Analysis of the impact of the Asset Health Index in a Maintenance Strategy

Hosted by the Johannes Kepler University, Linz, Austria. May 23-24, 2019 - European Safety, Reliability & Data Association (ESReDA)During many years, asset management methodologies used in industry were focused on knowing and analysing the operational control of the daily work and the impact of the maintenance on the availability. Later, the costs turn into the priority, and strategies were focused on assesses a longer lifecycle and optimizing processes and contracts. Finally, recent normative have included concepts as “knowing and managing the risks” and the target is to prioritize the maintenance tasks to the critical assets. However, taking a balanced asset management model for the operational environment, quite a lot of facilities of Oil & Gas sector are reaching the end of their initially estimated lifecycle. New challenges are related to extend the life of the main items of the facilities or at least, to find the optimal replacement moment that guarantees that the maintenance strategy is being optimized. Asset Health Index methodology considers a theoretical lifecycle of an item, in which depending on the proximity to the end of the useful life, the probability of failure increases. But take this theoretical lifecycle as a base, different operation location factors or O&M aspects can modify this period. All these factor are quantified and permit us to calculate a new theoretical profile. This paper is about assess the impact of the AHI into the maintenance strategy optimisation. AHI enables us to compare future alternative cost profiles and assess the impact in the failure probability of the item. As a result, we are able to know the risk that is taken when we enlarge the operation of an item, and the impact in the operational costs

Integrating complex asset health modelling techniques with continuous time simulation modelling: A practical tool for maintenance and capital investments analysis

Article number 103507An Asset Health Index (AHI) is a tool that processes data about asset’s condition. That index is intended to explore if alterations can be generated in the health of the asset along its life cycle. These data can be obtained during the asset’s operation, but they can also come from other information sources such as geographical information systems, supplier’s reliability records, relevant external agent’s records, etc. The tool (AHI) provides an objective point of view to justify, for instance, the extension of an asset useful life, or to identify which assets from a fleet are candidates for an early replacement, or renovation, as a consequence of a premature aging. This paper describes how to build the AHI model as a continuous time simulation model, which is then implemented using Vensim simulation environment. This is done in order to: 1) improve model formu lating robustness, 2) benefit of the outstanding software optimization features for AHI model parameters calibration; and 2) easy the provision of predictions for asset degradation, operational and capital invest ments risk under different possible exogenous scenarios and endogenous managerial options. The process of model building, and parameterization is applied to an industrial case of a regasification terminal. Several strategies involving major maintenance scheduling are compared in terms of total expenditure in assets over their life cycle

Procedimiento para la selección de la estrategia de regulación más adecuada en estaciones de bombeo

[ES] La selección de la mejor estrategia de operación en una estación de bombeo que impulsa caudales directamente a red es un problema complejo de problema se puede plantear como la búsqueda de la mejor estrategia en una instalación ya existente (la mejora de un sistema que está en funcionamiento con posibilidades de instalar, por ejemplo, variadores de frecuencia en los equipos de la estación de bombeo y diseñar la estrategia de regulación más adecuada) o bien, directamente, como un problema de selección tanto de los equipos de bombeo como del sistema de regulación para una estación de bombeo a diseñar. Todo ello implica que en cada caso es necesario manejar un campo de soluciones excesivamente amplio, no conociendo la existencia de herramientas que, filtrando y acotando las soluciones posibles, aborden dicho problema teniendo en cuenta las variables más significativas: modelo de las bombas a instalar con sus curvas características, bombas de velocidad fija (BVF), número de bombas de velocidad variable (BVV), rendimiento mínimo aceptable, velocidad mínima y máxima de giro de las bombas, tarifas eléctricas, caudales a impulsar, etc. Debido a esto, el técnico se ve obligado a técnica que acote el número de soluciones. Al actuar de esta forma es posible que en muchos casos se desestimen soluciones atractivas desde el punto de vista energético y económico.Gómez Pajares, P.; García-Serra García, J.; Soriano Olivares, J.; Giner González, C. (2015). Procedimiento para la selección de la estrategia de regulación más adecuada en estaciones de bombeo. Universidad de Córdoba. 1191-1202. http://hdl.handle.net/10251/141658S1191120

Auditoría energética de estaciones de bombeo. Caso de estudio

[ES] El objetivo principal de este estudio es optimizar el funcionamiento de una estación de bombeo, lo que repercutirá directamente en una disminución de los costes de explotación. Para ello, se establecen los siguientes objetivos: - Analizar los flujos energéticos y pérdidas asociadas a cada transformación. - Identificación de los puntos de mejora de rendimiento. - Declaración de escenarios alternativos al actual. - Evaluación y valoración de los ahorros de los escenarios alternativos.Giner González, C.; Gómez Pajares, P.; Sanz Tarrega, F.; García-Serra García, J.; Soriano Olivares, J. (2020). Auditoría energética de estaciones de bombeo. Caso de estudio. 641-654. http://hdl.handle.net/10251/138452S64165

Genomic characterization of individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced lung cancer

Single nucleotide polymorphisms (SNPs) may modulate individual susceptibility to carcinogens. We designed a genome-wide association study to characterize individuals presenting extreme phenotypes of high and low risk to develop tobacco-induced non-small cell lung cancer (NSCLC), and we validated our results. We hypothesized that this strategy would enrich the frequencies of the alleles that contribute to the observed traits. We genotyped 2.37 million SNPs in 95 extreme phenotype individuals, that is: heavy smokers that either developed NSCLC at an early age (extreme cases); or did not present NSCLC at an advanced age (extreme controls), selected from a discovery set (n=3631). We validated significant SNPs in 133 additional subjects with extreme phenotypes selected from databases including >39,000 individuals. Two SNPs were validated: rs12660420 (p(combined)=5.66x10(-5); ORcombined=2.80), mapping to a noncoding transcript exon of PDE10A; and rs6835978 (p(combined)=1.02x10(-4); ORcombined=2.57), an intronic variant in ATP10D. We assessed the relevance of both proteins in early-stage NSCLC. PDE10A and ATP10D mRNA expressions correlated with survival in 821 stage I-II NSCLC patients (p=0.01 and p<0.0001). PDE10A protein expression correlated with survival in 149 patients with stage I-II NSCLC (p=0.002). In conclusion, we validated two variants associated with extreme phenotypes of high and low risk of developing tobacco-induced NSCLC. Our findings may allow to identify individuals presenting high and low risk to develop tobacco-induced NSCLC and to characterize molecular mechanisms of carcinogenesis and resistance to develop NSCLC

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field