Research on enterprise raw material ordering scheme based on dynamic programming

2021 ◽  
Author(s):  
Yuanmeng Song ◽  
He Yan ◽  
Peilin Liu
Keyword(s):  
Dynamic Programming ◽  
Raw Material ◽  
Material Ordering

scholarly journals Determination of Data Mining Application Design Patterns Booking Raw Food In Restaurant Fountain With Apriori Algorithm

2020 ◽  
Vol 2 (2) ◽  
pp. 275-285 ◽  
Author(s):  
Risnamawati Ndruru ◽  
Paska Marto Hasugian
Keyword(s):  
Data Mining ◽  
Inventory Management ◽  
Design Patterns ◽  
Raw Materials ◽  
Raw Material ◽  
Web Based ◽  
New Information ◽  
Material Ordering

Booking is an activity carried out by certain parties to ensure availability, in carrying out certain activities the company has a supply of material in quantities that exceed the needs. As a result, in the warehouse there is a buildup of raw materials or it can happen otherwise. Inventories of materials that are too small can hinder the company's operations in the form of unavailability of materials when needed. The role of inventory will determine the operation of the company because the inventory will run well if supported by good management. Therefore, the concept of inventory management that affects ordering is very important to be applied by companies so that the goals of effectiveness and efficiency are achieved. So we need a Data Mining that can quickly to determine the Determination of Food Raw Material Ordering Patterns in Restaurant Fountain Using Apriori. Data Mining is the extraction of new information taken from large chunks of data that helps in making decisions. One of the applications of data mining for Determining the Pattern of Ordering Food Raw Materials in Restaurant Fountain Using Apriori. Apriori method is a method for determining frequent itemsets for boolean association rules. The research aims to build the application of Determining the Pattern of Ordering Food Raw Materials in Restaurant Fountain with a web-based application and as a tool for designing applications using the Mysql Database. This data mining is able to determine the ordering of food items in the Restaurant Fountain with the required amount.  

scholarly journals Optimization And Analysis Of Copper Wire Raw Material Inventory For Magnetic Process With Dynamic Programming Method

OPSI ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 208
Author(s):  
Annisa Indah Pratiwi ◽  
Akda Zahrotul Wathoni ◽  
Dewih Adetia ◽  
Ahmad Ridho Nurohman
Keyword(s):  
Dynamic Programming ◽  
Copper Wire ◽  
Programming Method ◽  
Raw Material ◽  
Dynamic Programming Method ◽  
Magnetic Process

scholarly journals Comparison of optimized Markov Decision Process using Dynamic Programming and Temporal Differencing – A reinforcement learning approach

2021 ◽  
Vol 2107 (1) ◽  
pp. 012026
Author(s):  
Annapoorni Mani ◽  
Shahriman Abu Bakar ◽  
Pranesh Krishnan ◽  
Sazali Yaacob
Keyword(s):  
Dynamic Programming ◽  
Reinforcement Learning ◽  
Raw Materials ◽  
Raw Material ◽  
Process Failure ◽  
Markov Decision ◽  
Inspection Process ◽  
Research Problems ◽  
Temporal Differencing ◽  
Incoming Inspection

Abstract Reinforcement learning is one of the promising approaches for operations research problems. The incoming inspection process in any manufacturing plant aims to control quality, reduce manufacturing costs, eliminate scrap, and process failure downtimes due to non-conforming raw materials. Prediction of the raw material acceptance rate can regulate the raw material supplier selection and improve the manufacturing process by filtering out non-conformities. This paper presents a Markov model developed to estimate the probability of the raw material being accepted or rejected in an incoming inspection environment. The proposed forecasting model is further optimized for efficiency using the two reinforcement learning algorithms (dynamic programming and temporal differencing). The results of the two optimized models are compared, and the findings are discussed.

Manufacturer Decision Analysis on RFID Adoption

2013 ◽  
Vol 336-338 ◽  
pp. 2483-2487
Author(s):  
Gui Tao Zhang ◽  
Jin Song Hu ◽  
Chun Long Zhao ◽  
Kui Kui Wang ◽  
Guo Rui Wen
Keyword(s):  
Decision Analysis ◽  
Decision Maker ◽  
Raw Materials ◽  
Raw Material ◽  
Newsvendor Model ◽  
Rfid Technology ◽  
Manufacturing Enterprise ◽  
The Impact ◽  
Material Ordering ◽  
Ordering Quantity

RFID technology has many advantages and plays an important part in eliminating the inaccuracy of inventory information. This paper analyzed how manufacturers decided the raw material ordering quantity to maximize their profit when the price of raw materials was given through newsvendor model. Combined with the impact of putting raw materials wrongly and lost of raw materials, we compare the profits of not adopting RFID technology and that of adopting it. Then we obtain the biggest cost that manufacturer could undertake when adopting RFID, and the results can provide the foundation for the decision maker of manufacturing enterprise.

scholarly journals PERENCANAAN KEBUTUHAN MATERIAL DENGAN METODE MATERIAL REQUIREMENT PLANNING

2016 ◽  
Vol 15 (2) ◽  
pp. 190
Author(s):  
SUHARTINI .
Keyword(s):  
Raw Materials ◽  
Raw Material ◽  
Performance Rating ◽  
Productive Capacity ◽  
Material Requirements Planning ◽  
Product Demand ◽  
Material Requirement Planning ◽  
Material Requirement ◽  
Many Sources ◽  
Material Ordering

Kegiatan produksi yang dilakukan oleh beberapa perusahaan masih menggunakan persediaan material yang banyak agar kegiatan produksi dapat berjalan lancar, akan tetapi kondisi ini dianggap tidak optimal karena banyak sumber daya yang ditanam, sehingga investasi hanya digunakan untuk keperluan kebutuhan material. Pemesanan material yang tidak didukung dengan data-data permintaan produk secara tepat, akan membuat persediaan bahan baku tidak dapat dipastikan sehingga material terkadang banyak dan kadang kala habis. Dalam menggunakan tenaga kerja dan fasilitas produksi yang tidak sesuai dengan kebutuhan permintaan, maka kegiatan produksi tidak berjalan secara efektif dan efisien. Sumber daya yang dimiliki oleh perusahaan harus diketahui secara detail, agar perusahaan dapat menggunakan kemampuan sumber daya yang ada secara optimal. Perusahaan dalam mencapai permintaan produk harus mengetahui kapasitas produksi yang dimiliki, sehingga kemampuan target produksi perusahaan dapat dicapai secara optimal, dengan melakukan pengukuran waktu standar pada operasi kerja dan menentukan performance rating untuk masing-masing operator. Dalam menentukan permintaan produk untuk periode berikutnya menggunakan metode peramalan jenis regresi linier dengan jumlah permintaan produk sebesar 1278 kg. Perencanaan kebutuhan material (MRP) pesanan dapat dilakukan pada hari ke-7 tiap bulan sesuai dengan jumlah masing-masing jenis bahan baku. Production activities which are conducted by some companies still use a lot of material inventory that production activities can run smoothly, but this condition is not considered optimal because many sources in the plant, so the investment is only in use for material. Ordering a material is not supported by data appropriately in product demand, it will make inventory of raw materials can not be sure so that the material is sometimes a lot and sometimes run out. The use of labor and production facilities are not accordance with demand, finally the production activities are not effective and efficient. Resources owned by the company must to be known in detail, so that the company can use capabilities of existing resources optimally. Company to achieve product demand should know the productive capacity, so that the ability of the company’s production targets can be achieved optimally, by measuring standard time at work operations and determine performance rating for each operator. In determining the demand for the product the next period using the method of linear regression forecasting the number of types of product demand of 1278kg. Material requirements planning (MRP) orders can be made on day 7 of each month in accordance with the number of each type of raw material.

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