Application of OEE Coefficient for Manufacturing Lines Reliability Improvement

Gola, Arkadiusz; Nieoczym, A.

doi:10.2991/msmi-17.2017.42

Cited by 7 publications

(3 citation statements)

References 19 publications

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“…Contemporary publications describing the results of research on the efficiency of exploitation cover a wide range of issues concerning Total Productive Maintenance (TPM) strategy, including methodological assumptions, among others [21,34], and application solutions [16,29,30]. Attempts to build computational models and their industrial verification are also widely undertaken, based on the measures focused on the OEE model [9,28], or operational measures concentrated in a set of KPI (Key Performance Indicators) [22,27,31], often associated with the issue of benchmarking [26,37].…”

Section: Analysis Of the Possibility And Need Of Using Oeementioning

confidence: 99%

Geometric approach to machine exploitation efficiency : modelling and assessment

Loska¹,

Paszkowski²

2022

Eksploatacja i Niezawodność – Maintenance and Reliability

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This article presents a new approach to the exploitation assessment of machines and devices. A key aspect of this approach is the construction of the assessment model based on the geometric representation of measures associated with each other, which covers the full specifics of the exploitation process. This approach is successfully implemented by the Overall Equipment Effectiveness (OEE) model, which is fully susceptible to the geometric modelling process due to the three-way system of assessed exploitation aspects. The result of this approach is the vectored OEE model and its interpretation in terms of time series of changes in values of components. Methods of determining vector calculus measures were developed, including the second-order tensor and gradient. This is the subject of the variability of the reliability conditions of machines or production processes. It allows for the realisation of an exploitation assessment based on dynamic changes in the values of their components in the time domain. This is a significant difference to the classical static approach to such an assessment. The developed new geometric OEE model was confirmed by verification tests using the LabView software, based on two parallel data sets obtained with analytical and simulation methods using the FlexSim software.

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Section: Analysis Of the Possibility And Need Of Using Oeementioning

confidence: 99%

Geometric approach to machine exploitation efficiency : modelling and assessment

Loska¹,

Paszkowski²

2022

Eksploatacja i Niezawodność – Maintenance and Reliability

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“…Table 1 illustrates all the fields that are provided in the description of any KPI in the ISO 22400 standards. Besides the ISO 22400 standards, the Overall Equipment Effectiveness (OEE), the Overall Throughput Effectiveness (OTE) and the Sustainable OTE present other commonly used KPIs for measuring the efficiency of machines and systems, as described in [19,20]. Table 1.…”

Section: Existing Kpi Based Solutionsmentioning

confidence: 99%

Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems

et al. 2018

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The employment of tools and techniques for monitoring and supervising the performance of industrial systems has become essential for enterprises that seek to be more competitive in today’s market. The main reason is the need for validating tasks that are executed by systems, such as industrial machines, which are involved in production processes. The early detection of malfunctions and/or improvable system values permits the anticipation to critical issues that may delay or even disallow productivity. Advances on Information and Communication Technologies (ICT)-based technologies allows the collection of data on system runtime. In fact, the data is not only collected but formatted and integrated in computer nodes. Then, the formatted data can be further processed and analyzed. This article focuses on the utilization of standard Key Performance Indicators (KPIs), which are a set of parameters that permit the evaluation of the performance of systems. More precisely, the presented research work demonstrates the implementation and visualization of a set of KPIs defined in the ISO 22400 standard-Automation systems and integration, for manufacturing operations management. The approach is validated within a discrete manufacturing web-based interface that is currently used for monitoring and controlling an assembly line at runtime. The selected ISO 22400 KPIs are described within an ontology, which the description is done according to the data models included in the KPI Markup Language (KPIML), which is an XML implementation developed by the Manufacturing Enterprise Solutions Association (MESA) international organization.

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“…SA plays a crucial role in enhancing the transparency model and guiding decision-making processes by identifying critical factors that influence system behaviour. Given the significance of sensitivity analysis in uncovering the dynamics between input variables and their resultant effects on outputs, it stands as a fundamental tool for enhancing model accuracy and predictive power [6,7]. The significance of SA extends beyond enhancing model transparency; it is instrumental in the decision-making process by identifying key factors that influence system behaviour.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Analysis of Sensitivity in Simulation Models for Enhanced System Understanding and Optimisation

Grznár,

Gregor,

Mozol

et al. 2024

Processes

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This article delves into sensitivity analysis within simulation models of real systems, focusing on the impact of variability in independent input factors (x) on dependent system outputs (y). It discusses linear and nonlinear regression to analyse and represent relationships between input factors and system responses. This study encompasses three sensitivity analysis areas: factor screening, local sensitivity analysis, and global sensitivity analysis, highlighting their roles in understanding the significance of factors in simulation models. The practical application of sensitivity analysis becomes clear through a case study in a manufacturing system. The case study utilises the Simio simulation system to investigate the impact of input factors on production lead time and work in process (WIP). The analysis uses regression to quantify the impact of seven factors, showcasing the most significant ones with tornado charts and emphasising the application of sensitivity analysis to optimise system responses.

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Application of OEE Coefficient for Manufacturing Lines Reliability Improvement

Cited by 7 publications

References 19 publications

Geometric approach to machine exploitation efficiency : modelling and assessment

Geometric approach to machine exploitation efficiency : modelling and assessment

Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems

A Comprehensive Analysis of Sensitivity in Simulation Models for Enhanced System Understanding and Optimisation

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