Diagram Kendali Wilcoxon Triple Exponential Weighted Moving Average dengan IMFIR dalam Pengendalian Kualitas Produksi Celana PT. XYZ
Abstract
Abstract. Control diagrams are Statistical Process Control which are used to control the production process. In the case of control charts, there are parametric and non-parametric control charts. One of the SPCs is the EWMA control chart which is capable of detecting small shifts, assuming the data is normally distributed. Then the Wilcoxon EWMA nonparametric control diagram was proposed which can detect small shifts with data that is not normally distributed, then W EWMA was developed into Wilcoxon TEWMA so that it can detect smaller shifts by carrying out the shifting process three times. Control charts have a common problem, namely that shifts at the beginning of time are not quickly detected. To overcome this weakness, Fast Initial Response was implemented to increase sensitivity in the initial period, Letshedi et al. (2021) proposed this feature by developing FIR, becoming IMFIR which is able to produce better out of control performance than the previous feature. In this research, we apply the W TEWMA control chart with IMFIR to the waist circumference data of PT cargo pants production. XYZ. The results of the nonparametric Shewhart control diagram in phase I showed that there were no observation points that were outside the control limits. Next, in phase II, using the W TEWMA IMFIR control diagram with the values λ=0.5, L=2.937, f=0.5 and a=0.3, the W TEWMA control diagram with IMFIR is statistically uncontrolled.
Abstrak. Diagram kendali merupakan Statistic Process Control yang digunakan untuk mengontrol proses produksi. Pada kasus diagram kendali terdapat diagram kendali parametrik dan nonparametrik, Salah satu SPC yaitu diagram kendali EWMA yang mampu mendeteksi pergeseran yang kecil, dengan asumsi data berdistribusi normal. Kemudian diusulkanlah diagram kendali nonparametrik Wilcoxon EWMA yang dapat mendeteksi pergeseran kecil dengan data yang tidak berdistribusi normal, lalu W EWMA dikembangkan menjadi Wilcoxon TEWMA sehingga dapat mendeteksi pergeseran lebih kecil dengan melakukan proses pergeseran sebanyak tiga kali. Diagram kendali memiliki permasalahan umum yaitu pergeseran pada awal waktu tidak cepat terdeteksi. Untuk mengatasi kelemahan tersebut, diterapkanlah Fast Initial Response untuk meningkatkan kepekaan pada periode awal, Letshedi et al. (2021) mengusulkan fitur ini dengan mengembangkan FIR, menjadi IMFIR yang mampu menghasilkan kinerja out of control lebih baik dari fitur yang sebelumnya. Dalam penelitian ini menerapkan diagram kendali W TEWMA dengan IMFIR pada data panjang lingkar pinggang produksi celana cargo PT. XYZ. Hasil diagram kendali Shewhart nonparametrik pada fase I, diperoleh bahwa tidak ada titik pengamatan yang berada diluar batas kendali. Selanjutnya pada fase II, menggunakan diagram kendali W TEWMA IMFIR dengan nilai , , dan diperoleh diagram kendali W TEWMA dengan IMFIR tidak terkendali secara statistik.
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