Failure rate evaluation with influencing factors

A new methodology for failure rate evaluation with influencing factors is proposed. A quantitative part allows integrating potential available data from feedback. Then, a qualitative analysis deals with influencing factors such as design, environment, and use to provide more coherent and argued results. The main idea is to use some criteria to fix the failure rate within a prior interval, according to the influencing factor states. To this end, the system is broken up into main component groups. When a component group is susceptible to an influencing factor, its baseline failure rate is multiplied by the relevant influencing coefficient. A seven-step methodology is presented to define the model, identify and rate the influencing factors, set indicator functions taking the uncertainties into account, and calculate the influencing coefficients. The proposed methodology is global enough to be usable for a large number of safety instrumented systems and influencing factors. For example, an application regarding safety pressure relief valves is given. The prospect is for more efficient risk management by acting both on systems and influencing factors.     

Process chemicals – An ever present concern during plant shutdowns

Chemical accidents during process plant shutdowns may have severe consequences. In spite of this, the safety management systems in place in many companies still mainly cover the normal operations and little explicitly addresses the maintenance shutdown and plant start-up phases. A Finnish research project found that the level of safety during shutdowns is more closely related to the skills of key individuals at the plants and less due to the systematic safety management system of the companies. A guidebook on the topic in conjunction with tools to improve the situation were developed during the project in order to help the companies improve their documentation associated with chemical safety during shutdowns.     

Common operations failure modes in the process industries

The Abnormal Situation Management^® (ASM^®) Consortium (This research study was sponsored by the Abnormal Situation Management (ASM) Consortium. ASM^® and Abnormal Situation Management^® are registered trademarks of Honeywell International, Inc.) funded a study to investigate common failure modes and root causes associated with operations practices. The study team analyzed 20 public and 12 private incident reports using the TapRoot^® methodology to identify root causes. These root causes were mapped to operations practice failures. This paper describes the top ten operations failure modes identified in the analysis. Specific recommendations include how to analyze plant incident reports to better understand the sources of systemic failures and improve plant operating practices.     

Leading and lagging: Process safety climate–incident relationships at one year

In order to evaluate the leading and lagging effects of process safety climate on incidents, we correlated safety climate survey data with organizational safety records from before and after the survey time period. We obtained data from a large, multinational organization with manufacturing operations involving a number of complex processes, chemicals, and hazardous substances. A total of 7728 employees from 62 sites responded to a safety climate survey in 2007. Individual responses were aggregated to the site-level and matched to site-level organizational records of process safety incidents 1 year before and 1 year after survey administration. Employees’ perceptions of good routine housekeeping were significantly related to environmental impact incidents as both a leading and a lagging indicator, as well as fires/explosions and property damage outcomes. Employees’ perceptions of systems to prevent backlogs and the extent to which health and safety problems are promptly corrected were also related to environmental releases and fires/explosions. Implications for process safety climate research, organizational survey strategies, and organizational climate change are discussed.     

Oxidation of kerosene components in a soil matrix by a dielectric barrier discharge reactor

This paper discusses some aspects of the kerosene components oxidation in a soil matrix by a dielectric barrier discharge reactor at atmospheric pressure. The total kerosene components abatement can reaches 90% for an energy density of 960 J g_soil^?1. The analyses of the discharge cell outlet gas reveals that CO_x and hydrocarbon compounds selectivity is close to 10%. A semi-quantitative approach by GC-FID shows that the carbon content in the oxidized compounds in soil is about 20% of the carbon content in the initial kerosene components. The polar species formed in soil are a mixture of aliphatic and aromatic molecules containing alcohol and carboxylic acid groups. The process of kerosene oxidation in soil matrix is more promoted than kerosene desorption followed by an oxidation in gas phase.     

Estimation of chemical concentration due to fugitive emissions during chemical process design

Fugitive emissions are not an environmental concern alone, but are also a health concern. From occupational health standpoint, fugitive emissions are the main sources of origin of the continuous exposure to workers. Operating plants regularly measure release and concentration levels through a plant-monitoring program. However, for processes which are still ‘on paper’, predictive estimation methods are required. Therefore, three methods for estimating concentration of the fugitive emissions are presented for the process development and design phases of petrochemical processes. The methods estimate the fugitive emission rates and plant plot dimensions resulting to fugitive emission concentrations. The methods were developed for the type and amount of information available in three process design stages; conceptual design, preliminary process design, and detailed process design. The methods are applied on a real benzene plant; the estimated benzene concentrations are compared to the actual concentration measured at the plant. The results show that as the information mounts up during design, the concentration estimate becomes more accurate. The results indicate that the methods presented provide simple estimates of fugitive emission-based concentrations during the design stages.     

Climatic and genetic controls of yields of switchgrass, a model bioenergy species

The U.S. Renewable Fuel Standard calls for 136 billion liters of renewable fuels production by 2022. Switchgrass (Panicum virgatum L.) has emerged as a leading candidate to be developed as a bioenergy feedstock. To reach biofuel production goals in a sustainable manner, more information is needed to characterize potential production rates of switchgrass. We used switchgrass yield data and general additive models (GAMs) to model lowland and upland switchgrass yield as nonlinear functions of climate and environmental variables. We used the GAMs and a 39-year climate dataset to assess the spatio-temporal variability in switchgrass yield due to climate variables alone. Variables associated with fertilizer application, genetics, precipitation, and management practices were the most important for explaining variability in switchgrass yield. The relationship of switchgrass yield with climate variables was different for upland than lowland cultivars. The spatio-temporal analysis showed that considerable variability in switchgrass yields can occur due to climate variables alone. The highest switchgrass yields with the lowest variability occurred primarily in the Corn Belt region, suggesting that prime cropland regions are the best suited for a constant and high switchgrass biomass yield. Given that much lignocellulosic feedstock production will likely occur in regions with less suitable climates for agriculture, interannual variability in yields should be expected and incorporated into operational planning.     

First-trimester maternal factors and biomarker screening for preeclampsia

Preeclampsia (PE), which affects about 2% of pregnancies, is a major cause of maternal and perinatal morbidity and mortality. PE can be subdivided into early onset PE with delivery <34 weeks' gestation and late onset PE with delivery ≥34 weeks. Early onset PE is associated with a higher incidence of adverse outcome. This review illustrates that effective screening for the development of early onset PE can be provided in the first-trimester of pregnancy. Screening by a combination of maternal risk factors, mean arterial pressure, uterine artery Doppler, maternal serum pregnancy-associated plasma protein-A and placental growth factor can identify about 95% of cases of early onset PE for a false-positive rate of 10%. © 2014 John Wiley & Sons, Ltd.