A zero-one integer programming for preventive maintenance scheduling for electricity and distiller plants with production

Purpose The purpose of this paper is to describe a method that has been set up to schedule preventive maintenance (PM) tasks for power and water plants with all constraints such as production and maintenance. Design/methodology/approach The proposed methodology relies on the zero-one integer program...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Journal of quality in maintenance engineering Ročník 26; číslo 4; s. 555 - 574
Hlavní autori: Alhamad, Khaled, Alhajri, Mohammad
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Bradford Emerald Publishing Limited 12.10.2020
Emerald Group Publishing Limited
Predmet:
ISSN:1355-2511, 1758-7832
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Purpose The purpose of this paper is to describe a method that has been set up to schedule preventive maintenance (PM) tasks for power and water plants with all constraints such as production and maintenance. Design/methodology/approach The proposed methodology relies on the zero-one integer programming model that finds the maximum number of power and water units available in separate generating units. To verify this, the model was implemented and tested as a case study in Kuwait for the Cogeneration Station. Findings An effective solution can be achieved for scheduling the PM tasks and production at the power and water cogeneration plant. Practical implications The proposed model offers a practical method to schedule PM of power and water units, which are expensive equipment. Originality/value This proposed model is an effective decision-making tool that provides an ideal solution for preventive maintenance scheduling problems for power and water units in a cogeneration plant, effectively and complies with all constraints.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1355-2511
1758-7832
DOI:10.1108/JQME-12-2018-0102