Schedule Planning and Maintenance Activities Auxiliary Power Unit (APU) Boeing 737-500 Aircraft With Reliability Method

Penelitian ini bertujuan untuk merencanakan jadwal dan aktifitas maintenance yang yangefektif pada sistem auxiliary power unit sehingga tidak terjadi lagi kegagalan ataupun kerusakan yang tidak di rencanakan atau terjadi secara tiba – tiba. Kegagalan pada peralatan auxiliary power unit ada sering terjadi pada beberapa sistem kerja yaitu electrical system, Lubrication System dan Ignition System, di mana hal ini menimbulkan kerugian yang cukup besar bagi perusahaan penerbangan. Metode penelitian ini menggunakan pendekatan kualitatif dan kuantitatif, analisis kualitatif menggunakan metode Failure Mode Effect and Critically Analysis (FMECA) dengan menganalisis faktor – faktor penyebab kegagalan dan efek terjadinya kegagalan, dengan hasil penyebab kegagalan pada beberapa sitem kerja auxiliary power unit (APU) adalah sebagai berikut electrical system adalah pada komponen start Relay, Lubrication System adalah pada komponen Oil Filter, Ignition System adalah pada igniter plug. Dari hasil analisis FMECA tersebut di lakukan analisis kuantitatif dengan analisis dilakukan menggunakan metode reliability, parameter kehandalan dihitung dengan probabilitas distribusi Weibull, untuk menentukan batas kritis waktu operasional komponen ataupun part sistem yang merupakan batas kehandalan suatu sistem auxiliary power unit. Batas kritis operasional electrical system adalah sebesar 434 jam terbang, lubrication system adalah 1186 jam terbang, dan Ignition system adalah sebesar 1610 jam terbang, selanjutnya hasil tersebut di gunakan untuk menentukan jadwal maintenance yang efektif di dukung dengan perencanaan aktifitas maintenance yang tepat untuk menghilangkan penyebab – penyebab kegagalan pada peralalatan auxiliary power unit.

Machine Optimization of SNK HF Fabrication Plant in PT. Komatsu Indonesia with FMEA Method and Overall Equipment Effectiveness (OEE)

The effectiveness of a machine is an important thing in the production process; the losses that arise can cause time losses and hamper the process, especially in vital production facilities. The SNK HF machine is a machine with category A or critical with the highest damage occurring throughout 2019–2020. Analysis of the condition of the machine’s effectiveness in this study was done by using the overall equipment effectiveness (OEE) method, namely by knowing the conditions of availability, performance and quality. The results of the OEE analysis are followed by a failure mode effect analysis (FMEA) to overcome the problems that occur. The condition of machine damage and the availability of machine parts are the factors that most affect the decrease in the effectiveness of the SNK HF machine.

Risk and DoE-Based Analytical Failure Mode Effect Analysis (AFMEA) to Simultaneous Estimation of Montelukast Sodium and Bilastine by HPTLC Method Using Enhanced AQbD Approach

The fixed-dose combination (FDC) of montelukast sodium (MLS) and bilastine (BIL) is used for monotherapy in the patient with seasonal allergic rhinoconjuctivitis and asthma. According to the upcoming ICH (International Council for Harmonization) Q14 guideline, the development of the analytical method by the implementation of the Analytical Quality by Design (AQbD) approach based on principles of Quality Risk Management (QRM) and design of experiments (DoE) would be a regulatory requirement for the registration of new drug substance and product in ICH countries. Hence, a robust high-performance thin layer chromatography method has been developed, which was not previously reported for simultaneous estimation of MLS and BIL using risk and DoE-based enhanced AQbD approach. The analytical failure mode effect analysis (AFMEA) was started with the identification of potential analytical failure modes followed by their effect analysis by RPN ranking and filtering method. The DoE-based AFMEA was applied for optimization of high-risk analytical failure modes by central composite design using Design-Expert software. The method operable design ranges and control strategy was set for quality risk management throughout the lifecycle of the developed method. The developed method was validated as per ICH Q2 (R1) guideline. The method was applied for the assay of FDC, and results were found in compliance with the labeled claim.

Perbaikan Proses Delivery Dokumen Maintenance C-Check Pesawat dengan Metode CCFE, FMEA, dan PICA (Studi Kasus di PT. GMF Aeroasia Tbk.)

PT. GMF Aeroasia, Tbk is a company engaged in aircraft maintenance services. The aircraft maintenance lead time is regulated according to the agreement set forth in the agreement in the form of a work order, when the maintenance process takes place there is almost always a delay when working on the aircraft, both in terms of physical work or delivery of documents. These problems are several forms of waste, where waste is any activity that does not provide added value. Therefore, the purpose of this study is to identify the type of waste and determine the factors that cause waste in the delivery process of aircraft c-check maintenance documents. The method used in this study used a fishbone chart, cause failure mode effect, failure mode and effects analysis and problem identification and corrective action. Fishbone chart and cause failure mode effect are used to find waste that causes delay in document delivery, then analyzed using failure mode and effects analysis, three causes of the highest delay were found, namely stamps on incomplete documents (RPN 16), waiting for customer approval (RPN 16) and material certificates not available (RPN 12). Corrective Action was prepared as a recommendation to improve the delivery process for aircraft c-check maintenance documents. By knowing the types of waste and the factors causing waste in the delivery process of aircraft c-check maintenance documents at PT. GMF Aeroasia Tbk is expected to reduce waste and fulfill customer satisfaction. Keywords: Lead Time, Waste, Delay Delivery of Documents, Cause Failure Mode Effect Method, Corrective Action

Evaluasi Proses Bisnis Layanan Identitas Penduduk Menggunakan Quality Evaluation Framework (QEF) (Studi Kasus: Dinas Kependudukan dan Pencatatan Sipil Kabupaten Bekasi)

Dinas Kependudukan dan Pencatatan Sipil Kabupaten Bekasi mengakomodasi beberapa pelayanan dalam dokumen identitas kependudukan pada seksi identitas penduduknya. Seksi identitas penduduk menjalani tiga layanan yaitu, perekaman KTP elektronik, penerbitan surat keterangan identitas penduduk, dan penerbitan KTP elektronik. Dalam eksekusinya, proses bisnis layanan kerap terjadi ketidaksesuaian dengan target organisasi sehingga perlu adanya evaluasi. Langkah yang dilakukan untuk mengevaluasi dimulai dengan memodelkan proses bisnis menggunakan Business Process Model and Notation (BPMN), kemudian memetakan quality factor dan menentukan target serta kalkuasi sesuai dengan rumus yang ada menggunakan metode Quality Evaluation Framework (QEF) untuk mengetahui aktivitas yang mengalami ketidaksesuaian. Setelah itu, aktivitas yang mengalami ketidaksesuaian akan diidentifikasi permasalahannya menggunakan metode Failure Mode Effect Analysis (FMEA) agar dapat diketahui tingkat prioritas yang perlu menjadi perhatian utama melalui nilai Risk Priority Number (RPN). Selanjutnya digunakan analisa tulang ikan agar diketahui akar permasalahannya. Hasil dari akar permasalahan menunjukkan quality factor yang berkode Q1, Q4, dan Q8 dengan RPN 120 memiliki akar permasalahan dari aspek kategori mesin dan teknologi, pengukuran, serta metode. Sedangkan untuk quality factor berkode Q2, Q5, dan Q9 dengan RPN 36 memiliki akar permasalahan dari aspek kategori mesin dan teknologi serta material.

Implementation of Six Sigma to Minimize Reject Gusset Difference and Fold in the Blowing Process

PT. Elastis Reka Aktif including companies engaged in manufacturing made from rHDPE (recycling High Density Polyethylene). The problem that often occurs is that the achievement of the Not Good Key Point Indicator exceeds the tolerance given by management by 1%. Therefore, improvements were made using the Six Sigma method and the Failure Mode Effect Analysis method in order to get the priority of improvement targets. The first improvement proposal given to the company is for RPN 280, namely the material characteristics are not homogeneous by proposing a re-design of the silo which is in the pelletizing process and the fourth is RPN 252 where the roll takeup and winder positions are not parallel, namely by providing area boundaries in order to minimize the position not being aligned. parallel. After providing a proposal for each potential problem and socializing it to the production side, it is hoped that it can reduce the reject rate in the blowing process.

Assessing and Adjusting Bias Due to Mixed-Mode in Aspect of Daily Life Survey

The mixed-mode (MM) designs are adopted by NSIs both to contrast declining response and coverage rates and to reduce the cost of the surveys. However, MM introduces several issues that must be addressed both at the design phase, by defining the best collection instruments to contain the measurement error, and at the estimation phase, by assessing and adjusting the mode effect. In the MM surveys, the mode effect refers to the introduction of bias effects on the estimate of the parameters of interest due to the difference in the selection and measurement errors specific to each mode. The switching of a survey from single to mixed-mode is a delicate operation: the accuracy of the estimates must be ensured in order to preserve their consistency and comparability over time. This work focuses on the methods chosen for the evaluation of the mode effect in the Italian National Institute of Statistics (ISTAT) mixed-mode survey “Aspects of Daily Life – 2017”, in the experimental context for which an independent control single-mode (SM) PAPI sample was planned to assess the introduction of the sequential web/PAPI survey. The presented methods aim to analyze the causes that can determine significant differences in the estimates obtained with the SM and MM surveys.