Overall Equipment Effectiveness Measurement: Weighted Approach Method and Fuzzy Expert System

Maran, Murasoli; Manikandan, G.; Thiagarajan, K.

doi:10.1007/978-94-007-5651-9_17

Cited by 7 publications

(6 citation statements)

References 8 publications

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“…1 Sukanta and R Maulana are with Departement of Industrial Engineering, University of Singaperbangsa Karawang, Karawang -West Java, 41361, Indonesia. Email: sukanta@staff.unsika.ac.id 2 Dessy Agustina Sari is with Departement of Electrical Engineering, University of Singaperbangsa Karawang, Karawang -West Java, 41361, Indonesia.…”

Section: Methodsmentioning

confidence: 99%

“…The OEE point could show the latest situation in SIC line 1 and performance all of the equipment that losing could be pushed. This way also acted as image performance from day to day and as tools in continuous improvement program for manufacturing industry [2] and supported by supply of necessary resources [3]. Data that given was weekly outlet OEE on 1st until 31st -2016 years, see Figure 3 -6.…”

Section: A Measuring Of Overall Equipment Effectivenessmentioning

confidence: 99%

“…OEE could do compilation between daily and artificial report. Both of them were headed to company future (Maran et al, 2012). Implementation was a next step to improve productivity thorough production planning and maintenance procedure [4], [9].…”

Section: Domentioning

confidence: 99%

See 2 more Smart Citations

Implementations of Autonomous Maintenance to Relieve Stoppages on PT NIKF – Sachet Packaging Chain

Sukanta

Maulana

Sari

2019

JTS

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Autonomous maintenance taught operator to keep devices, create cooperation each employer and did problem solving that occurring in machine. This research described assembling of autonomous maintenance on PT NIKFminor stoppages trouble in sachet production line. Our team used the OEE method to know the latest line condition and variety losses that causing the performance were not optimal. After that, the next steps were using visual losses map and diagram Pareto to get the detail (component with many losses). By Go See Think Do, the researcher could find much maintenance that must be done in SIC line 1. Through the application, this effort could reduce the losses of minor stoppages-79,52%.

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Section: Methodsmentioning

confidence: 99%

Section: A Measuring Of Overall Equipment Effectivenessmentioning

confidence: 99%

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Implementations of Autonomous Maintenance to Relieve Stoppages on PT NIKF – Sachet Packaging Chain

Sukanta

Maulana

Sari

2019

JTS

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“…Given the above, the OEE is normally calculated as follows: OEE = A × P × Q Therefore OEE takes into account the six major losses. Significant improvement can be achieved within a short period by eliminating these losses in industry as a result of enhanced maintenance activities and equipment management (M. Maran et al, 2012). In a situation where a manufacturing line consists of unbalanced/decoupled machines OEE alone is not sufficient (Braglia et al, 2009).…”

Section: Total Piecesmentioning

confidence: 99%

Overall Equipment Effectiveness and Overall Line Efficiency Measurement using Fuzzy Inference Systems

Moradizadeh

Mayorga

2014

Proceedings of the International Conference on Fuzzy Computation Theory and Applications

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Increasingly, Intelligent Systems (IS) techniques are being used to solve both complex problems and industrial problems with uncertainty. They also can implement the operator's knowledge (experience) into the system. This Paper aims to improve and compute the well-known manufacturing metrics: the Overall Equipment Effectiveness (OEE), and Overall Line Efficiency (OLE), using IS techniques. The proposed methodologies to improve the OEE and OLE weakness are based on Fuzzy Inference Systems. These techniques result in an effective way to measure OEE and OLE considering different weight of losses and also the difference in machine's weight factors. Moreover, they allow the operator's knowledge to be taken into account in the measurement using uncertain input and output with implementation of linguistic terms.

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“…Information visualization for factory performance analysis helps the managers to effectively monitor the operations through reformulating complex issues into simple indicators [ 50 ], like equipment availability and product quality. Various techniques have been developed for analyzing collected manufacturing data, i.e., signals.…”

Section: Introductionmentioning

confidence: 99%

Smart Monitoring of Manufacturing Systems for Automated Decision-Making: A Multi-Method Framework

Cheng

Pourhejazy

Hung

et al. 2021

Sensors

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Smart monitoring plays a principal role in the intelligent automation of manufacturing systems. Advanced data collection technologies, like sensors, have been widely used to facilitate real-time data collection. Computationally efficient analysis of the operating systems, however, remains relatively underdeveloped and requires more attention. Inspired by the capabilities of signal analysis and information visualization, this study proposes a multi-method framework for the smart monitoring of manufacturing systems and intelligent decision-making. The proposed framework uses the machine signals collected by noninvasive sensors for processing. For this purpose, the signals are filtered and classified to facilitate the realization of the operational status and performance measures to advise the appropriate course of managerial actions considering the detected anomalies. Numerical experiments based on real data are used to show the practicability of the developed monitoring framework. Results are supportive of the accuracy of the method. Applications of the developed approach are worthwhile research topics to research in other manufacturing environments.

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Overall Equipment Effectiveness Measurement: Weighted Approach Method and Fuzzy Expert System

Cited by 7 publications

References 8 publications

Implementations of Autonomous Maintenance to Relieve Stoppages on PT NIKF – Sachet Packaging Chain

Implementations of Autonomous Maintenance to Relieve Stoppages on PT NIKF – Sachet Packaging Chain

Overall Equipment Effectiveness and Overall Line Efficiency Measurement using Fuzzy Inference Systems

Smart Monitoring of Manufacturing Systems for Automated Decision-Making: A Multi-Method Framework

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