Spatial GHG Inventory: Analysis of Uncertainty Sources. A Case Study for Ukraine

2007 ◽  
pp. 63-74 ◽  
Author(s):  
R. Bun ◽  
M. Gusti ◽  
L. Kujii ◽  
O. Tokar ◽  
Y. Tsybrivskyy ◽  
...  
Keyword(s):  
Inventory Analysis ◽  
Uncertainty Sources

Spatial GHG Inventory: Analysis of Uncertainty Sources. A Case Study for Ukraine

2007 ◽  
Vol 7 (4-5) ◽  
pp. 483-494 ◽  
Author(s):  
R. Bun ◽  
M. Gusti ◽  
L. Kujii ◽  
O. Tokar ◽  
Y. Tsybrivskyy ◽  
...  
Keyword(s):  
Inventory Analysis ◽  
Uncertainty Sources

scholarly journals Analisis Persediaan Karton dengan Metode Economic Order Quantity (EOQ) (Studi Kasus: PT. Asegar Murni Jaya, Minahasa Utara)

2021 ◽  
Vol 21 (2) ◽  
pp. 170
Author(s):  
Therechia A.F. Soares ◽  
Chriestie E.J.C. Montolalu ◽  
Tohap Manurung
Keyword(s):  
Mineral Water ◽  
Raw Materials ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Inventory Analysis ◽  
Inventory Costs ◽  
Holding Cost ◽  
Materials Used

Karton merupakan salah satu bahan baku pembantu yang digunakan dalam produksi Air Mineral dalam Kemasan. Menurut beberapa penelitian Metode EOQ digunakan untuk menganalisa persediaan. Tujuan penelitian ini yaitu untuk menentukan jumlah pemesanan ekonomis menggunakan metode Economic Order Quantity (EOQ) dan pengoptimalan biaya yang dapat dilakukan dengan metode EOQ.  Penelitian ini dilakukan pada bulan November 2019 hingga Januari 2020 di perusahaan PT. Asegar Murni Jaya. Variabel yang digunakan yaitu frekuensi kebutuhan karton, biaya pemesanan bahan baku dan biaya penyimpanan bahan baku.  Hasilnya menunjukkan bahwa pemesanan ekonomis menurut metode EOQ untuk karton dengan biaya optimal sebesar  unit untuk periode November 2017 – Oktober 2018 dan unit untuk periode November 2018 – Oktober 2019. Terjadi penghematan dalam biaya persediaan untuk periode November 2017 – Oktober 2018 sebesar  dan untuk periode November 2018 – Oktober 2019 sebesar .Kata kunci: Economic Order Quantity;  karton;  persediaan Carton Inventory Analysis Using the Economic Order Quantity (EOQ) Method (Case Study: PT. Asegar Murni Jaya, Minahasa Utara)ABSTRACTCarton is one of the supporting raw materials used in the production of bottled  or glass mineral water. Based on some research, for analyzed inventory will be used  Economic Order Quantity (EOQ) Method. The purpose of this research was to determine the amount of economic order using Economic Order Quantity (EOQ). This research was conducted in November 2019 until January 2020 at PT. Asegar Murni Jaya. Variables used i.e the frequency of carton demand, ordering cost and holding cost.  The results show that it can be seen that economical order according to EOQ method cartons is  pcs for November 2017 – October 2018 periode and for November 2018 – October 2019 periode. There were savings in inventory costs for the period November 2017 - October 2018 amounting to  and for the period November 2018 - October 2019 amounting to .Keywords : Carton; Economic Order Quantity; inventory

scholarly journals Flood Forecasting with Uncertainty Using a Fully Automated Flood Model Chain: a Case Study for the City of Kulmbach

10.29007/jb27 ◽  
2018 ◽  
Author(s):  
Md Nazmul Azim Beg ◽  
Jorge Leandro ◽  
Punit Bhola ◽  
Iris Konnerth ◽  
Kanwal Amin ◽  
...  
Keyword(s):  
Real Time ◽  
Hydrological Model ◽  
Flood Forecasting ◽  
Flood Forecast ◽  
The Public ◽  
Uncertainty Sources ◽  
Flood Model ◽  
The City ◽  
Model Chain

Real time flood forecasting can help authorities in providing reliable warnings to the public. This process is, however, non-deterministic such that uncertainty sources need to be accounted before issuing forecasts. In the FloodEvac project, we have developed a tool which takes as inputs rainfall forecasts and links a hydrological with a hydraulic model for producing flood forecasts. The tool is able to handle calibration/validation of the hydrological model (LARSIM) and produces real-time flood forecast with associated uncertainty of flood discharges and flood extents. In this case study, we focus on the linkage with the hydrological model and on the real-time discharge forecasts generated.

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