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Quality Control Analysis of Porcelain Products Using Overall Equipment Effectiveness and Statistical Quality Control Methods

Nurprihatin Filscha, Rembulan Glisina Dwinoor, Andry Johanes Fernandes, Immanuella Sarah, Widiwati Ivana Tita Bella

Management and Production Engineering Review

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2023

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Vol. 14, No. 3

134--147

EN

This study uses statistical quality control (SQC) and overall equipment effectiveness (OEE) to examine quality at a porcelain production firm. The study is motivated by the most frequently broken machines in 2019, is the Jigger 01 machine. This paper aims to evaluate the machine’s effectiveness using the OEE method. The OEE determines the scope of the problem to be solved using the SQC method. The average OEE value in 2019 was 70%. Based on the SQC method, the product defect produced is still under control. However, the average defect is still above the company’s tolerance limit of 10%. Consequently, this study offers enhancements utilizing the Failure Mode Effect Analysis (FMEA) technique. The results indicate that human resources and machines caused defective products. This paper contributes to providing several improvements that the company can apply to maximize its quality control analysis. After implementing the improvement, the OEE value increases to 74%.

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Integration of Overall Equipment Effectiveness and Six Sigma Approach to Minimize Product Defect and Machine Downtime

Nurprihatin Filscha, Rembulan Glisina Dwinoor, Andry Johanes Fernandes, Lubis Maulidina, Widiwati Ivana Tita Bella, Vaezi Ali

Management and Production Engineering Review

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2023

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Vol. 14, No. 4

71--91

EN

This study was conducted in a company that produces palm oil-based products such as cooking oil and margarine. The study aimed to encounter defects in packaging pouches. This study integrated the overall equipment effectiveness (OEE) with the six sigma DMAIC method. The OEE was performed to measure the efficiency of the machine. Three factors were measured in OEE: availability, performance, and quality. These factors were calculated and compared to the OEE world-class value. Then, the Multiple Linear Regression was performed using SPSS to determine the correlation between measurement variables toward the OEE value. Lastly, the six sigma method was implemented through the DMAIC approach to find the solution and improve the packaging quality. Supposing the recommendations are implemented, the OEE is expected to increase from 82% to 85%, with availability ratio, performance ratio, and quality ratio at, 99%, 86%, and 99.8%, respectively.

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Propaedeutic of the methodology of improving electromagnetic compatibility of railway traffic control systems in relation to the implementation of the EMC4CCS – BRIK project

Warzyński Tomasz, Sieczkarek Krzysztof, Maćkowiak Adam, Nagórny Bartłomiej, Szczepański Radosław, Rokossowski Michał

Pojazdy Szynowe

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2022

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Nr 1-2

86--89

EN

The purpose of this article is to introduce to the methodology of increasing electromagnetic compatibility in distributed system, on the example of the implementation of works in the field: "Research and improvement of electromagnetic compatibility of railway traffic control devices and rolling stock", which are the subject of the BRIK project. The methodology is defined here as a set of rules for conducting research in order to achieve an intended goal. The article proposes a procedure to improve the EMC condition of distributed systems. For monitoring the quality of the system operation in terms of electromagnetic compatibility, the implementation of the OEE indicator was suggested.

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Methodology of overall equipment effectiveness calculation in the context of Industry 4.0 environment

Aleš Zdeněk, Pavlů Jindřich, Legát Václav, Mošna František, Jurča Vladimír

Eksploatacja i Niezawodność

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2019

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Vol. 21, no. 3

411--418

EN

Industry 4.0 and related Maintenance 4.0 demand higher requirement for productivity and maintenance effectiveness. Nakajim’s OEE indicator still plays an important role in measuring effectiveness of production and maintenance. In connection with the current Industry 4.0 challenge, the issue of Industrial Internet of Things (IIoT) is highly accentuated. This topic includes the matter of autonomous management and communication of individual machines and equipment within higher and more complex production units. Authors propose original calculations OEE for the whole production line from OEE knowledge and individual machines, including knowledge of their nominal and actual performance. The presented solution allows a greater depth of analysis of machine efficiency and overall effectiveness calculation of different assembled production lines based on knowledge of individual machines efficiencies.

PL

Industry 4.0 i związana z nią strategia Maintenance 4.0 stawiają wyższe wymagania odnośnie wydajności produkcji i utrzymania ruchu. Wskaźnik ogólnej efektywności urządzeń (OEE) Nakajimy nadal odgrywa ważną rolę w pomiarach efektywności produkcji i utrzymania ruchu. W związku z wyzwaniami stawianymi obecnie przez Industry 4.0, dużą uwagę zwraca się na koncepcję Przemysłowego Internetu Rzeczy. Obejmuje ona kwestię autonomicznego zarządzania i komunikacji pomiędzy poszczególnymi maszynami i urządzeniami w bardziej złożonych jednostkach produkcyjnych wyższego stopnia. Autorzy niniejszej pracy proponują oryginalną metodę obliczania OEE dla całej linii produkcyjnej na podstawie znajomości ogólnej efektywności urządzeń oraz efektywności pojedynczych maszyn, w tym wiedzy o ich nominalnej i rzeczywistej wydajności. Przedstawione rozwiązanie pozwala na głębszą analizę wydajności maszyn oraz obliczanie ogólnej efektywności różnych linii produkcyjnych w oparciu o wiedzę na temat wydajności poszczególnych maszyn.

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Modelling and Simulation Method for Production Process Automation in Steel Casting Foundry

Kampa A., Gołda G.

Archives of Foundry Engineering

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2018

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Vol. 18, iss. 1

47--52

EN

The problem of production flow in steel casting foundry is analysed in this paper. Because of increased demand and market competition, a reorganisation of the foundry process is required, including the elimination of manual labour and the implementation of automation and robotisation of certain processes. The problem is how to determine the real difference in work efficiency between human workers and robots. We show an analysis of the production efficiency of steel casting foundry operated by either human operators or industrial robots. This is a problem from the field of Operations Research for which the Discrete Event Simulation (DES) method is used. Three models are developed, including the foundry before and after automation when taking into consideration parameters of the availability of machines, operators and robots. We apply the OEE (Overall Equipment Effectiveness) indicator to present how the availability, performance and quality parameters influence the foundry’s productivity. In addition, stability of the simulation model was analysed. This approach allows for a better representation of real production processes and the obtained results can be used for further economic analysis.