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"Small Soekardie ceramic industries is located in the center of Betek ceramic Penanggungan village of Malang city government, it is one of ceramic center in Malang City, based on Lukman research in 2005 the resulth of SPC is an indicator of process cabability index Cp, the value of Cp at that center area of the vallue of process capability index cp registration is 0.000000801848 so an improvement step of prodsuction process must be done, to increase quality of ceramic product...."

"PT. X adalah sebuah perusahaan industri manufaktur yang bergerak dalam bidang pembuatan kemasan industri dengan sistem proses berdasarkan pesanan (job order), dimana desain produk ditentukan oleh konsumen eksternal (external customers). Produk yang dihasilkan terbagi atas 2 jenis, Kemas Bentuk (Fine Flexible Packaging) yaitu kemasan jadi yang masih dalam bentuk gulungan atau rol untuk diproses lanjut oleh konsumen yang bersangkutan dan Pengemasan (Packaging) yaitu kemasan jadi yang telah berbentuk kantong (bag). Kualitas memiliki peranan penting dalam proses produksi, karena berhubungan dengan fungsi produk yang dihasilkan dan kepuasan konsumen yang memakainya. Proses merupakan integrasi sekuensial dari orang (manusia), material, metode dan mesin atau peralatan, dalam suatu lingkungan yang bekerja sama guna menghasilkan nilai tambah output (produk), dan berkualitas yang selanjutnya diserahkan kepada konsumen agar memenuhi kebutuhan dan ekspektasi dari konsumen itu. Proses juga merupakan sekumpulan kondisi yang berbeda-beda, akan menghasilkan unit produk yang berbeda pula, yang tentunya akan menimbulkan adanya variasi atau keragaman pada produk yang dihasilkan sehingga perlu dilakukan pencegahan melalui pengendalian proses. Suatu proses dikatakan beroperasi dalam pengendalian statistikal apabila variasi-variasi yang timbul hanya bersumber dari variasi penyebab umum. Metode pengendalian proses secara statistik merupakan salah satu pendekatan agar proses berada dalam pengendalian secara statistikal melalui catatan data yang secara terus-menerus dikumpulkan dan dianalisis agar menghasilkan informasi yang dapat digunakan dalam mengendalikan dan meningkatkan proses sehingga proses itu memiliki kemampuan untuk memenuhi spesitikasi output yang diinginkan konsumen. Kemampuan ini disebut dengan kapabilitas proses. Analisa kapabilitas proses dan mesin merupakan salah satu analisa kualitas proses, yaitu untuk menentukan kapabilitas proses dan merupakan suatu cara untuk mengetahui dan mengukur kemampuan proses dan mesin dengan membandingkannya terhadap toleransi yang ditentukan oleh spesifikasi. Analisa kapabilitas proses dilakukan pada proses pelapisan (laminasi) pada mesin extrution laminating. Dari hasil pengumpulan dan pengolahan data yang dilakukan memperlihatkan bahwa hampir seluruh data tidak berada dalam kendali secara statistik, kecuali proses untuk jenis laminasi ukuran 351.1 kerataan (berat) gramatur dan kerataan ketebalan (thickness). Demikian juga hasil perhitungan dan analisa terhadap kapabilitas proses, memperlihatkan bahwa hampir seluruh proses tidak mampu untuk menghasilkan unit produk yang memenuhi batas toleransi spesifikasi yang ditetapkan, kecuali proses untuk jenis laminasi ukuran 351.1 kerataan gramatur. Dari kondisi tersebut maka perlu dilakukan pengecekan dan bahkan perbaikan terhadap proses agar dicapai proses terkendali secara statistik dan mampu manghasilkan output (produk) yang memenuhi batas spesikasi yang ditentukan sebelumnya."

"Persaingan dunia usaha saat ini semakin kompetitif. Semua perusahaan khususnya bidang manufaktur, berusaha untuk memberikan yang terbaik bagi konsumennya dengan produk yang berkualitas yang baik serta delivery time yang tepat. Oleh karena itu, setiap perusahaan manufaktur harus pintar menyiasati dan menerapkan strategi yang tepat dalam mendukung proses produksinya. Di sini akan dibahas mengenai salah satu strategi TPM (Total Productive Maintenance) yang secara signifikan bisa membuat proses produksi menjadi lebih baik dalam hal peralatan, pengiriman produk dan tingkat cacat produk. Penerapan yang benar dari strategi TPM ini dapat meningkatkan kinerja produksi sehingga kelangsungan hidup sebuah perusahaan manufaktur dapat terus terjaga. Dalam penelitian ini digunakan metode pengukuran OEE, regresi majemuk dan korelasi, FMEA, dan SPC untuk mengetahui dan menyelesaikan permasalahan yang terjadi tersebut. Hasil penelitian ini didapatkan bahwa equipment losses adalah salah satu penyebab tertinggi dari rendahnya nilai OEE dan availability ratio.

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Competition world of today's increasingly competitive business. All companies, especially in manufacturing, seeks to provide the best for its customers with products of good quality and appropriate delivery time. Therefore, every smart manufacturing companies must deal with and implement the right strategies in support of the production process. Here will be discussed on one of the strategies TPM (Total Productive Maintenance) which significantly could make the production process for the better in terms of equipment, product delivery and product defect rates.

The correct application of the TPM strategy can improve the performance of production so that the survival of a manufacturing company can be maintained. This study used methods by measuring OEE, multiple regression and correlation, and FMEA to identify and resolve these problems occurred. The results of this study found that the equipment losses are one of the highest causes of the low value of OEE and availability ratio."

"The moisture content of cut tobacco in Tobacco industry affects directly the quality of tobacco. To prevent the abnormal changes of the moisture content of cut tobacco, effective surveillance systems would be extremely helpful to give out-of-control (OC) signals as quickly as possible. The conventional statistical process control charts are not suitable to use due to complex structures, such as semiparametric trend, within-batch correlation in the moisture content data. In this paper, we propose a four-step procedure in which Semiparametric longitudinal model, time series analysis methods and normal transformation methods are utilized to eliminate the impact of the complex structures. And our procedure is demonstrated using the moisture content data of cut tobacco at the outlet (MCCTO) collected in Shanghai tobacco group co., Ltd of China. The results show that our procedure is effective in detecting the abnormal changes of the MCCTO data."

"Recently, a varied L ranked set sampling (VLRSS) scheme has been introduced in the literature for estimating the population mean. The VLRSS scheme is a cost-efficient alternative to the classical ranked-set sampling (RSS) and median RSS (MRSS) schemes. In this paper, we construct a new cumulative sum (CUSUM) control chart for efficiently monitoring the process mean using VLRSS, named the CUSUM-VLRSS chart. The CUSUM-VLRSS chart encompasses the existing CUSUM charts based on RSS and MRSS schemes, named the CUSUM-RSS and CUSUM-MRSS charts. We use extensive Monte Carlo simulations to compute the run length characteristics of the proposed CUSUM chart. It is shown that the CUSUM-VLRSS chart is able to perform uniformly better than the CUSUM-RSS and CUSUM-MRSS charts when detecting different kinds of shift in the process mean. A similar trend is observed when the proposed CUSUM chart is constructed under imperfect rankings. A real data-set is also used to explain the implementation of the CUSUM-VLRSS chart. "

"ABSTRACTCount data are often described by the Poisson distribution, which requires identical mean and variance, namely equi dispersion. However, in practical situations, count data usually exhibit either over dispersion with variance larger than mean, or under dispersion with variance smaller than mean. Therefore, traditional approaches that focus on only mean shifts, such as the c chart, cannot monitor count data with over/under dispersion efficiently.To monitor mean and dispersion of count data simultaneously, this paper adopts Conway MaxwelI Poisson (COMPoisson) distributions to ht count data with over/under dispersion, and constructs a control chart based on the likelihood ratio test. The proposed chart is powerful in detecting both mean and dispersion shifts of count data with either over dispersion or under dispersion. Numerical simulations have demonstrated its performance in various cases."

"ABSTRACTThis research work assesses quality-related problem in Ethiopian garment enterprises in order to develop an applicable quality improvement model to improve the overall performance of the sector. A sample of 11 garment enterprises was taken considering the unexpected response rate, requirements for performing statistical analysis, available time, and survey cost. Primary and secondary data were collected and analyzed to identify quality-related problems of the sector using a well-structured questionnaire, interviews, personal observations, and review of previous works. The study performs a preliminary gap analysis is made by considering a case study to investigate the quality associated costs and apply SQC tools to identify the potential areas of improvements. Then, a quality improvement model is developed along with primary steps to implement the model to improve the competitiveness of the sector."

"This book discusses the integrated concepts of statistical quality engineering and management tools. It will help readers to understand and apply the concepts of quality through project management and technical analysis, using statistical methods. Prepared in a ready-to-use form, the text will equip practitioners to implement the Six Sigma principles in projects. The concepts discussed are all critically assessed and explained, allowing them to be practically applied in managerial decision-making, and in each chapter, the objectives and connections to the rest of the work are clearly illustrated.To aid in understanding, the book includes a wealth of tables, graphs, descriptions and checklists, as well as charts and plots, worked-out examples and exercises. Perhaps the most unique feature of the book is its approach, using statistical tools, to explain the science behind Six Sigma project management and integrated in engineering concepts. The material on quality engineering and statistical management tools offers valuable support for undergraduate, postgraduate and research students. The book can also serve as a concise guide for Six Sigma professionals, Green Belt, Black Belt and Master Black Belt trainers."

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Penyakit COVID-19 yang ditetapkan WHO sebagai pandemi global telah mengubah tatanan kehidupan banyak orang. Berbagai macam kebijakan ditetapkan oleh pemerintah setempat untuk menekan angka penularan COVID-19 antar penduduk, salah satunya dengan menerapkan pembatasan kegiatan. DKI Jakarta yang merupakan Ibukota Negara Republik Indonesia juga menerapkan kebijakan pembatasan kegiatan, mulai dari PSBB hingga PPKM Level 1. Tujuan penelitian ini adalah untuk menganalisis pergerakan grafik penambahan kasus positif COVID-19 dan penambahan kasus meninggal akibat COVID-19 di Provinsi DKI Jakarta dalam setiap penerapan kebijakan pembatasan kegiatan yang ditetapkan Pemprov DKI Jakarta. Metode yang digunakan adalah Statistical Process Control (SPC), yaitu teknik statistika yang dapat digunakan untuk memonitor terjadinya sebuah proses. Salah satu tools dalam SPC yang umum digunakan adalah bagan kendali (control chart). Bagan kendali yang digunakan dalam penelitian ini adalah bagan kendali  untuk memonitor rata-rata dan variabilitas suatu proses. Data yang digunakan adalah penambahan kasus positif COVID-19 dan penambahan kasus meninggal akibat COVID-19 di Provinsi DKI Jakarta yang diambil mulai tanggal 18 Maret 2020 hingga 16 November 2021 melalui website Kemenkes RI. Data tersebut terdiri dari 609 pengamatan penambahan kasus positif dan 609 pengamatan penambahan kasus meninggal yang kemudian dibentuk ke dalam 87 subgrup dengan masing-masing subgrup terdiri dari 7 pengamatan. Berdasarkan hasil analisis, puncak penambahan kasus positif COVID-19 dan penambahan kasus meninggal akibat COVID-19 di DKI Jakarta terjadi pada bulan Juli 2021. Selain itu, hasil analisis menunjukkan saat pembatasan kegiatan dilonggarkan oleh Pemprov DKI Jakarta, yaitu pada masa PSBB Transisi, PSBB Transisi Jilid II, dan PPKM Mikro, penambahan kasus positif dan meninggal di minggu-minggu akhir kebijakan tersebut, nilai pada bagan kendali   yang terbentuk berada di atas Upper Control Limit.

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Corona Virus Disease 2019 (COVID-19), which has been designated by WHO as global pandemic, has changed the way of life many people. Various of policies have been set by local government to reduce the transmission of COVID-19 in public. One of them is activity restrictions. DKI Jakarta, capital of Indonesia, also implementing the activity restrictions, start from PSBB to PPKM Level 1. The purpose of this research was to analyze the movement of the graphs of additional of positive COVID-19 cases and additional of death due to COVID-19 cases in DKI Jakarta Province, at each implementation of activity restriction policy set by DKI Jakarta provincial government. The method used is Statistical Process Control (SPC), a statistical technique that can be used to monitor process. One of the tools in SPC commonly used is control chart. The control chart used in this research is  control chart to monitor the mean and variability of a process. The data used is additional of positive COVID-19 cases and additional of death due COVID-19 cases in DKI Jakarta Province which were taken from March 18, 2020 to November 16, 2021 through Indonesian Ministry of Health website. Data consist of 609 observations of additional positive cases and 609 additional death cases and then formed into 87 subgroups with each subgroups consist of 7 observations. Based on the results of the analysis, the peak of additional positive COVID-19 cases and additional death due to COVID-19 cases in DKI Jakarta occurred in July 2021. Moreover, the results of the analysis show that when activity restrictions were relaxed by the DKI Jakarta Provincial Government, during the PSBB Transisi, PSBB Transisi Jilid II, and PPKM Mikro, the additional of positive cases and deaths about last weeks of the policy, the value on  control chart formed is above the Upper Control Limit (UCL).                 

 

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