An assessment of maintenance performance indicators using the fuzzy sets approach and genetic algorithms

Abstract

In this article, a novel approach for assessment and ranking of maintenance process indicators as well as maintenance cost indicators and maintenance equipment indicators using the fuzzy sets approach and genetic algorithms is presented. Weight values of these indicators are defined using the experience of decision makers from analyzed small and medium enterprises (total number of 197 persons) and calculated using the fuzzy sets approach. In the second step, a model for ranking and optimization of maintenance performance indicators and small and medium enterprises by using genetic algorithm is presented. The presented approach enables multi-objective optimization of selected key performance indicators in the scope of optimization of maintenance performances. The value of optimization was tested on a group of small and medium enterprises which proved that improvement of maintenance performance could be more significant (or performed at the shorter period of time) if the specific key performance indicators were targeted for improvement. The presented solution could provide identification of strengths and weaknesses (comparing key performance indicators), learning from a leading organization (in prioritization of key performance indicator improvement) and improvement of maintenance performance.

The Application of the EDAS Method in the Parametric Selection Scheme for Maintenance Plans in the Nigerian Food Industry

“…The principal indicators were grouped using the analytical hierarchy process multicriteria tool. Moreover, Stefanovic et al (2017) dealt with the subject of the ranking maintenance process, cost and equipment indicators with the methods of fuzzy sets and genetic procedure. The proposed procedure allowed the optimisation of the chosen principal performance indices.…”

“…However, VIKOR and TOPSIS are concerned with the distance from the ideal and nadir solutions to establish a superior option. With the stated benefit of EDAS, it has gained recognition in several fields in the literature: traffic problems (Kikomba et al, 2016), steam boiler choices (Kundakci, 2019), autonomous maintenance (Srivastava et al, 2020), smartphone evaluation (Aggraval et al, 2018), maintenance performance assessment (Stefanovic et al, 2017), logistics (Stevic et al, 2016, sewing machine choice (Ulutas, 2017), waste disposal site choice (Kahraman et al, 2017) and third-party logistics (Ecer, 2017).…”

Gestão Da Manutenção Industrial: Procedimento Para Suporte a Tomada De Decisão

“…A medição do desempenho de manutenção (MPM) é uma parte dos processos de gerenciamento de manutenção e uma ferramenta de gerenciamento para a viabilidade econômica de longo prazo da organização. Indicadores de desempenho bem definidos podem potencialmente apoiar a identificação de lacunas de desempenho, entre o desempenho atual e o desejado, e podem indicar o progresso para o fechamento das lacunas (Assaf et al 2015;Stefanovic et al 2017;Muchiri et al 2011).…”

“…Várias pesquisas foram focadas na seleção correta de KPIs ou diferentes estruturas aplicadas em diferentes setores. Estruturas de MPM também foram desenvolvidas e discutidas para setores específicos, como a indústria de mineração ou aviação militar, ou uma classe específica de empresas, como pequenas e médias empresas (PMEs) (Assaf et al 2015;Stefanovic et al 2017). 6…”

Performance indicators for measuring the effects of Smart Maintenance

“…For a long time, there has been a lack of consensus about which methodologies to use for PIs selection (Kumar et al , 2013). Researchers have, therefore, suggested different approaches for maintenance PIs selection (see for example: Stefanovic et al , 2017; Fangucci et al , 2017; Brundage et al , 2018; Wijesinghe and Mallawarachchi, 2019). In spite of this, the most common approach in practice is to select PIs based on measures already available, which neglects its relevance (Simões et al , 2016).…”