scholarly journals Analisis Pengendalian Kualitas Crude Palm Oil (CPO) PT. Kampar Tunggal Agrindo Dengan Menggunakan Statistical Process Control

2022 ◽  
Vol 8 (2) ◽  
pp. 327-332
Author(s):  
Denny astrie Anggraini
Keyword(s):  
Process Control ◽  
Statistical Process Control ◽  
Palm Oil ◽  
Material Handling ◽  
Crude Palm Oil ◽  
Statistical Process

Kampar Tunggal Agrindo merupakan perusahaan yang bergerak dibidang Pabrik Kelapa Sawit berskala 15 T/H berasal dari Kabupaten Kampar mengolah buah brondolan sawit menjadi minyak mentah (crude palm oil). Perusahaan ini mengalami ketidaksesuaian standart hasil produksi yang ditetapkan oleh perusahaan, dengan standar kadar asam < 30%, kadar air <0,50%, kadar kotoran <0,030%. Maka dari itu dibutuhkan analisis menggunakan metode statistical process control. Dari 3 parameter analisis ketidaksesuaian standart produk crude palm oil (CPO), diparamater kadar asam dan kadar air ada beberapa data yang out of control yang berarti tidak terkendali dan harus dilakukan analisis lebih lanjut. Dari 3 parameter kualitas produk CPO, maka yang menjadi prioritas untuk diperbaiki adalah parameter kadar air. Akar penyebab dari tingginya kadar air (> 0,50%) adalah manusia antara lain kurangnya inspeksi pada waktu perebusan akibatnya tekanan steam uap berlebihan sehingga suhu terlalu panas akibat kurang komunikasi antara operator boiler dan perebusan. Untuk itu perlu dilakukan pengawasan SOP dari pihak kepala produksi terhadap operator, penambahan unit material handling berupa loader dan merancang checklist preventif untuk mencegah kerusakan.      

scholarly journals PEMODELAN KERANGKA ADAPTIVE THRESHOLD UNTUK MEMONITOR PRODUKSI MINYAK SAWIT NASIONAL BERBASIS STATISTICAL PROCESS CONTROL DAN ARTIFICIAL NEURAL NETWORK-BACKPROPAGATION

2016 ◽  
Vol 11 (2) ◽  
pp. 113-122
Author(s):  
Wahyu Widji Pamungkas ◽  
Syamsul Maarif ◽  
Tun Tedja Irawadi ◽  
Yandra Arkeman
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Process Control ◽  
Statistical Process Control ◽  
Palm Oil ◽  
Historical Data ◽  
Adaptive Threshold ◽  
The Other ◽  
Production Volume ◽  
Statistical Process

Indonesia is the largest exporter of palm oil in the world, as the largest producer Indonesia still havemany problems. The problem caused by incomparable between the growth of upstream and downstreampalm oil industries. This impact to low added value of palm oil, then Indonesia exports palm oil in crudeform. On the other hand, On the other hand , orientation export of this commodity is also prone of barrier,because Indonesia was not the price setter of this commodity in the international market. Therefore it isimportant to monitor and predict the development of national palm oil production volume in order to takegood anticipation. This research develop a framework model adaptive threshold to monitor the growing ofnational palm oil production volume with techniques of statistical process control (SPC) and back propagationartificial neural network (ANN - BP) methods. Historical data production volume period from 1967 to 2015was used as a base of the behavior as data to determine the threshold and prediction volume for nextperiods. The formation of the threshold value was based on the behavior of the historical data, which areoriented by the epicenter of the average value in the last two periods .Through mapping of data historicalperiod values, existing and forecast values with adaptive threshold can show tolerant level for the threshold.Furthermore, based on the analysis, it is known that the prediction of 2016 to 2018 period, there will behappen the dynamics production volume of national palm oil within tolerance threshold. The values of thesepredictions generated from the simulation model predictions of ANN-BP with the level very good of validationmodel, demonstrated the level of squared errors is very small1 in the MSE = 0.00021136 with a degree ofoutput correlation and the target is very strong2 with R Validation is 99.98 percent.Keywords: adaptive threshold, statistical process control, artificial neural network, national palm oilproduction.

APPLICATION OF SPC AND GROWTH MODELS ON THE ECONOMIC TRAJECTORY OF THE LEATHER AND FOOTWEAR INDUSTRY

2020 ◽  
Author(s):  
Mario Lesina ◽  
Lovorka Gotal Dmitrovic
Keyword(s):  
Human Capital ◽  
Process Control ◽  
Statistical Process Control ◽  
Control Charts ◽  
Growth Models ◽  
Pearson Correlation ◽  
Small Companies ◽  
Statistical Process ◽  
Production Staff ◽  
Footwear Industry

The paper shows the relation among the number of small, medium and large companies in the leather and footwear industry in Croatia, as well as the relation among the number of their employees by means of the Spearman and Pearson correlation coefficient. The data were collected during 21 years. The warning zone and the risk zone were determined by means of the Statistical Process Control (SPC) for a certain number of small, medium and large companies in the leather and footwear industry in Croatia. Growth models, based on externalities, models based on research and development and the AK models were applied for the analysis of the obtained research results. The paper shows using the correlation coefficients that The relation between the number of large companies and their number of employees is the strongest, i.e. large companies have the best structured work places. The relation between the number of medium companies and the number of their employees is a bit weaker, while there is no relation in small companies. This is best described by growth models based on externalities, in which growth generates the increase in human capital, i.e. the growth of the level of knowledge and skills in the entire economy, but also deductively in companies on microeconomic level. These models also recognize the limit of accumulated knowledge after which growth may be expected. The absence of growth in small companies results from an insufficient level of human capital and failure to reach its limit level which could generate growth. According to Statistical Process Control (SPC), control charts, as well as regression models, it is clear that the most cost-effective investment is the investment into medium companies. The paper demonstrates the disadvantages in small, medium and large companies in the leather and footwear industry in Croatia. Small companies often emerge too quickly and disappear too easily owing to the employment of administrative staff instead of professional production staff. As the models emphasize, companies need to invest into their employees and employ good production staff. Investment and support to the medium companies not only strengthens the companies which have a well-arranged technological process and a good systematization of work places, but this also helps large companies, as there is a strong correlation between the number of medium and large companies.

Sign in / Sign up

Export Citation Format

Share Document