Material Requirements Planning Research Articles

Pengendalian Persediaan Bahan Baku Dengan Metode Material Requirement Planning Pada Produksi Majalah SM PT ABC

PT ABC operates in the printing and publishing sector which produces magazines using a make to order system. The problem that often occurs is related to the fluctuating demand for SM magazines from March 2021 to February 2024. As a result of this condition, the company cannot estimate the amount of raw materials needed, so orders are made based on estimates only. This causes overstock, especially 1001 reams of 58 gram HVS paper. The research objective is to find out planning, inventory control, and ordering techniques that produce minimal costs. In this case, suitable methods to apply are Material Requirement Planning (MRP), lot size Economic Order Quantity (EOQ), Lot For Lot (LFL) and Period Order Quantity (POQ). From the proposed improvements, the minimum cost with Lot For Lot (LFL) was IDR 2.320.000. So, costs can be minimized to IDR 93.260.746 or 98% compared to the method used by the company.

Material Planning Analysis with Material Requirement Planning Method in High-rise Building Projects

Planning material supplies well is very important in implementing construction projects to ensure smoothness and efficiency. Smoothness includes thorough planning, including ensuring materials are met as planned, while efficiency aims to reduce time and cost. In this study, material planning will be carried out using the Material Requirement planning (MRP) method, using three different lot measurement techniques, namely Lot for Lot (LFL), Economic Order Quantity (EOQ), and Period Order Quantity (POQ). The MRP method is carried out to accurately calculate the amount of material needed to avoid excessive material inventory levels. After the MRP method, the most optimal number of orders and the total cost required for each lot measurement technique are obtained. The results of this study show that the LFL technique produces the optimum number of orders for gelam wood, plywood, reinforcement, bendrat wire, and ready mix concrete. Meanwhile, for materials such as lubricating oil, meranti wood, randu wood, and nails, it is optimal to order using the POQ technique.

Analisis Penerapan Metode Material Requirement Planning (MRP) dalam Perencanaan dan Pengendalian Bahan Baku pada PT. BSM

PT. BSM, is a company that operates in the manufacturing sector by producing Mechanical Seals and is also a distributor of the Nippon Pillar Japan brand. Production planning and control is necessary to ensure that all processes function smoothly and production efficiency and effectiveness are achieved. PT.BSM's production system implements Make To Order (MTO), in which production activities are carried out when the customer places an order. This process will take place from raw materials, and semi-finished goods to finished products. This will pose a risk to the production process if the raw materials to be produced are not yet available. So it is necessary to have an analysis of planning and inventory control to expedite the production process. Therefore, the purpose of this study is to plan and control raw materials in accordance with requests from customers in the future using the Material Requirement Planning (MRP) method with the Lot For Lot (LFL) technique, after calculating the MRP with The Lot For Lot (LFL) technique obtained the planning results for mechanical seal raw material requirements for 2023 every month. Based on MRP calculations using the Lot For Lot technique, mechanical seal raw materials can be planned and controlled for the next 12 periods. Key Words: LFL, Mechanical Seals, MRP, Supplies

Research on integration of enterprise ERP and E-commerce systems based on adaptive ant colony optimization

Integrating the E-commerce system with an enterprise resource planning tool can help the firm improve performance, maintain customers, and increase sales. In Enterprise Resource Planning, integration features can be provided either as developed features or as separate assignments and contributions. Problems with the online platform, improper addresses, rejected payments, and especially apparent transactions are frequent problems for online buyers. The enhanced Adaptive Ant Colony Optimization is utilized to optimize the rural E-commerce express of transportation. Several innovative routes can lower the downlink transportation cost and reach all collecting places with a fast delivery route. Convolutional Neural Networks were utilized to increase the collective innovation of the E-commerce platform and simplify network communication. E-commerce is a mechanism used to market information services and products. Hence, ERP-AACO-CNN has been designed to integrate Enterprise Resource Planning and E-commerce, and business operations can stream smoothly from the front to the back of the business. Statistics on sales orders, customers, stock levels, price, and essential performance measurement systems. The automated invoices, frequent communications, financial report preparation, product and service delivery, and material requirements planning. The most significant results will likely finance businesses that employ it as a stimulant for a wide-ranging process improvement. In addition, E-commerce is a valuable innovation that connects buyers and sellers in various corners of the globe. Customer satisfaction is projected to be more significant than fault detection at 95.2 % accuracy for the proposed method’s E-commerce system with the superior value. According to client demand, an E-commerce system is the most accurate development at a given input level, and a future ERP is 64.9% efficient. The proposed approach has a 24.5% random error rate and a 13.2% mean square error rate. A comparison of E-commerce and enterprise ERP precision to the proposed technique yields 83.8% better results.

Improving MRP Precision in Engineering and Manufacturing Sectors

This study evaluates the effectiveness of Material Requirement Planning (MRP) in the engineering and manufacturing sector through a five-month empirical investigation focused on production processes. Utilizing a combination of literature review, interviews, and direct observation, the research aimed to compare theoretical MRP calculations with actual raw material usage. Results highlighted significant discrepancies between projected and actual figures, indicating potential inaccuracies in current MRP applications. These findings underscore the need for refining MRP systems to enhance forecasting precision and inventory management, suggesting that integrating real-time data and improving algorithmic methodologies could bridge the existing gap between theory and practice in industrial manufacturing. Highlights: Essential Raw Material Management: Key for timely production and meeting customer needs. MRP Efficiency: PT. Weiss Tech uses MRP for precise raw material calculations. Accuracy Assessment: Research evaluates MRP accuracy through literature, interviews, and observation. Keywords: Raw Materials, MRP, Inventory Control

Fuzzy demand-driven material requirements planning: a comprehensive analysis of fuzzy logic implementation in DDMRP

ABSTRACT Demand-Driven Material Requirements Planning (DDMRP) is a new method of inventory control designed to address the challenges of today's complex and volatile supply chain environment. DDMRP replaces traditional Material Requirements Planning (MRP) with a more agile and responsive approach that is based on a set of colour-coded buffers. DDMRP ensures that the right inventory is in the right place at the right time, enabling companies to respond quickly and effectively to changing customer demand. DDMRP requires the setting of various parameters, such as variability factor (VF) and lead time factor (LTF), which can have a significant impact on systems’ performance. Pre-assumed fixed values of DDMRP parameters are used in most of the existing studies. This may lead to either high stockout levels or excess inventory especially in environments involving high level of variability. In this study, we proposed a fuzzy logic-based approach which dynamically adjusts the values of VF and LTF parameters considering demand and lead time variability. The effectiveness of the proposed approach was investigated by comparing its performance with DDMRP based on several numerical experiments. The results showed that the proposed Fuzzy Demand-Driven Material Requirements Planning (FDDMRP) outperforms DDMRP in terms of backorder rate and total cost.

Raw Material Control Production of Crumble Type Chicken Animal Feed at PT Japfa Comfeed Indonesia, Tbk.

. Raw materials are tangible items used in production which can be obtained from natural sources or 
 purchased from suppliers or companies that produce raw materials for the industry that uses them. MRP (Material Requirement Planning) According to Haizer and Render (2005: 160) the material requirement planning method is a bound demand technique that uses materials, inventory, estimated receipts, and master production schedules to determine the amount of material. Inventory control is a very important managerial function for the Company, material requirements planning is a planning system that focuses on the amount and time of finished goods requested 
 which then determines the derivative demand for raw materials. From inventory control, it can be seen from the MRP 
 calculation how much raw material PPIC must order, so that there is no shortage of raw materials or no inventory at all.And the results of MRP for one year or 12 periods can be known how much raw material must be provided for production in a year that will be data.

The role of effective inventory management practices on organizational performance: a case of Tarkwa municipal hospital, western region, Ghana

The study aimed at investigating the role of effective inventory management practices on organisational performance; a case study of Municipal Hospital Tarkwa in the Western Region of Ghana. The specific objectives of the study were to establish the inventory management practices used by organisations, to find the effect of inventory management practices on organisational performance, and to determine the challenges of implementing inventory management practices in organizations. The study adopted descriptive and causal research designs and used questionnaires as the data collection instrument. Data were collected from 200 respondents and STATA 13 analytical tool was used to perform the analysis. The results were presented using frequency tables and descriptive statistics tables. The study also used Probit regression analysis to establish the relationship between the dependent and the independent variables. The findings show that the stakeholders of the hospital are generally happy with the service delivery of the hospital. Thus, the results show that the hospital adopts various inventory management practices including; activity-based costing, economic order quantity, material requirement planning, materials resource planning, enterprise resource planning, distribution requirement planning, and just in time. The study concludes that effective inventory management positively affects the performance of organizations, in this case, the quality of service delivery of organizations. The study recommends organizations successfully implement an effective inventory management system. This will help reduce the risks of shortages. In addition, the concept of inventory management could be simplified for organizations in Ghana. This can be done through education or training to all staff in organizations to enlighten them on the need for effective inventory management practices for their organization’s performance.

Quantitative insights into the integrated push and pull production problem for lean supply chain planning 4.0

Validated quantitative models for lean supply chain planning (LSCP) are still scarce in the literature, particularly because conventional push systems have not been widely integrated and tested with pull systems in sustainable and resilient environments in the Industry 4.0 context. Hence the main contribution of this paper is to develop an optimisation model that is able to contribute to the LSCP with the combination of push and pull strategies. Here we present an integrated just-in-time (JIT) production system with material requirement planning (MRP) for a SC that takes a traditional five-level structure based on a mixed-integer linear programming model (MILP) dubbed as LSCP 4.0. The model is able to simultaneously plan the production and inventory of materials and finished goods to satisfy demand from forecasts and firm orders. The selection of alternative suppliers as a proactive measure to face disruptive events is also considered. Furthermore, sustainable practices are included in the objective function for profit maximisation by considering CO2 emissions. This proposal is tested in the footwear sector. The results demonstrate that the combined use of JIT and MRP through a quantitative approach improve performance in leanness, sustainability and resilience by decreasing the bullwhip effect at different SC levels.

Data Processing Analysis Using Material Requiremnt Planning (MRP) Method at PT. XYZ

This journal discusses the application of material requirements management strategies in various manufacturing industries, based on material requirements planning (MRP) methodology. Manufacturing industries around the world are increasingly focused on increasing efficiency and reducing production costs. The key to achieving this goal is the implementation of management strategies in materials management, including planning, procurement, storage, inventory control, and efficient use of raw materials. This paper discusses the importance of MRP as an effective material management tool and outlines various approaches and strategies that have been applied in various manufacturing industries, including automotive, electronics, and pharmaceuticals. The result is increased productivity, reduced costs, and increased industrial competitiveness. This article provides an in-depth understanding of how using MRP to implement material requirements management strategies can enable manufacturers to respond quickly to changing market demands.

Classifying MRP Strategy of Aircraft Spare Parts Using Supervised Machine Learning

Spare-parts provisioning strategy is crucial for airlines or Maintenance Repair Overhauls (MRO). The strategy is divided into multiple classes that refer to several criteria, then uses Material Requirements Planning (MRP) to run those strategies. However, classifying spare parts into a strategy is onerous and requires innovation. Therefore, we employ three algorithms: Decision Tree, Random Forest, and Support Vector Machine (SVM), and use spare parts and aircraft utilization data to classify the strategy and optimize spare parts provisioning of MRO over time. The results showed Random Forest performs best by accuracy, sensitivity, and specificity with a score of more than 97%.

IMPROVING MATERIAL REQUIREMENTS PLANNING THROUGH WEB-BASED: A CASE STUDY THAILAND SMEs

In the small business industry, effective cost control is of paramount importance. A well-functioning Material Requirements Planning (MRP) process plays a vital role in enabling businesses to manage their costs efficiently. This research paper explores the improvement of MRP in the context of small businesses in Thailand through the implementation of a web-based application. The objective was to enhance the MRP process by developing an MRP system using ReactJS, NodeJS, and PostgreSQL. The system was evaluated using heuristic evaluation techniques and the results indicated a positive outcome, the mean value is 0.83. The developed web based MRP system proved beneficial for small businesses, as it effectively reduced stocking costs and facilitated efficient raw material procurement. This research provides valuable insights into the implementation of web based MRP systems, enabling small businesses to optimize inventory management and enhance operational efficiency.

LEAN SIX SIGMA APPROACH TO IMPROVE THE PRODUCTION PROCESS IN THE GARMENT COMPANY: A CASE STUDY

PT “X” is a company engaged in the garment industry. The company is facing problems that inhibit the production process. These problems comprise an excess of product defects beyond the specified limits, a considerable rate of product returns, delays in product shipment, and disorderly arrangements in storing raw material. This study aims to determine the root causes of problems in the PT “X” and provide recommendations for improvement using the concept of lean six sigma. The waste assessment model is used to identify the dominant waste, while the value stream analysis tools is a method used to analyze the causes of the dominant waste. From the research results, four dominant wastes are identified, namely waste defects, unnecessary inventory, waiting and unnecessary motion, with percentages of 27.02%, 15.92%, 14.32% and 14.0% respectively. The results of the analysis using mapping tools show the details of waste in each dominant waste. Proposed recommendations for improvement are made using the failure mode and effect analysis based on the highest risk priority number for each dominant waste. The recommendations proposed by the researchers include implementing a standard operating procedure and work instruction for the sewing process; scheduling machine maintenance using reliability centered maintenance II; planning and scheduling materials using material requirement planning; implementing line balancing; and designing name tags, visual displays, and storage rack layout.

IMPLEMENTASI METODE EOQ DAN POQ PADA PENGENDALIAN PERSEDIAAN BAHAN BAKU ALAT UJI KESEHATAN PT. X

Manufacturing companies essentially transform raw materials into finished products through various production operations. This research aims to evaluate the inventory control of raw materials for health diagnostic test device products (HBSAG & HIV) at PT X. The method used is Material Requirement Planning (MRP) with lot sizing techniques using EOQ and POQ methods. The calculated actual inventory costs for the company are Rp 25,357,043 (HBSAG) and Rp 23,973,320 (HIV). The research results using the EOQ lot sizing method show reduced costs to Rp 17,486,791 (HBSAG) and Rp 13,243,617 (HIV). Meanwhile, the POQ lot sizing method yields inventory costs of Rp 16,403,312 (HBSAG) and Rp 12,556,514 (HIV). In the final analysis, the most optimal inventory control method is the Period Order Quantity (POQ) method, as it can save inventory costs by Rp. 8,953,731 (HBSAG) and Rp. 11,346,116 (HIV) annually.

Exploring Applications and Practical Examples by Streamlining Material Requirements Planning (MRP) with Python

Background: Material Requirements Planning (MRP) is critical in Supply Chain Management (SCM), facilitating effective inventory management and meeting production demands in the manufacturing sector. Despite the potential benefits of automating the MRP tasks to meet the demand for expedited and efficient management, the field appears to be lagging behind in harnessing the advancements offered by Artificial Intelligence (AI) and sophisticated programming languages. Consequently, this study aims to address this gap by exploring the applications of Python in simplifying the MRP processes. Methods: This article offers a twofold approach: firstly, it conducts research to uncover the potential applications of the Python code in streamlining the MRP operations, and the practical examples serve as evidence of Python’s efficacy in simplifying the MRP tasks; secondly, this article introduces a conceptual framework that showcases the Python ecosystem, highlighting libraries and structures that enable efficient data manipulation, analysis, and optimization techniques. Results: This study presents a versatile framework that integrates a variety of Python tools, including but not limited to Pandas, Matplotlib, and Plotly, to streamline and actualize an 8-step MRP process. Additionally, it offers preliminary insights into the integration of the Python-based MRP solution (MRP.py) with Enterprise Resource Planning (ERP) systems. Conclusions: While the article focuses on demonstrating the practicality of Python in MRP, future endeavors will entail empirically integrating MRP.py with the ERP systems in small- and medium-sized companies. This integration will establish real-time data synchronization between the Python and ERP systems, leading to accurate MRP calculations and enhanced decision-making processes.

IMPLEMENTATION OF MSME INVENTORY MANAGEMENT IN CIPULIR VILLAGE – JAKARTA SELATAN

Community Service Activities (CSA) were carried out in the Cipulir sub-district. The activity participants are MSMEs who live in Cipulir sub-district. The people at the location generally work as traders and small industries. MSMEs often face problems with shortages or excess supplies which have the impact of hampering business activities. The causes of shortages or excess inventory include: a) MSME actors do not forecast sales, so MSME actors only order inventory according to previous order history. This causes ambiguity between the production plan and the raw material requirements plan, which is the reference for purchasing inventory, b) the absence of safety stock, which is useful for guarding against the possibility of stock outs, c) the absence of clear inventory management, with no there is evidence of inventory recording, as well as inventory control. Based on an analysis of the situation faced by partners, the Community Service Team intends to provide solutions to partner problems by increasing knowledge and understanding regarding inventory management for MSMEs. The method used in this activity is sharing sessions and discussions, which are then given training related to inventory management. Then the activity continued with questions and answers and case study simulations. The results of the evaluation showed that most participants understood the material presented. The evaluation results also illustrate that all participants felt they had benefited from this activity, and were satisfied with the implementation of this activity.

THE PLANNING FOR UPPER SHOES RAW MATERIAL INVENTORY USING THE MATERIAL REQUIREMENT PLANNING (MRP) METHOD (Case Study : PT X)

The planning of raw material inventory is one of the essential factors in planning the order of the raw materials that can make a company maintain its production quality. The company’s policies can be implemented in various ways, such as in planning the raw materials inventory to avoid shortages and excesses of the raw materials supply. However, X Inc. has not implemented inventory planning properly, making the costs incurred by the company not optimal. Thus, Material Requirement Planning (MRP) will be used to determine the scheduling time and quantity of raw materials for ordering with lot sizing techniques. Lot sizing techniques provide solutions to determine the right quantity of raw material orders and minimum total inventory costs with techniques which are Lot for Lot (LFL), Least Unit Cost (LUC), Economic Order Quantity (EOQ), and Silver-Meal. Based on the calculation results, the four lot sizing techniques show that the LFL technique is the optimal technique compared to other techniques because it produces the minimum inventory cost of Rp566.015.685,05. Thus, the company can profit Rp13.295.563,75 compared to company policy.

SISTEM INFORMASI MANAJEMEN PLANING STOK DENGAN METODE MATERIAL REQUIREMENT STUDI KASUS DI PT. ARRGO SURYA ABADI

Technology currently plays an important role for a company. The implementation of information systems in companies is very popular because performance activities will run well, including the ease of data processing. In this case the company that wants information technology is PT. Arrgo Surya Abadi. The inventory system used at PT. Arrgo Surya Abadi still uses notes in the form of spreadsheets which are summarized every day, making it prone to errors in planning raw material needs, and it is difficult to control the use of production raw materials such as dyes. From this phenomenon, of course, a capable raw material planning information system is needed to process data and create raw material reports automatically. The aim of this research is to provide report data regarding the amount and time of raw materials procured to smooth production activities. The method used in this research is Material Requirement Planning (MRP). The results of this research conclude that with the existence of a computerized system at PT. Arrgo Surya Abadi can assist the production process related to procuring the right materials, in efficient quantities and time.

Inventory Lot Sizing Decisions for Material Requirements Planning to Minimize Inventory Costs

<p><em>Inventory control is one of the most important factors in achieving optimal organizational performance. Material Requirement Planning (MRP) is a common method used by businesses to manage inventories. This study focuses on a hydraulic firm that has been in operation since 2016. This research examines the planning of eleven components to get the best planning for the company. This study contributes to the integration of Moving Average (MA) and Exponential Smoothing (ES) forecasting techniques alongside the MRP and three lot sizing techniques, such as LFL, EOQ, and LUC. T</em><em>he minimum error value</em><em>s</em><em> </em><em>between MA and ES are evaluated and followed by the comparison between three lot sizing techniques. The result shows that ES (α=0.1) is selected as the best forecasting technique, and LUC presents the lowest total inventory cost. However, LUC is only 0.05 percent lower than what LFL presents. A larger difference is shown by EOQ with 14.57 percent higher than LUC which makes EOQ unlikely to be selected.</em></p>

Analysis of Fabric Raw Material Inventory Control in Backpack Products Using the Material Requirements Planning (MRP) Method at CV. Metassa Collection

Inventory of raw materials is an important factor in the company so that the supply of raw materials in CV. Metassa Collection must be sufficient to guarantee the needs for the smooth running of production activities. The purpose of this study is to determine the supply of raw materials with the Material Requirements Planning method. The method used is Material Requirement Planning (MRP). In calculating the MRP, the methods used are Lot For Lot and Economic Order Quantity (EOQ). The results of the research on the smallest forecasting calculation using the Linear Regression method with MAD values ​​of 274.52, MSE 114.536, and MADE Based on MRP calculations with the Lot Sizing EOQ method produce a total cost of Rp. 2,811,032,000. The minimum ordering of raw materials using the EOQ method for controlling raw material inventory at CV. Metassa Collection.