Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "maintenance scheduling" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Total production maintenance and robust scheduling for a production system efficiency increasing
Autorzy:
Paprocka, I.
Powiązania:
https://bibliotekanauki.pl/articles/99766.pdf
Data publikacji:
2012
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
Total Productive Maintenance
robust scheduling
modeling
simulation
Opis:
In the paper, the proposition of application of two methodologies: the predictive scheduling and Total Productive Maintenance – TPM to increase efficiency of a production system is presented. To assess wastes due to unplanned events in the machine’s work the Overall Equipment Effectiveness (OEE) indicator is applied. Any failure of a bottle neck decreases value of the OEE. In this paper, the problem of predicting a time of the bottle neck failure is considered. In the paper, models of a production system and failures are presented. For the bottle neck various reliability characteristics are computed: the probability that, beginning with moment t0 , the first failure occurs after given time t, probability that in the interval [f ,g], there occurs at least one failure, failure intensity function, Mean Time To Failure (MTTF) and Mean Time of Repair (MTTR). Having the MTTF and MTTR of the bottle neck, a robust schedule is generated. At the time of predicted failure, preventive actions and technical survey of the machine are scheduled. In the second paper a numerical example is given.
Źródło:
Journal of Machine Engineering; 2012, 12, 3; 52-61
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A numerical example of total production maintenance and robust scheduling application for a production system efficiency increasing
Autorzy:
Paprocka, I.
Urbanek, D.
Powiązania:
https://bibliotekanauki.pl/articles/99603.pdf
Data publikacji:
2012
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
Total Productive Maintenance
robust scheduling
modeling
simulation
Opis:
In the paper, the proposition of application of two methodologies: the predictive scheduling and Total Productive Maintenance - TPM to increase efficiency of a production system is presented. In this paper, an example of problem of predicting a time of a bottle neck failure is presented. Using the Statistica program, histograms that show the graphical relationship of a number of observations and failure-free times of the bottle neck for historical periods are created. The fitting of the histograms to the theoretical distributions: normal, exponential, gamma and Weibull using appropriate tests (for example the Kolmogorov-Smirnov test for normal distribution) is researched. After finding distribution and setting parameters for historical periods, for the next scheduling horizon values of parameters are extrapolated using the regression method in the Statistica program. For the bottle neck various reliability characteristics are computed. Having the Mean Time To Failure (MTTF) and Mean Time of Repair (MTTR) of the bottle neck, robust schedule is generated. At the time of the predicted failure, preventive actions and technical survey of the machine are scheduled. The production system is modeled in the simulation program - Enterprise Dynamics 8.1.
Źródło:
Journal of Machine Engineering; 2012, 12, 3; 62-79
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies