International Journal of Environmentally Conscious Design & Manufacturing 

Volume 12, Number 2, 2004

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Contents
Contents 

A CONTINUOUS NOX EMISSIONS TRACKING, PREDICTION AND MONITORING FRAMEWORK FOR PROCESS IMPROVEMENT, by ROLANDO QUINTANA AND ERNESTO A. OCHOA

    This paper presents statistical framework for assessing and quantifying the inherent uncertainty and variability associated with emissions from electrical power generation and delivery in order to systematically monitor, track, control and predict emission levels that directly affect air quality. The goal of the Continuous Emissions Tracking and Prediction Methodology (CETPM) is to expand federally mandated Continuous Emission Monitoring (CEM) data acquisition capabilities, provide a practical and usable tool to assist environmental decision- and policy-makers in rendering decisions and policies, and assist electric utilities by allowing them to operate in a manner that compares favorably with the individual plant’s mandated allowances. The premise of this research was that complete utilization of current (and future) technology, such as federally mandated CEM systems, can significantly contribute to the goals of EPA in reducing risks to human health and ecosystems while simultaneously contributing to the compliance and profitability of electric utilities. Fossil fuel-burning electric utilities are the primary emitters of NOX, SO2 and other toxic substances as part and parcel of manufacturing and delivering electrical power. Since 1970, the principal air pollutants have decreased except for NOX. A case study utilizing 3 years of data from an electric power provider provided the test bed for the validation of the CETPM. A fossil-fuel fired boiler was chosen, with the focus on its NOX emissions. The control charts generated, based on an emissions sampling scheme through which data were collected by the utility’s CEM system, correctly predicted the NOX emissions. The special causes assigned to the out of control points were verified, validated and classified into three groups as: air control, calibration drift and the unit gross load. As a result, three recommendations focused on air control were provided and generated statistically significant improvements: 1) systematically and continuously train the operators on selecting the best set-ups that minimize emissions based on criteria delineated in a checklist, 2) improve the system maintenance schedule in order to reduce branching that results in a greater likelihood of substantial variation in the flow path resistance, and 3) reduce the accumulation of debris and/or ash particles in air ducts.
Key words: Real-Time Process Monitoring and Control, Cost-Effective Regulatory Compliance

DIGRAPH AND MATRIX METHODS FOR EVALUATING ENVIRONMENTALLY CONSCIOUS MANUFACTURING PROGRAMS, by DR. R. VENKATA RAO

     In the present work, a methodology based on digraph and matrix methods is developed for evaluation of alternative environmentally conscious manufacturing (ECM) programs. An ECM program selection index is proposed that evaluates and ranks ECM programs for a given application. The index is obtained from a ECM program selection attributes function, obtained from the ECM program selection attributes digraph. The digraph is developed considering ECM program selection attributes and their relative importance for the application considered. A step by step procedure for evaluation of ECM program selection index is suggested. An example is included to illustrate the approach. 

Keywords: ECM program selection; Digraph and matrix methods 

PERFORMANCE EVALUATION OF CUTTING FLUIDS FOR GREEN MANUFACTURING USING A COMBINED MULTIPLE ATTRIBUTE DECISION MAKING METHOD, by DR. R. VENKATA RAO

    This paper presents an efficient procedure for selection of a cutting fluid specifically for a green manufacturing situation. The procedure is based on a combined TOPSIS and AHP method. The proposed green cutting fluid selection index helps to evaluate and rank any given set of cutting fluid alternatives. An example is included to illustrate the approach. 

Keywords: Cutting fluid selection; Green manufacturing; Multiple attribute decision making method.