4 resultados para Objective measures
em Digital Commons at Florida International University
Resumo:
Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.
Resumo:
Salinity, water temperature, and chlorophyll a (chl-a) biomass were used as performance measures in the period 1999–2001 to evaluate the effect of a hydrological rehabilitation project in the Ciénaga Grande de Santa Marta (CGSM)–Pajarales lagoon complex, Colombia where freshwater diversions were initiated in 1995 and completed in 1998. The objective of this study was to evaluate how diversions of freshwater into previously hypersaline (>80) environments changed the spatial and temporal distribution of environmental characteristics. Following the diversion, 19 surveys and transects using a flow-through system were surveyed in the CGSM–Pajarales complex to continuously measure selected water quality parameters. Geostatistical analysis indicates that hydrology and salinity regimes and water circulation patterns in the CGSM lagoon are largely controlled by freshwater discharge from the Fundacion, Aracataca, and Sevilla Rivers. Residence times in the CGSM lagoon were similar before (15.5 ± 3.8 days) and after (14.2 ± 2.0 days) the rehabilitation project and indicated that the system is flushed regularly. In contrast, chl-a biomass was highly variable in the CGSM–Pajarales lagoon complex and not related to discharge patterns. Mean annual chl-a biomass (44–250 μg L−1) following the diversion project was similar to values recorded since the 1980s and still remains among the highest reported in coastal systems around the world owing to its unique hydrology regulated by the Magdalena River and Sierra Nevada de Santa Marta watersheds and the high teleconnection to the El Niño Southern Oscillation (ENSO). Our results confirm that the reduction in salinity in the CGSM lagoon and Pajarales complex during 1999–2000 was largely driven by high precipitation (2500 mm) induced by the ENSO–La Niña rather than by the freshwater diversions.
Resumo:
Context: Accurately determining hydration status is a preventative measure for exertional heat illnesses (EHI). Objective: To determine the validity of various field measures of urine specific gravity (Usg) compared to laboratory instruments. Design: Observational research design to compare measures of hydration status: urine reagent strips (URS) and a urine color (Ucol) chart to a refractometer. Setting: We utilized the athletic training room of a Division I-A collegiate American football team. Participants: Trial 1 involved urine samples of 69 veteran football players (age=20.1+1.2yr; body mass=229.7+44.4lb; height=72.2+2.1in). Trial 2 involved samples from 5 football players (age=20.4+0.5yr; body mass=261.4+39.2lb; height=72.3+2.3in). Interventions: We administered the Heat Illness Index Score (HIIS) Risk Assessment, to identify athletes at-risk for EHI (Trial 1). For individuals “at-risk” (Trial 2), we collected urine samples before and after 15 days of pre-season “two-a-day” practices in a hot, humid environment(mean on-field WBGT=28.84+2.36oC). Main Outcome Measures: Urine samples were immediately analyzed for Usg using a refractometer, Diascreen 7® (URS1), Multistix® (URS2), and Chemstrip10® (URS3). Ucol was measured using Ucol chart. We calculated descriptive statistics for all main measures; Pearson correlations to assess relationships between the refractometer, each URS, and Ucol, and transformed Ucol data to Z-scores for comparison to the refractometer. Results: In Trial 1, we found a moderate relationship (r=0.491, p<.01) between URS1 (1.020+0.006μg) and the refractometer (1.026+0.010μg). In Trial 2, we found marked relationships for Ucol (5.6+1.6shades, r=0.619, p<0.01), URS2 (1.019+0.008μg, r=0.712, p<0.01), and URS3 (1.022+0.007μg, r=0.689, p<0.01) compared to the refractometer (1.028+0.008μg). Conclusions: Our findings suggest that URS were inconsistent between manufacturers, suggesting practitioners use the clinical refractometer to accurately determine Usg and monitor hydration status.
Resumo:
Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.