Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Standardising Maintenance Jobs to Improve Grouping Decision Making
Maintenance decision making is an important part of managing the costs, effectiveness and risk of maintenance. One way to improve maintenance efficiency without affecting the risk picture is to group maintenance jobs. Literature includes many examples of algorithms for the grouping of maintenance activities. However, the data is not always available, and with increasing plant complexity comes increasingly complex decision requirements, making it difficult to leave the decision making up to algorithms. This paper suggests a framework for the standardisation of maintenance data as an aid for maintenance experts to make decisions on maintenance grouping. The standardisation improves the basis for decisions, giving an overview of true variance within the available data. The goal of the framework is to make it simpler to apply tacit knowledge and make right decisions. Applying the framework in a case study showed that groups can be identified and reconfigured and potential savings easily estimated when maintenance jobs are standardised. The case study enabled an estimated 7%-9% saved on the number of hours spent on the investigated jobs.
Standardising Maintenance Jobs to Improve Grouping Decision Making
Maintenance decision making is an important part of managing the costs, effectiveness and risk of maintenance. One way to improve maintenance efficiency without affecting the risk picture is to group maintenance jobs. Literature includes many examples of algorithms for the grouping of maintenance activities. However, the data is not always available, and with increasing plant complexity comes increasingly complex decision requirements, making it difficult to leave the decision making up to algorithms. This paper suggests a framework for the standardisation of maintenance data as an aid for maintenance experts to make decisions on maintenance grouping. The standardisation improves the basis for decisions, giving an overview of true variance within the available data. The goal of the framework is to make it simpler to apply tacit knowledge and make right decisions. Applying the framework in a case study showed that groups can be identified and reconfigured and potential savings easily estimated when maintenance jobs are standardised. The case study enabled an estimated 7%-9% saved on the number of hours spent on the investigated jobs.
Standardising Maintenance Jobs to Improve Grouping Decision Making
Agergaard, Julie Krogh (Autor:in) / Sigsgaard, Kristoffer Vandrup (Autor:in) / Mortensen, Niels Henrik (Autor:in) / Ge, Jingrui (Autor:in) / Hansen, Kasper Barslund (Autor:in) / Khalid, Waqas (Autor:in)
01.01.2021
Agergaard , J K , Sigsgaard , K V , Mortensen , N H , Ge , J , Hansen , K B & Khalid , W 2021 , Standardising Maintenance Jobs to Improve Grouping Decision Making . in Proceedings of the Design Society . vol. 1 , Cambridge University Press , pp. 2701 - 2710 , 23rd International Conference on Engineering Design (ICED21) , Gothenburg , Sweden , 16/08/2021 . https://doi.org/10.1017/pds.2021.531
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC:
690
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