In the past two decades researchers in the field of sequencing and scheduling have analyzed several priority dispatching rules through simulation techniques. This paper presents a summary of over 100 such rules, a list of many references that analyze them, and a classification scheme.
The National Institute for Occupational Safety and Health (NIOSH), recognizing the difficulties inherent in using old military data to define modern industrial respirator fit test panels, recently completed a study to develop an anthropometric database of the measurements of heads and faces of civilian respirator users. Based on the data collected, NIOSH researchers developed two new panels for fit testing half-facepiece and full-facepiece respirators. One of the new panels (NIOSH bivariate panel) uses face length and face width. The other panel is based on principal component analysis (PCA) to identify the linear combination of facial dimensions that best explains facial variations. The objective of this study was to investigate the correlation between respirator fit and the new NIOSH respirator fit test panel cells for various respirator sizes. This study was carried out on 30 subjects that were selected in part using the new NIOSH bivariate panel. Fit tests were conducted on the test subjects using a PORTACOUNT device and three exercises. Each subject was tested with three replications of four models of P-100 half-facepiece respirators in three sizes. This study found that respirator size significantly influenced fit within a given panel cell. Face size categories also matched the respirator sizing reasonably well, in that the small, medium, and large face size categories achieved the highest geometric mean fit factors in the small, medium, and large respirator sizes, respectively. The same pattern holds for fit test passing rate. Therefore, a correlation was found between respirator fit and the new NIOSH bivariate fit test panel cells for various respirator sizes. Face sizes classified by the PCA panel also followed a similar pattern with respirator fit although not quite as consistently. For the LANL panel, however, both small and medium faces achieved best fit in small size respirators, and large faces achieved best fit in medium respirators. These findings support the selection of the facial dimensions for developing the new NIOSH bivariate respirator fit test panel.
A study was conducted at a secondary lead smelter to evaluate the workplace performance of the 3M W-344 and Racal AH3 powered air-purifying respirators equipped with helmets and high efficiency filters. The research protocol developed for the study has been described in a companion paper. The results of the study indicate that the mean lead concentrations, measured inside the facepiece of both PAPRs, were significantly less than the OSHA lead exposure limit of 50 micrograms/m3. The means of the workplace protection factor measurements on both PAPRs were significantly less than the PAPR selection guide protection factor classification of 1000. Correlation analysis of preshift quantitative fit factors and corresponding workplace protection factors indicated no linear association between these two measures of performance. This finding suggests that for PAPRs equipped with helmets and high efficiency filters quantitative fit factors as presently determined are not indicative of the workplace protection which the respirators provide. Since the PAPR protection factor classification of 1000 was originally based on quantitative fit factors, the lack of a demonstrated association between quantitative fit factors and workplace protection as found in this study may explain why their performance was significantly less than expected.
A model was developed to simulate the operations of the Same Day Care Unit (SDCU) at a major medical institution, and to evaluate the system performance for different alternatives, under various patient load conditions. The model was used to successfully identify the facility needs at the SDCU in order to optimize patient care and accommodate projected growth in patient volumes.
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