scholarly journals A Continuous Review Production-Inventory System with a Variable Preparation Time in a Fuzzy Random Environment

Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 747
Author(s):  
Amalendu Singha Mahapatra ◽  
Hardik N Soni ◽  
Maheswar Singha Mahapatra ◽  
Biswajit Sarkar ◽  
Sanat Majumder
Keyword(s):  
Inventory Management ◽  
Setup Time ◽  
Order Quantity ◽  
Setup Cost ◽  
Preparation Time ◽  
Numerical Illustration ◽  
Expected Cost ◽  
Continuous Review ◽  
Production Inventory ◽  
Production Preparation

With the increase in the varieties products and the increasing uncertainty about product demand, the production preparation time is a significant factor in addressing these issues. The trade-off between the reduction of the production preparation time and the associated cost remains a critical decision. With this backdrop, this study presents a continuous review production-inventory model with a variable production preparation time and a time-dependent setup cost. The demand during the preparation time is captured through a min-max distribution-free approach. In a stochastic framework, the order quantity, reorder point, and setup time are optimized by minimizing the expected cost considering the time-value effect. Further, a fuzzy model is formulated to tackle the imprecise nature of the production setup time and demand. Two algorithms are developed using an analytical approach to obtain the optimal solution. A numerical illustration is given to present the key insights of the model for effective inventory management. It is observed that order quantity and total cost are more sensitive at the lower side of the optimal setup time rather than at the higher side. The discount rate is also found to be a sensitive factor while minimizing the total expected cost.

PRODUCTION–INVENTORY MODEL FOR A DETERIORATING ITEM WITH IMPRECISE PREPARATION TIME FOR PRODUCTION IN A FINITE TIME HORIZON

2006 ◽  
Vol 23 (02) ◽  
pp. 171-192 ◽  
Author(s):  
N. K. MAHAPATRA ◽  
M. MAITI
Keyword(s):  
Finite Time ◽  
Time Horizon ◽  
Inventory Level ◽  
Pareto Optimal ◽  
Selling Price ◽  
Setup Cost ◽  
Preparation Time ◽  
Weighted Sum Method ◽  
Production Inventory ◽  
Finite Time Horizon

In this paper, realistic production-inventory models with shortages for a deteriorating item with imprecise preparation time for production (hereafter called preparation time) has been formulated and an inventory policy is proposed for maximum profit in a finite time horizon. Here, the rate of production is constant, demand depends on selling price, marketing cost, and inventory level, and setup cost depends on preparation time. The imprecise preparation time is assumed to be represented by a fuzzy number and is first transformed to a corresponding interval number and then following interval mathematics, the objective function for total profit over the finite time horizon is changed to respective multi-objective functions. These functions are maximized and solved for a set of Pareto optimal solution with the help of the weighted sum method using the generalized reduced gradient technique. Different case studies have been made depending upon the occurrence of shortages. The models have been illustrated by numerical data. Pareto-optimal solutions for different weights are obtained and presented in tables and graphs.

Production-Inventory Decisions under Order-Occurrence Risk: The Deterministic Order Quantity Case

1976 ◽  
Vol 22 (6) ◽  
pp. 664-676 ◽  
Author(s):  
Richard R. Jesse
Keyword(s):  
Order Quantity ◽  
Production Inventory ◽  
Inventory Decisions

Parameter values for lot size and quality level via CAE simulation, statistical method, and mathematical programming

2021 ◽  
pp. 095440542093787
Author(s):  
Angus Jeang ◽  
Chien-Ping Chung
Keyword(s):  
Inventory Management ◽  
Quality Level ◽  
Response Functions ◽  
Lot Size ◽  
Optimal Process ◽  
Production Inventory ◽  
Production Quantity ◽  
Parameter Values ◽  
Back Order ◽  
Order Intervals

Because of the stochastic nature of production systems, it is necessary to first build an uncertainty model for subsequent real applications. Moreover, process parameter planning, quality design, and production inventory management are interdependent elements. In this research, a computer simulation model via computer-aided engineering (CAE) was developed to determine the optimal process parameters, lot size, and back order intervals for an integrated process design and inventory management system with simultaneous quality and cost considerations. Based on the estimated process time and costs obtained using CAE, the derived production rate and unit cost were then used for production inventory applications. In consideration of the uncertainty factor, the response surface method (RSM) was employed to analyze the output, namely the total costs incurred in employing the proposed approach, as well as the inputs, which include the cutting parameters, production quantity, and back order intervals. After the RSM was used to obtain the response functions, which represent the output of the collective interests, the mathematical programming (MP) was formulated based on the response functions to determine the optimal process parameters, process quality levels, production order quantities, and back order intervals. The total cost per set time unit was minimized by determining the required quality level, process parameter values, Economic Production Quantity (EPQ), and back order intervals. A cutting example was chosen to demonstrate the proposed approach. Two cases were used for comparison: the Integrated Case (the proposed approach herein) and the Disintegrated Case.

ANALYSIS OF THE MANAGEMENT OF MATERIAL AND TECHNICAL ASSETS OF ENTERPRISES

2021 ◽  
Vol 116 (1) ◽  
pp. 293-299
Author(s):  
Aizhan Talgatkyzy Syrkebai
Keyword(s):  
Inventory Management ◽  
Realistic Model ◽  
Process Approach ◽  
Sustainable Competitive Advantage ◽  
Order Quantity ◽  
Specific Product ◽  
Abc Classification ◽  
Eoq Model ◽  
Demand Rate ◽  
Abc Analysis

Variability of demand for goods, depending on their availability and cost is a frequently observed phenomenon in the sphere of production and consumption. This paper discusses the possibility of using the ABC analysis for the inventory management system. This type of analysis makes it possible to apply various methods of inventory management for increasing the income and reducing the costs of particular products for manufacturers. As is known, the management process approach emphasizes the systematic study of management by defining management functions in an organization and then examining each in detail. There is a general agreement on the planning, organizing, and controlling functions. Traditional inventory management systems, such as the Lean Order Quantity (EOQ) model, are based on the assumptions of constant demand rate, constant inventory cost, and instant order. The EOQ assumption of instant order receipt means that the entire order quantity, that is, all units of the purchased lot is immediately received from the supplier. The Economic Production Quantity (EPQ) model weakens this assumption by including incremental order receipt, i.e. debit. In recent years, major advances in the sphere of management include the following elements: process approach management science decision support approach, scientific approach to human resources development, and sustainable competitive advantage. These four approaches complement one another in current practice and provide a useful framework for project management. This paper presents a realistic model of the goods production and their inventory, since ABC analysis or ABC classification is an integral part of materials management. According to this approach, the inventory is divided into three categories depending on income generation. The ABC analysis helps entrepreneurs identify the main types of products in the warehouse, prioritize the goods management based on their cost, and analyze customer demand for a specific product.

scholarly journals Note—Comments on “Single Cycle Continuous Review Policies for Arborescent Production/Inventory Systems”

1978 ◽  
Vol 24 (16) ◽  
pp. 1766-1768 ◽  
Author(s):  
John A. Muckstadt ◽  
Howard M. Singer
Keyword(s):  
Inventory Systems ◽  
Single Cycle ◽  
Continuous Review ◽  
Production Inventory

scholarly journals THE ANALYSIS OF RAW MATERIAL INVENTORY OF DOHO SUWAR-SUWIR BUSINESS IN JEMBER REGENCY

2020 ◽  
Vol 20 (2) ◽  
Author(s):  
Ardhitya Alam Wiguna ◽  
Linda Ekadewi Widyatami
Keyword(s):  
Inventory Management ◽  
Raw Material ◽  
Processed Food ◽  
Order Quantity ◽  
Stock Management ◽  
Safety Stock ◽  
Typical Food ◽  
The Stability ◽  
Small Medium Enterprises ◽  
Medium Enterprises

Doho Suwar-Suwir is a Micro Small Medium Enterprises (UMKM) processing Fermented Cassava (Tape Singkong) to become a processed food in Jember, which is Suwar-Suwir. To maintain the stability of production process, needs a control for the stock management towards the raw material at Doho Suwar-Suwir UMKM. The raw material inventory management at Doho Suwar-Suwir UMKM is about fermented cassava raw material inventory which then are processed to become the typical food of Jember Regency, which is Suwar-Suwir. The goal of this research were to analyze the fermented cassava raw material inventory quantity and to analyze the safety stock quantity at Doho Suwar-Suwir UMKM. The method used in this research was stock management calculation or Economical Order Quantity (EOQ) where the result of this research was the quantity of fermented cassava raw material  needed using Economical Order Quantity (EOQ) method at Doho Suwar-Suwir business was 60,6 kg and the number of the safety stock which must exist was 5,5 kg.

scholarly journals PERENCANAAN DAN PENGENDALIAN PERSEDIAAN BAHAN BAKU PAIL CAT MENGGUNAKAN METODE MATERIAL REQUIRMENT PLANNING (MRP) PADA PT. XYZ

JUMINTEN ◽  
2020 ◽  
Vol 1 (4) ◽  
pp. 163-172
Author(s):  
Vify Elviana ◽  
Akmal Suryadi
Keyword(s):  
Inventory Management ◽  
Consumer Demand ◽  
Raw Materials ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Material Requirements Planning ◽  
Total Cost ◽  
Material Requirements

Persediaan merupakan aset perusahaan yang memiliki peran penting dalam operasi bisnis, sehingga perusahaan penting untuk melakukan manajemen persediaan yang baik, artinya perusahaan harus mampu mengantisipasi kendala maupun tantangan yang ada dalam pengelolahan persediaan untuk meminimalisasi total biaya yang harus dikeluarkan oleh perusahaan. Permasalahan yang timbul pada persediaan bahan baku di PT XYZ adalah perusahaan melakukan perencanaan dan pengendalian bahan baku hanya berdasarkan pada pengalaman-pengalaman sebelumnya dan tidak berdasarkan pada metode yang sudah baku. Oleh karena itu pembelian bahan baku tidak sesuai dengan permintaan konsumen. Hal tersebut sering menyebabkan terjadinya kelebihan maupun kekurangan stok bahan baku. Kesalahan dalam penentuan besarnya investasi dalam persediaan akan mengurangi keuntungan perusahaan. Adanya persediaan bahan baku yang terlalu besar, akan menambah beban biaya pemeliharaan dan penyimpanan dalam gudang, serta kemungkinan terjadinya penurunan kualitas bahan baku yang dapat menyebabkan berkurangnya keuntungan perusahaan. Namun jika persediaan bahan baku terlalu sedikit maka akan berakibat pada terhambatnya proses produksi, sehingga tidak terpenuhinya permintaan konsumen. Hasil penelitian ini dapat menyimpulkan bahwa perencanaan kebutuhan bahan baku dengan metode perusahaan didapatkan total cost sebesar Rp 1.796.762.429,-, sedangkan metode Material Requirements Planning (MRP) didapatkan total cost sebesar Rp 1.576.011.801,-. Maka dapat disimpulkan telah terjadi penurunan total cost seluruh bahan baku sebesar 12,28%. Hal ini membuktikan bahwa metode Material Requirements Planning (MRP) lebih efisien daripada metode PT. XYZ. Oleh karena itu untuk mendapatkan total cost yang minimum, metode Material Requirements Planning (MRP) diterapkan pada periode Februari-Juni 2020 sehingga didapatkan total cost sebesar Rp 1.576.011.801,-. Kata Kunci:         Material Requirements Planning (MRP), PT XYZ, Pail Cat, Economic Order Quantity (EOQ), Period Order Quantity (POQ), Lot For Lot (LFL). ABSTRACT                     Inventory is a company asset that has an important role in business operations, so the company is important to conduct good inventory management, meaning that the company must be able to anticipate obstacles and challenges that exist in managing inventory to minimize the total cost to be incurred by the company.The problem that arises in the supply of raw materials in PT XYZ is that the company plans and controls raw materials based only on previous experiences and not based on established methods. Therefore, the purchase of raw materials is not in accordance with consumer demand. This often leads to excess or shortage of raw material stock. Mistakes in determining the amount of investment in inventories will reduce company profits. The availability of raw materials that are too large, will add to the burden of maintenance and storage costs in the warehouse, as well as the possibility of a decline in the quality of raw materials that can lead to reduced company profits. However, if the supply of raw materials is too little, it will result in obstruction of the production process, so that consumer demand is not fulfilled. The results of this study can conclude that the planning of raw material needs by the company method obtained a total cost of Rp 1,796,762,429, - while the Material Requirements Planning (MRP) method obtained a total cost of Rp 1,576,011,801, -. Then it can be concluded that there has been a decrease in the total cost of all raw materials by 12.28%. This proves that the Material Requirements Planning (MRP) method is more efficient than the PT. XYZ. Therefore, to get the minimum total cost, the Material Requirements Planning (MRP) method was applied in the February-June 2020 period so that a total cost of Rp 1,576,011,801 was obtained.   KeyWords: Material Requirements Planning (MRP), PT XYZ, Pail Cat, Economic Order Quantity (EOQ), Period Order Quantity (POQ), Lot for Lot (LFL).

scholarly journals A Production Inventory Model with Shortages, Fuzzy Preparation Time and Variable Production and Demand

2012 ◽  
Vol 02 (02) ◽  
pp. 183-192 ◽  
Author(s):  
Nirmal Kumar Mahapatra ◽  
Uttam Kumar Bera ◽  
Manoranjan Maiti
Keyword(s):  
Inventory Model ◽  
Preparation Time ◽  
Production Inventory ◽  
Variable Production
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