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Wyświetlanie 1-2 z 2
Tytuł:
Contribution Overview to the Evaluation and Development of Spare Parts Management Models: Meta-Heuristic and Probabilistic Methods
Autorzy:
Bounou, Oumaima
El Barkany, Abdellah
El Biyaali, Ahmed
Powiązania:
https://bibliotekanauki.pl/articles/1841431.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
spare parts
maintenance
inventory management
probabilistic methods
meta heuristic method
risk management
performance
Opis:
The presence of the spare parts stock is a necessity to ensure the continuity of services. The supply of spare parts is a special case of the global supply chain. The main objective of our research is to propose a global spare parts management approach which allows decision makers to determine the essential points in stock management. Thus, it is important for the stock manager to evaluate the system considered from time to time based on performance indicators. Some of these indicators are presented in the form of a dashboard. The presentation of this chapter chronologically traces the progress of our research work. In the first part, we present the work related to the forecast of spare parts needs through parametric and statistical methods as well as a Bayesian modelling of demand forecasting. To measure the appreciation of the supply of spare parts inventory, the second part focuses on work related to the evaluation of the performance of the spare parts system. Thus, we concretize the link between the management of spare parts and maintenance in the third part, more precisely, in the performance evaluation of the joint -management of spare parts and maintenance, in order to visualize the influence of parameters on the system. In the last section of this chapter, we will present the metaheuristic methods and their use in the management of spare parts and maintenance and make an analysis on work done in the literature.
Źródło:
Management and Production Engineering Review; 2021, 12, 1; 24-37
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Experiencing a probabilistic approach to clarify and disclose uncertainties when setting occupational exposure limits
Autorzy:
Vernez, David
Fraize-Frontier, Sandrine
Vincent, Raymond
Binet, Stéphane
Rousselle, Christophe
Powiązania:
https://bibliotekanauki.pl/articles/2159984.pdf
Data publikacji:
2018-07-04
Wydawca:
Instytut Medycyny Pracy im. prof. dra Jerzego Nofera w Łodzi
Tematy:
risk management
chemical toxicity
assessment factors
uncertainty distributions
probabilistic methods
occupational exposure limits
Opis:
Objectives Assessment factors (AFs) are commonly used for deriving reference concentrations for chemicals. These factors take into account variabilities as well as uncertainties in the dataset, such as inter-species and intra-species variabilities or exposure duration extrapolation or extrapolation from the lowest-observed-adverse-effect level (LOAEL) to the noobserved- adverse-effect level (NOAEL). In a deterministic approach, the value of an AF is the result of a debate among experts and, often a conservative value is used as a default choice. A probabilistic framework to better take into account uncertainties and/or variability when setting occupational exposure limits (OELs) is presented and discussed in this paper. Material and methods Each AF is considered as a random variable with a probabilistic distribution. A short literature was conducted before setting default distributions ranges and shapes for each AF commonly used. A random sampling, using Monte Carlo techniques, is then used for propagating the identified uncertainties and computing the final OEL distribution. Results Starting from the broad default distributions obtained, experts narrow it to its most likely range, according to the scientific knowledge available for a specific chemical. Introducing distribution rather than single deterministic values allows disclosing and clarifying variability and/or uncertainties inherent to the OEL construction process. Conclusions This probabilistic approach yields quantitative insight into both the possible range and the relative likelihood of values for model outputs. It thereby provides a better support in decision-making and improves transparency. Int J Occup Med Environ Health 2018;31(4):475–489
Źródło:
International Journal of Occupational Medicine and Environmental Health; 2018, 31, 4; 475-489
1232-1087
1896-494X
Pojawia się w:
International Journal of Occupational Medicine and Environmental Health
Dostawca treści:
Biblioteka Nauki
Artykuł
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