scholarly journals Sistem Penghitung Nilai Efektivitas Mesin Forming Menggunakan Metode Overall Equipment Effectiveness

2020 ◽  
Vol 4 (2) ◽  
pp. 34-39
Author(s):  
Vernando Vernando ◽  
Indra Hardian Mulyadi
Keyword(s):  
Failure Mode ◽  
Effect Analysis ◽  
Data Output ◽  
World Class ◽  
Arduino Uno ◽  
Crystal Report ◽  
Limit Switch

Overall Equipment Effectiveness (OEE) adalah metode yang digunakan untuk menghitung nilai efektivitas dari sebuah mesin atau peralatan. Jika nilai OEE ≥ 85%, maka mesin dapat dikatakan efektif. Jika nilai OEE < 85%, maka mesin tidak efektif dan akan dilakukan analisis untuk mencari akar permasalahan, di antaranya menggunakan metode Failure Mode and Effect Analysis (FMEA). Penelitian ini bertujuan membuat sistem penghitung nilai efektivitas mesin forming menggunakan metode OEE. Limit switch dan Arduino UNO digunakan untuk mengambil data output dari mesin, seperti jumlah produksi, total durasi kerja mesin, dan total durasi mesin berhenti. Data diolah menggunakan Microsoft Visual Studio (C#) dan  disimpan dalam database sehingga dapat ditampilkan dalam bentuk laporan bulanan menggunakan Crystal Report. Pengujian lapangan sistem ini dilaksanakan untuk menghitung OEE pada mesin die form. Berdasarkan hasil dari pengujian tersebut, sistem penghitung ini berfungsi dengan baik dalam menghitung OEE mesin die form tersebut, yang dalam hal ini berada dalam kisaran 59,05% s.d 97,17% (efektivitas di bawah nilai World class standard).

scholarly journals ANALISIS PRODUKTIVITAS MESIN PERCETAKAN PERFECT BINDING DENGAN METODE OEE DAN FMEA

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Arif Rahman ◽  
Surya Perdana
Keyword(s):  
Failure Mode ◽  
Effect Analysis ◽  
World Class

Mesin Perfect Binding merupakan alat finishing untuk proses menjilid buku yang sering digunakan pada industri percetakan. Ketika berproduksi masalah yang sering muncul pada mesin Perfect Binding adalah downtime, breakdown, setup and adjustment yang mengakibatkan produktivitas hasil produksi berkurang. Tujuan dalam penelitian ini adalah untuk meningkatkan produktifitas dengan cara mengetahui hasil perhitungan Overall Equipment Effetiviness (OEE) pada mesin Perfect Binding dan mengetahui beberapa faktor yang menjadi penyebab menurunnya produktivitas hasil produksi dengan menggunakan diagram sebab akibat dan metode Failure Mode and Effect Analysis (FMEA) sehingga dapat dilakukan langkah-langkah perbaikan. Berdasarkan perhitungan Overall Equipment Effetiviness (OEE) pada Mesin Perfect Binding, periode April-Juni 2016 dibandingkan dengan periode April-Juni 2017, didapatkan hasil terjadi peningkatan di bulan April 2017 sebesar 2,24%, di bulan Mei 2017 sebesar 11,88%, dan di bulan Juni 2017 sebesar 4,53%. Secara umum pencapaian OEE meningkat tetapi belum mencapai kriteria World Class OEE. Rendahnya nilai OEE disebabkan oleh 4 faktor yaitu pengetahuan operator tentang mesin kurang (Manusia), temperatur lem tidak stabil (Mesin), vendor terlambat supply (Material), dan waktu ganti pisau tidak efisien (Metode).

scholarly journals Penerapan Efektivitas Mesin Debarker Menggunakan Overall Equipment Effectiveness (Studi pada PT. Tri Tunggal Laksana Unit Blitar)

2020 ◽  
Vol 6 (2) ◽  
pp. 12-17
Author(s):  
Sigit Dwi Cahyono ◽  
Fourry Handoko ◽  
Nelly Budiharti
Keyword(s):  
Failure Mode ◽  
Performance Ratio ◽  
Risk Priority Number ◽  
Total Productive Maintenance ◽  
Effect Analysis ◽  
Availability Ratio ◽  
World Class ◽  
Performance Rate

Total Productive Maintenance atau TPM adalah salah satu metode proses maintenance yang dikembangkan untuk meningkatkan produktifitas di area kerja, dengan cara membuat proses tersebut lebih reliable dan lebih sedikit terjadi pemborosan (waste). PT. Tri Tunggal Laksana menggunakan mesin debarker sebagai alat pemotong dan pengupas kulit kayu dalam memproduksi veneer. Selama periode produksi, mesin sering mengalami downtime sehingga mengganggu proses kerja produksi. Untuk itulah perusahaan perlu melakukan evaluasi atas mesin yang digunakan sehingga penerapan Total Productive Maintenance dapat dilaksanakan optimal demi meningkatkan efektivitas mesin produksi. Penelitian ini bertujuan menilai efektivitas mesin debarker menggunakan metode Overall Equipment Effectiveness (OEE). Hasilnya, semua faktor yang mempengaruhi nilai OEE berada dibawah standar dunia. Nilai availability ratio (89,78 % < 90,00%), performance ratio (87,97% < 95,00%), dan nilai quality ratio (91,43% < 99,90%). Nilai OEE mesin debarker sebesar 72,1% yang berarti masih berada di bawah world class standart yaitu sebesar 85%. Hasil analisis menunjukkan nilai performance rate yang rendah dipengaruhi oleh adanya komponen–komponen mesin yang kritis dan sering mengalami gangguan. Melalui Failure Mode and Effect Analysis (FMEA) diketahui bahwa komponen rantai conveyor dan mata pisau memiliki nilai Risk Priority Number (RPN) tertinggi sehingga komponen ini yang harus diutamakan dalam upaya meningkatkan efektivitas produksi.

Risk analysis of cutting system under intuitionistic fuzzy environment

2020 ◽  
Vol 1 (1) ◽  
pp. 162-173
Author(s):  
Dinesh Kumar Kushwaha ◽  
◽  
Dilbagh Panchal ◽  
Anish Sachdeva ◽  
◽  
...  
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Thermal Power ◽  
Failure Detection ◽  
Engineering System ◽  
Effect Analysis ◽  
Intuitionistic Fuzzy ◽  
Mode Effect ◽  
Cutting System ◽  
Failure Mode Effect Analysis

Failure Mode Effect Analysis (FMEA) is popular and versatile approach applicable to risk assessment and safety improvement of a repairable engineering system. This method encompasses various fields such as manufacturing, healthcare, paper mill, thermal power industry, software industry, services, security etc. in terms of its application. In general, FMEA is based on Risk Priority Number (RPN) score which is found by product of probability of Occurrence (O), Severity of failure (S) and Failure Detection (D). As human judgement is approximate in nature, the accuracy of data obtained from FMEA members depend on degree of subjectivity. The subjective knowledge of members not only contains uncertainty but hesitation too which in turn, affect the results. Fuzzy FMEA considers uncertainty and vagueness of the data/ information obtained from experts. In order to take into account, the hesitation of experts and vague concept, in the present work we propose integrated framework based on Intuitionistic Fuzzy- Failure Mode Effect Analysis (IF-FMEA) and IF-Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) techniques to rank the listed failure causes. Failure cause Fibrizer (FR) was found to be the most critical failure cause with RPN score 0.500. IF-TOPSIS has been implemented within IF-FMEA to compare and verify ranking results obtained by both the IF based approaches. The proposed method was presented with its application for examining the risk assessment of cutting system in sugar mill industry situated in western Uttar Pradesh province of India. The result would be useful for the plant maintenance manager to fix the best maintenance schedule for improving availability of cutting system.

scholarly journals Utility of Failure Mode and Effect Analysis to Improve Safety in Suctioning by Orotracheal Tube

2017 ◽  
Vol 32 (1) ◽  
pp. 28-37 ◽  
Author(s):  
Agustín Vázquez-Valencia ◽  
Andrés Santiago-Sáez ◽  
Bernardo Perea-Pérez ◽  
Elena Labajo-González ◽  
Maria Elena Albarrán-Juan
Keyword(s):  
Failure Mode ◽  
Effect Analysis ◽  
Orotracheal Tube

FMEA method in operational reliability of forest harvesters

2020 ◽  
Vol 11 (1) ◽  
pp. 29-38
Author(s):  
Ján Kováč ◽  
Pavol Ťavoda ◽  
Jozef Krilek ◽  
Pavol Harvánek
Keyword(s):  
Failure Mode ◽  
Working Conditions ◽  
Operational Reliability ◽  
Human Potential ◽  
Information Analysis ◽  
Effect Analysis ◽  
Operational Conditions ◽  
Its Analysis ◽  
Fmea Method ◽  
Operational Data

AbstractThe article deals with the research of operational reliability of forest felling machines by FMEA method (Failure Mode and Effect Analysis). It describes collection of operational data and its analysis. It explains the procedure of realization for the method FMEA in the organization. Harvesters John Deere 1070D in the Company Lesy SR B. Bystrica were chosen for this research. The research was held in real operational conditions. Application of the FMEA method allows flexibility in case of unexpected situations and optimization of human potential abilities. FMEA tool is a tool preventing outages operational reliability and preventive tool for ensuring the maintenance of facilities. The method of information analysis mentioned below is simple ale precise enough for implementation in real working conditions.

Failure mode and effect analysis (FMEA) to improve collaborative project-based learning: Case study of a Study and Research Path in mechanical engineering

2021 ◽  
pp. 030641902199904
Author(s):  
Elena Bartolomé ◽  
Paula Benítez
Keyword(s):  
Active Learning ◽  
Failure Mode ◽  
Mechanical Engineering ◽  
Failure Modes ◽  
Collaborative Study ◽  
Project Based Learning ◽  
Educational Process ◽  
Effect Analysis ◽  
Questions And Answers

Failure Mode and Effect Analysis (FMEA) is a powerful quality tool, widely used in industry, for the identification of failure modes, their effects and causes. In this work, we investigated the utility of FMEA in the education field to improve active learning processes. In our case study, the FMEA principles were adapted to assess the risk of failures in a Mechanical Engineering course on “Theory of Machines and Mechanisms” conducted through a project-based, collaborative “Study and Research Path (SRP)” methodology. The SRP is an active learning instruction format which is initiated by a generating question that leads to a sequence of derived questions and answers, and combines moments of study and inquiry. By applying the FMEA, the teaching team was able to identify the most critical failures of the process, and implement corrective actions to improve the SRP in the subsequent year. Thus, our work shows that FMEA represents a simple tool of risk assesment which can serve to identify criticality in educational process, and improve the quality of active learning.

Application of failure mode and effects analysis to reduce microplastic emissions

2021 ◽  
pp. 0734242X2110031
Author(s):  
Ana Pires ◽  
Paula Sobral
Keyword(s):  
Failure Mode ◽  
Quantitative Methods ◽  
Policy Instruments ◽  
Effect Analysis ◽  
Advantages And Disadvantages ◽  
Heuristic Technique ◽  
Single Use ◽  
Regulatory Measures ◽  
Plastic Products

A complete understanding of the occurrence of microplastics and the methods to eliminate their sources is an urgent necessity to minimize the pollution caused by microplastics. The use of plastics in any form releases microplastics to the environment. Existing policy instruments are insufficient to address microplastics pollution and regulatory measures have focussed only on the microbeads and single-use plastics. Fees on the use of plastic products may possibly reduce their usage, but effective management of plastic products at their end-of-life is lacking. Therefore, in this study, the microplastic–failure mode and effect analysis (MP–FMEA) methodology, which is a semi-qualitative approach capable of identifying the causes and proposing solutions for the issue of microplastics pollution, has been proposed. The innovative feature of MP–FMEA is that it has a pre-defined failure mode, that is, the release of microplastics to air, water and soil (depending on the process) or the occurrence of microplastics in the final product. Moreover, a theoretical recycling plant case study was used to demonstrate the advantages and disadvantages of this method. The results revealed that MP–FMEA is an easy and heuristic technique to understand the failure-effect-causes and solutions for reduction of microplastics and can be applied by researchers working in different domains apart from those relating to microplastics. Future studies can include the evaluation of the use of MP–FMEA methodology along with quantitative methods for effective reduction in the release of microplastics.

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