Site reliability engineering for IOS mobile application in small-medium scale industries

Kavyashree, N; Chandramouli, Supriya Maganahalli; Lokesh, .

doi:10.1016/j.gltp.2021.08.065

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…An additional filter to our search was the date of publication: for the most appropriate findings, only recent (since 2017) articles were processed. As a first step of the research, requirements and indicators were collected and evaluated from the literature [29][30][31][32][33][34][35][36][37][38][39][40][41][42][43]. This input supported the authors to make AHP analyses with the use of which the importance of these components were calculated and consistency calculations carried out.…”

Section: Meta-analysismentioning

confidence: 99%

Selection of Production Reliability Indicators for Project Simulation Model

2022

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Due to technological enhancements, traditional, qualitative decision-making methods are usually replaced by data-driven decision-making even in smaller companies. Process simulation is one of these solutions, which can help companies avoid costly failures as well as evaluate positive or negative effects. The reason for this paper is twofold: first, authors conducted a Quality Function Deployment analysis to find the most vital reliability indicators in the field of production scheduling. The importance was acquired from the meta-analysis of papers published in major journals. The authors found 3 indicators to be the most important: mean time between failure (MTBF), mean repair time and mean downtime. The second part of the research is for the implementation of these indicators to the stochastic environment: possible means of application are proposed, confirming the finding with a case study in which 100 products must be produced. The database created from the simulation is analyzed in terms of major production KPIs, such as production quantity, total process time and efficiency of the production. The results of the study show that calculating with reliability issues in production during the negotiation of a production deadline supports business excellence.

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