Cost impact analysis of future health management concepts in aviation maintenance

2008 ◽  
Author(s):  
M. Buderath ◽  
H. Fromm
Keyword(s):  
Impact Analysis ◽  
Health Management ◽  
Future Health ◽  
Aviation Maintenance ◽  
Cost Impact ◽  
Management Concepts

A cost/impact analysis of selected clinical pharmacy functions in three hospitals

1974 ◽  
Vol 31 (10) ◽  
pp. 947-953
Author(s):  
Paul J. Munzenberger ◽  
Larry N. Swanson ◽  
Robert E. Smith ◽  
Frances H. Zalewski ◽  
Jules I. Schwartz ◽  
...  
Keyword(s):  
Clinical Pharmacy ◽  
Impact Analysis ◽  
Cost Impact

scholarly journals Clinical and Cost Impact Analysis of a Novel Prognostic Test for Early Detection of Preterm Birth

2016 ◽  
Vol 06 (04) ◽  
pp. e407-e416 ◽  
Author(s):  
John Zupancic ◽  
James Greenberg ◽  
Susan Garfield ◽  
Stephen Thung ◽  
Jay Iams ◽  
...  
Keyword(s):  
Preterm Birth ◽  
Early Detection ◽  
Impact Analysis ◽  
Prognostic Test ◽  
Cost Impact

Quantifying costs of the productivity loss due to schedule changes in construction projects

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jae-Seob Lee
Keyword(s):  
Construction Projects ◽  
Design Methodology ◽  
Impact Analysis ◽  
Productivity Loss ◽  
Content Type ◽  
Cost Impact ◽  
Analysis Technique ◽  
Lost Productivity ◽  
Change Order ◽  
Practical Implications

PurposeThe purpose of the paper is to develop a method to integrate the schedule-based analysis with a productivity-based analysis to prove and support the result of the damages calculation.Design/methodology/approachIn this paper, a “cost and schedule impact integration” (CSI2) model is proposed to objectively show and estimate lost productivity due to changes in construction projects.FindingsA schedule-based analysis to include separate tracking of change order costs can be used to predict productivity due to the delay and disruption; changes in construction projects almost always result in delay and disruption. However, the schedule-based analysis needs to be integrated with a productivity-based analysis to prove and support the result of the damages calculation.Practical implicationsThe results of this study expand upon construction practices for proving and quantifying lost productivity due to changes in construction projects.Originality/valueThe contribution of the paper is summarized as the introduction of a “schedule impact analysis” into a “cost impact analysis” technique to assess the damages, as well as to demonstrate the labor productivity impact due to delay and disruption in construction projects.

scholarly journals The economics of altruistic punishment and the maintenance of cooperation

2008 ◽  
Vol 275 (1637) ◽  
pp. 871-878 ◽  
Author(s):  
Martijn Egas ◽  
Arno Riedl
Keyword(s):  
Impact Analysis ◽  
Low Cost ◽  
Threshold Level ◽  
Altruistic Punishment ◽  
Cost Impact ◽  
The Social ◽  
Subject Pool ◽  
The Cost ◽  
The Impact ◽  
Cognitive Cost

Explaining the evolution and maintenance of cooperation among unrelated individuals is one of the fundamental problems in biology and the social sciences. Recent findings suggest that altruistic punishment is an important mechanism maintaining cooperation among humans. We experimentally explore the boundaries of altruistic punishment to maintain cooperation by varying both the cost and the impact of punishment, using an exceptionally extensive subject pool. Our results show that cooperation is only maintained if conditions for altruistic punishment are relatively favourable: low cost for the punisher and high impact on the punished. Our results indicate that punishment is strongly governed by its cost-to-impact ratio and that its effect on cooperation can be pinned down to one single variable: the threshold level of free-riding that goes unpunished. Additionally, actual pay-offs are the lowest when altruistic punishment maintains cooperation, because the pay-off destroyed through punishment exceeds the gains from increased cooperation. Our results are consistent with the interpretation that punishment decisions come from an amalgam of emotional response and cognitive cost–impact analysis and suggest that altruistic punishment alone can hardly maintain cooperation under multi-level natural selection. Uncovering the workings of altruistic punishment as has been done here is important because it helps predicting under which conditions altruistic punishment is expected to maintain cooperation.

Gas Turbine Health State Prognostics by Means of Bayesian Hierarchical Models

2019 ◽  
Author(s):  
Enzo Losi ◽  
Mauro Venturini ◽  
Lucrezia Manservigi
Keyword(s):  
Gas Turbine ◽  
Field Data ◽  
Health Management ◽  
Theoretical Background ◽  
Health State ◽  
Prediction Errors ◽  
Probabilistic Prediction ◽  
Future Health ◽  
Bayesian Hierarchical ◽  
Prediction Reliability

Abstract The prediction of the time evolution of gas turbine performance is an emerging requirement of modern prognostics and health management (PHM), aimed at improving system reliability and availability, while reducing life cycle costs. In this work, a data-driven Bayesian Hierarchical Model (BHM) is employed to perform a probabilistic prediction of gas turbine future health state thanks to its capability to deal with fleet data from multiple units. First, the theoretical background of the predictive methodology is outlined to highlight the inference mechanism and data processing for estimating BHM predicted outputs. Then, BHM is applied to both simulated and field data representative of gas turbine degradation to assess its prediction reliability and grasp some rules of thumb for minimizing BHM prediction error. For the considered field data, the average values of the prediction errors were found to be lower than 1.0 % or 1.7 % for single- or multi-step prediction, respectively.

Industrial Robot Accuracy Degradation Monitoring and Quick Health Assessment

2019 ◽  
Vol 141 (7) ◽  
Author(s):  
Guixiu Qiao ◽  
Brian A. Weiss
Keyword(s):  
Production Efficiency ◽  
Health Management ◽  
Research Effort ◽  
Industrial Robot ◽  
Health Assessment ◽  
Test Method ◽  
Health State ◽  
Future Health ◽  
Robot Accuracy ◽  
Degradation Monitoring

Robot accuracy degradation sensing, monitoring, and assessment are critical activities in many industrial robot applications, especially when it comes to the high accuracy operations which may include welding, material removal, robotic drilling, and robot riveting. The degradation of robot tool center accuracy can increase the likelihood of unexpected shutdowns and decrease manufacturing quality and production efficiency. The development of monitoring, diagnostic and prognostic (collectively known as prognostics and health management (PHM)) technologies can aid manufacturers in maintaining the performance of robot systems. PHM can provide the techniques and tools to support the specification of a robot’s present and future health state and optimization of maintenance strategies. This paper presents the robotic PHM research and the development of a quick health assessment at the U.S. National Institute of Standards and Technology (NIST). The research effort includes the advanced sensing development to measure the robot tool center position and orientation; a test method to generate a robot motion plan; an advanced robot error model that handles the geometric/nongeometric errors and the uncertainties of the measurement system, and algorithms to process measured data to assess the robot’s accuracy degradation. The algorithm has no concept of the traditional derivative or gradient for algorithm converging. A use case is presented to demonstrate the feasibility of the methodology.

scholarly journals Nutritional genomics: food industry applications from farm to fork

2007 ◽  
Vol 97 (6) ◽  
pp. 1027-1035 ◽  
Author(s):  
Louise Brown ◽  
Frans van der Ouderaa
Keyword(s):  
Food Industry ◽  
Health Management ◽  
Animal Health ◽  
Economic Benefits ◽  
Agriculture Sector ◽  
Genomic Technologies ◽  
Management Concepts ◽  
Science Area ◽  
Breeding Programmes ◽  
Nutritional Genomics

Nutritional genomics is a new and promising science area which can broadly be defined as the application of high throughput genomics (transcriptomics, proteomics, metabolomics/metabonomics) and functional genomic technologies to the study of nutritional sciences and food technology. First utilised in the food industry by plant biotechnologists to manipulate plant biosynthetic pathways, the use of genomic technologies has now spread within the agriculture sector, unleashing a host of new applications (e.g. approaches for producing novel, non-transgenic plant varietals; identification of genetic markers to guide plant and animal breeding programmes; exploration of diet–gene interactions for enhancing product quality and plant/animal health). Beyond agriculture, genomic technologies are also contributing to the improvement of food processing, food safety and quality assurance as well as the development of functional food products and the evolution of new health management concepts such as ‘personalised nutrition’, an emerging paradigm in which the diet of an individual is customised, based on their own genomic information, to optimise health and prevent disease. In this review the relevance of nutritional genomics to the food industry will be considered and examples given on how this science area is starting to be leveraged for economic benefits and to improve human nutrition and health.

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