authority. ^

A feasibility study for assessing building occupants' indoor air quality expectations compared to nationally recognized standards

Indoor Air Quality (IAQ) can have significant implications for health, productivity, job performance, and operating cost. Professional experience in the field of indoor air quality suggests that high expectations (better than nationally established standards) (American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE)) of workplace indoor air quality lead to increase air quality complaints. To determine whether there is a positive association between expectations and indoor air quality complaints, a one-time descriptive and analytical cross-sectional pilot study was conducted. Area Safety Liaisons (n = 330) at University of Texas Health Science Center – Houston were asked to answer a questionnaire regarding their expectations of four workplace indoor air quality indicators i.e., (temperature, relative humidity, carbon dioxide, and carbon monoxide) and if they experienced and reported indoor air quality problems. A chi-square test for independence was used to evaluate associations among the variables of interest. The response rate was 54% (n = 177). Results did not show significant associations between expectation and indoor air quality. However, a greater proportion of Area Safety Liaisons who expected indoor air quality indicators to be better than the established standard experienced greater indoor air quality problems. Similarly, a slightly higher proportion of Area Liaisons who expected indoor air quality indicators to be better than the standard reported greater indoor air quality complaints. ^ The findings indicated that a greater proportion of Area Safety Liaisons with high expectations (conditions that are beyond what is considered normal and acceptable by ASHRAE) experienced greater indoor air quality discomfort. This result suggests a positive association between high expectations and experienced and reported indoor air quality complaints. Future studies may be able to address whether the frequency of complaints and resulting investigations can be reduced through information and education about what are acceptable conditions.^