scholarly journals Integrasi Linear Regression dan Aggregate Planning untuk Perencanaan dan Pengendalian Produksi Leaf Spring Hino OW 190/200 di Industri Komponen Otomotif

2021 ◽  
Vol 13 (2) ◽  
pp. 245
Author(s):  
Deni Ahmad Taufik ◽  
Indra Setiawan ◽  
Muhammad Wahid ◽  
Abdul Rochim ◽  
Muhammad Tosin
Keyword(s):  
Linear Regression ◽  
Production Planning ◽  
Raw Materials ◽  
Raw Material ◽  
Leaf Spring ◽  
Linear Regression Method ◽  
Planning And Control ◽  
Automotive Assembly ◽  
And Control ◽  
Material Requirements

Production planning and control in a manufacturing company involves all production activities from raw material requirements to finished products. The Jakarta Automotive Components Industry is engaged in manufacturing which produces leaf spring products that are sent to several regular customers, namely the Automotive Assembly Industry. Leaf spring Hino OW 190/200 is the type of spring ordered and shipped to PT. HMMI. Based on data for the January-December 2019 period, the demand for Hino OW 190/200 leaf spring has fluctuated quite significantly. The purpose of this study was to plan and control the production process of Leaf Spring Hino OW 190/200. Forecasting for the next 12 periods is based on demand plots from the previous 12 periods, calculating the Aggregate production plan, determining the Master Production Schedule (MPS), calculating raw material requirements using the Hybrid and Lot for Lot methods. The results showed that to support the smooth production, it can be seen that the production planning for forecasting calculations using the Linear Regression method generates a model Y=319,575+3,723X. Calculation of the need for main raw materials and components in 2020 uses the Hybrid and Lot for Lot method, which is 256,182.88 kg, much smaller than the company's calculations based on 2019 data, namely 259,827.40 kg.

scholarly journals Elaboration of a production planning system for a snack manufacturing company

2019 ◽  
pp. 8-17
Author(s):  
Ana Maria Hernandez-Jasso ◽  
Miguel Ángel Gómez-Vicario ◽  
Lilia Araceli Bahena-Medina ◽  
Ángel Adrián Ordaz-González
Keyword(s):  
Production Planning ◽  
Raw Materials ◽  
Raw Material ◽  
Planning System ◽  
Control Material ◽  
Material Requirement Planning ◽  
Material Requirement ◽  
And Control ◽  
Production Company ◽  
Logic System

A Production Planning System was made for a snacks’ production Company by the development of a MRP system in order to increase the present production and to meet the demand. The methodology used was Material Requirement Planning (MRP) that basically consists in a logic system able to manage and control material requirement planning based on a number of pieces, components and material needed for manufacturing, in other words, it is a production planning system. The outcome of the Project has been an application with MRP features, with complements such as line balance, purchasing Budget of raw materials, among other things. The application relies on protection of information and backup by the same. The executable application of MRP system has contributed to reduce 50% the production breach at the company, as well as reducing waste in a 40%, idle time in a 50% and raw material costs in a 25%, achieving the stated goal.

scholarly journals Perencanaan dan Pengendalian Bahan Baku Sarung Batik (Studi Kasus CV. Mitra Setia Usaha)

2018 ◽  
Vol 1 (1) ◽  
pp. 24-30
Author(s):  
Debby Malinda ◽  
Tita Talitha ◽  
Jazuli Jazuli
Keyword(s):  
Textile Industry ◽  
Raw Materials ◽  
Raw Material ◽  
Business Partners ◽  
Planning And Control ◽  
Material Requirement ◽  
One Year ◽  
The Cost ◽  
And Control

Planning and controlling the needs of both raw materials and finished products is a significant thing for companies to optimize their production. This also applies to CV. Mitra Setia Usaha that  engaged in the textile industry with raw materials batik cloth. During this time, CV. Mitra Setia Usaha has not applied standard methods in the planning and control of raw material needs. Determination of the amount of raw materials so far only based on the number of consumer orders. In the last 2 (two years) (October 2014 to September 2016), the company received a request of 5.050,000 meters, but the existing supply of cotton fabric was only 4,920,500 meters. One of the methods that can be applied in the CV. Loyal Business Partners is the Material Requirement Planning (MRP). By applying this MRP-Lot for for lot (LFL) method, CV. Mitra Setia Usaha able to reduce the cost incurred in the procurement of raw materials for one year which initially amounted to 104.328.000 rupiah to 93.817.673 rupiah and can even be reduced again to 83.306.995 rupiah using the method of Order Quantity Period (POQ)

The Conversation Cycle

2011 ◽  
pp. 230-259
Author(s):  
Ashutosh Deshmukh
Keyword(s):  
Product Design ◽  
Production Planning ◽  
Raw Materials ◽  
Cost Accounting ◽  
Production Planning And Control ◽  
Planning And Control ◽  
External Reporting ◽  
Cost Accounting System ◽  
The Cost ◽  
And Control

The conversion cycle spans a range of activities — product design, production planning and control, and cost accounting. Product design is a collaborative activity and can involve a number of specialists from different functional areas. Production planning and control involves planning production by optimizing factors such as customer demand, availability of materials and labor, capacity constraints, distribution constraints and storage constraints, to mention a few. Planned manufacturing activities are carried out by processing raw materials though a combination of machines and humans and creating a finished product. The cost accounting system provides data useful for evaluating production function, determining product costs and generating information for inventory valuation for external reporting purposes.

scholarly journals Perencanaan persediaan bahan baku amoxicillin menggunakan metode material requirement planning: studi kasus

2020 ◽  
Vol 12 (3) ◽  
pp. 344
Author(s):  
Firda Pratiwi ◽  
Sawarni Hasibuan
Keyword(s):  
Linear Regression ◽  
Raw Materials ◽  
Moving Average ◽  
Raw Material ◽  
Linear Regression Method ◽  
Lot Size ◽  
Initial Stage ◽  
Material Requirement ◽  
Good Plan ◽  
The Cost

PT. XYZ is a pharmaceutical company that produces Amoxicillin. In managing its inventory, PT XYZ has not done a good plan to determine the size of raw material orders. The existence of these problems, a study was conducted with the aim of determining Amoxicillin raw material inventory planning to eliminate the accumulation of raw materials at future. The initial stage is forecasting using three methods, namely Linear Regression, Exponential Smoothing and Moving Average. Of the three forecasting methods, the Linear Regression method provides the smallest error accuracy. The chosen method of forecasting must be carried out in advance of verification test (Moving Range) to be used as a basis for planning future raw material requirements. Furthermore, calculations are carried out using the MRP method to determine the size of the order lot for each raw material and reduce the cost of saving. The lot size technique used includes Lot for Lot (LFL), Economic Order Quantity (EOQ), and Fixed Period Requirement (FPR). Of the three lot size techniques used, the LFL method provides the lowest total cost of inventory.

scholarly journals Perencanaan dan Pengendalian Persediaan Bahan Baku serta Komponen Mbox di PT. X

2019 ◽  
Vol 23 (2) ◽  
pp. 177-185
Author(s):  
Alif Nurul Hidayah
Keyword(s):  
Raw Materials ◽  
Raw Material ◽  
Lot Size ◽  
Inventory Cost ◽  
Planning And Control ◽  
Calculation Results ◽  
Total Inventory ◽  
The Difference ◽  
And Control ◽  
Material Ordering

The development of the industrial now increasingly rapid because the companies compete each other to be excellent in their fields. Companies can survive in the midst of competition if the company is able to increase efficiency. One of the way is to control inventory. This research was conducted to make the planning and control of the optimal needs of raw material and component at PT. X by applying the Wagner Within Algorithm method to achieve the Mbox production target. Types of raw materials and component in forming one Mbox product unit consist 18 types of component and 6 types of raw materials. Data processing will be done by setting the Mbox request every period. After that, inventory control costs are calculated using the 3 step Wagner Within Algorithm method. From the calculation results obtained by order lot size which results in a total inventory cost of Rp. 54.109.030. with component production every period must be fulfilled and raw material ordering is done at the beginning of the period to meet the production needs to entire period. Except for 1,5 mm steel plate order, which are ordered 6 times. The difference is due the calculation results from the Wagner Within Algorithm method which requires bookings made at certain periods.

PENGARUH HARGA DAN PEMAKAIAN PERSEDIAAN BAHAN BAKU TERHADAP VOLUME PRODUKSI PADA PT. KELOLA MINA LAUT DI GRESIK

MANAJERIAL ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 66
Author(s):  
BAYU YRI WIDHARTO
Keyword(s):  
Linear Regression ◽  
Hypothesis Testing ◽  
Multiple Linear Regression ◽  
Raw Materials ◽  
T Test ◽  
Raw Material ◽  
Analysis Tool ◽  
Production Volume ◽  
F Test ◽  
Material Price

The purpose of the research was to know the affect of many factors which affected to the production volume in PT. Kelola Mina Laut Gresik. What the price of raw materials was and the used of raw materials partially and simultan eously affected on the production volume. The analysis tool which used was a model of multiple linear regression. Hypothesis testing used t test and F test, both at the significant level 5%. Based of the analysis of research on PT Kelola Mina Laut Gresik. Partially, inventory raw material price had not significant effect on the production volume, consumption of raw material inventory affected significantly of the production volume. Inventory of raw material price and the use of raw material simultan eously affect significantly to the production volume.

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