Inventory Stock Research Articles

Determining and Managing Stock of Goods Based on Purchasing Patterns Using the Frequent Pattern Growth Algorithm

Stock inventory is one of the important work activities, because stock inventory is the main element in the field of commerce. Mistakes regarding stock inventory will result in fatal problems, especially when stock inventory management is still done manually or improper stock inventory planning can cause the amount of stock to pile up due to the small amount of demand from consumers, resulting in the stock being damaged, especially those contains elements of expiration because it is not sold. On the other hand, if the stock of goods is low while consumer demand is high, consumers will turn to other supermarkets to look for the goods they want. This can make supermarkets lose money because they cannot meet consumer needs. Therefore, a system is needed to look for product item combination patterns using association techniques in determining and managing stock. This research aims to look for product item combination patterns in previous period transaction data based on purchasing patterns in determining and managing inventory at supermarkets using the FP-Growth method. Where with Min. Support 30% and Min. Confidence 70% produces 12 rules then with Min. Support 45% and Min.Confidence 60% produces 6 rules. Based on the comparison and analysis results obtained using the FP-Growth method, in this study the Min limit was chosen. Support 30% and Min. Confidence 70% due to generating 12 association rules. This information can be used as a reference for supermarkets in making decisions in determining and managing stock of goods based on purchasing patterns.

ANALYSIS OF INVENTORY CONTROL OF RAW MATERIALS FOR OYSTER MUSHROOMS PLANTING MEDIA IN UMKM AQSHA GUNUNG LINGKAS URBAN VILLAGE, EAST TARAKAN

UMKM Aqsha is a Small and Medium Enterprise that produces oyster mushrooms in Tarakan City. In the implementation process, the inventory for oyster mushrooms has yet to use the calculation method of EOQ analysis. In this case, there might be a media shortage of raw planting materials. The objectives of the research were to (1) describe the system of controlling the inventory for oyster mushrooms planting media raw materials based on actual conditions at UMKM Aqsha, (2) analyze the system of controlling the inventory for oyster mushrooms planting media raw materials using economic order quantity analysis, buying frequency, safety stock, reorder point and maximum inventory. The technique of taking informants was conducted by selecting the key informants, namely business owners and workers who know the information needed in the research. The analysis method used economic order quantity analysis, buying frequency, safety stock, reorder point and maximum inventory. The results of the research showed that the inventory control of UMKM Aqsha required all three raw materials totaling 3,345 kg in a year, with a one-time order quantity for the three raw materials totaling 1,115 kg. The inventory control implemented by UMKM Aqsha was not optimal yet and also has not yet implemented a reorder point. So that it was not possible to prevent a shortage of the three raw materials during the production process. EOQ analysis was given an optimum order for all three materials with 1,655.9 kg of raw materials, no safety stock for all three materials, a reorder point for all three materials with 526,17 kg of raw materials, and for the maximum inventory for all three materials with 1655.9 kg of raw materials.

Perancangan Sistem Informasi Persediaan Stok Barang Dan Penjualan Pada Toko Raja Sosis Menggunakan Bahasa Pemrograman PHP Dan Database MySQL

E-commerce as a means of selling frozen food at the King Sausage shop, because it is considered to save time and energy so it is more effective and efficient, there is no need to queue and just wait for the goods ordered to arrive at the buyer's place without having to leave the house just by using connection and internet and assist employees in processing sales transactions. uses the EOQ (Economic Order Quantity) method to determine the economic quantity for each order so as to minimize the total cost of inventory at the sausage king shop. It is hoped that the information system for stock inventory and sales at the King Sausage shop will provide maintenance and development for this system so that it can be used sustainably as long as it is needed.

Multi-Level Site Selection of Mobile Emergency Logistics Considering Safety Stocks

With the increasing frequency of emergencies in recent years, the emergency response capacity of the emergency management system needs to be improved. Based on safety stock strategy, this paper proposes a multilevel siting model on the topic of mobile emergency response. We modeled the emergency response needs during emergencies by incorporating the population distribution of each region. The uncertainty of emergencies is modeled by aggregating the frequency of crises in each region over the past 20 years. The site selection model minimizes contingency logistics costs that include transshipment, deployment, inventory, and safety stock costs. In this paper, the IA (Immune Algorithm) is optimized to solve the constructed emergency site selection model. The experiments on the model were carried out with data from the area of Chongqing, Sichuan Province. The number of logistics centers and distribution storage warehouses was tested. The influence of safety stock strategy on the total cost of emergency logistics was analyzed. The research results found that the cost of safety stock is negatively related to the cost of transshipment. In addition, the total cost of emergency logistics has a lower bound. Adding distribution and storage warehouses does not further reduce the total emergency logistics cost.

Arduino IOT Based Inventory Management System Using Load Cell and NodeMCU

Nowadays, everything is made simpler with information and communication technological advancements. It is preferable to track and monitor using devices rather than perform it manually. This resulted in the rapid growth of Internet of Things (IoT) technology and relevant markets. Low cost IoT products has made access to IoT much easier and desirable. These low cost IoT devices and related technologies are widely used in areas such as educational, transportation, tracking, inventory management and many more. The use of Arduino and RFID in the inventory management system lacks in some areas including hardware limitations. In conjunction to the limitation of using an Arduino and RFID technology, this project aims to develop an IoT based inventory management system that incorporates the uses of a NodeMCU and a load cell. In comparison of the NodeMCU to an Arduino, the NodeMCU stands out with the built in Wi-Fi module with much higher processor and additional properties of it being much smaller. While the use of a load cell is much more convenient as to suit all kinds of inventory management needs compared to the use of RFID that suits better to larger scale businesses with larger inventory and massive stocks. Towards the end, this project is expected to ease inventory management by the implementation of IoT with IoT Based Inventory Management System using Load Cell and NodeMCU. The project will generate the inventory count and automatically stores data in the cloud platform. These data can be accessed with internet connection. The project also alerts users when the inventory is low or high in balance. The output of the project is that the project’s working prototype was successfully developed. Overall, the project is a success as all the objectives of the project was successfully achieved.

Penerapan Algoritma Adaptive Response Rate Exponential Smoothing Terhadap Business Intelligence System

PT. XYZ is one of the companies in the field of furniture sales by offering its flagship product, namely spring bed. The company's business continues to grow every year, of course, the company must be able to complete its work quickly and precisely. One of the main problems of the company is that the increase in company sales is still not able to cover the company's expenses and sometimes the company still suffers losses. This happens because companies often make mistakes in purchasing product inventory stock. Not all types of spring beds sell well, so sometimes purchases are made of the type of spring bed that is not selling well, which results in stock accumulation and instability of the company's cash inflow and outflow. In this study, a Business Intelligence System was built, which is a form of information technology implementation to store, collect and analyze data into knowledge so that it can be used as prediction results. The prediction algorithm used in this research is the Adaptive Response Rate Exponential algorithm. The expected goal of this research is to build a Business Intelligence System that can calculate product sales predictions in the following month using the Adaptive Response Rate Exponential Smoothing (ARRES) algorithm. Based on the results of the MAPE test, it can be concluded that the percentage of prediction accuracy from the ARRES algorithm on the sales transaction data of PT. XYZ is 53.33% which is categorized as quite accurate and the percentage of prediction error from the ARRES method is 46.67% which is categorized as reasonable

IoT-based milk-run routing for manufacturing system: an application case in an automotive company

The Internet of Things (IoT) provides new opportunities to improve manufacturing lines’ performance and in-plant logistic processes. The digital milk-run system represents the new frontier to optimize material handling strategies but is still not fully exploited to address material distribution depending on the time slots required by the manufacturing lines. Therefore, to fill this gap, this paper investigates the actual integration of the milk-run system with an IoT system. An analytical model for planning a dynamic routing strategy for tugger trains to deliver the materials to different workstations of a production line has been developed. The proposed model provides a materials distribution consistent with the time slot required by the manufacturing line, ensuring the minimisation of the total distance of the routes. An algorithm developed in Python is proposed to solve the NP-hard problem (nondeterministic polynomial time problem). The model has been applied to a real case of a worldwide automotive company to validate and prove its efficacy and efficiency. Indeed, compared to the current in-plant logistic strategy, (i) the inventory stock of each workstation was ensured, (ii) the average utilization rate of the tugger trains’ fleet was improved, and (iii) the daily path was minimized.

Implementation of Stock Goods Data Mining Using the Apriori Algorithm

Stock inventory in the pharmacy should be well recorded. This is to provide the best service to customers/buyers. Buyers who come with empty results or the drug they want to buy will not feel disappointed, especially if they have made several purchases. This research implements data mining of drug stock inventory, where in the research carried out there are many empty and excess inventory items, resulting in less than optimal service. The research method, namely the survey research method, is a research method that is carried out using surveys or data collection through research respondents. The algorithm used in analyzing the data is the Apriori algorithm. The results of this study are the results of association rules based on predetermined parameters, namely a minimum support of 25% and a minimum confidence of 60%. The rule that is formed is that if consumers buy amoxicillin, they will buy mefenamic acid with a support value of 37% and a confidence of 183%.

Product-platform design and multi-period, multi-platform lot-sizing for hybrid manufacturing considering stochastic demand and processing time

In the era of mass customization, customer demand is fluctuating recurrently. To keep pace with this situation, the manufacturer wants to offer a bundle of products in a cost-effective way. The more variety of products is offered, the more fluctuation in demand is observed. Stochastic demand makes mass customization more challenging and expensive. The product platform concept is an effective and economical strategy for product variety management. This concept can help the manufacturer to deal with frequent updates of customer requirements. Moreover, using different platforms for different periods considering stochastic demand is more cost-efficient than having a single platform for all periods. Integrating hybrid (Additive and Subtractive) manufacturing and product platform concepts make it more adaptable for manufacturers. Since there are more variants, the processing time is different for each variant. The stochastic production environment makes the situation more complex. Thus, this study focuses on developing a mixed integer linear programming (MILP) model to minimize manufacturing and holding costs along with considering multi-period stochastic demand. The novelty of this model is to satisfy a certain service level by incorporating inventory and safety stock. An exact optimization solver, Gurobi, is used to find optimal solutions for the proposed model. Finally, a case study of a guiding bushes family is used as an illustrative example.

Modeling and Analyzing the Inventory Level for Demand Uncertainty in the VUCA World: Evidence From Biomedical Manufacturer

As the world is witnessing unprecedented events such as the COVID-19 pandemic, we live in a volatile, uncertain, complex, ambiguity (VUCA) world. Where volatility in supplies, Uncertainty in demand, Complexity in getting the products, and Ambiguity in understanding the issues. Such a scenario constitutes a VUCA world, and inventory positioning is no exception. Inventory positioning manages the safety stock across echelons to maintain customer service levels undersupply or demand uncertainties. Therefore, this article focuses on optimizing the inventory levels in demand uncertainty and supply complexity through inventory positioning and making reliable forecasts using machine learning for biomedical equipment, especially knee implants. The product flow is mapped through a discrete event simulation model by considering a biechelon supply chain. The parameters like reorder point, order quantity, supply lead time, and inventory costs are considered, and Arena modelled and simulated inventory replenishment. They are optimized with in-built OptQuest to minimize back orders and total costs. The model determines the safety stock inventories positioned at both echelons to achieve service level constraints. The uncertainty in demand is the root cause of the abovementioned issues and may be reduced through more reliable forecasts.

Current Stock Monitoring System with Expiry Alerts

The main objective of this project is manage a stock for a Developing a “CURRENT STOCK MONITORING SYSTEM WITH EXPIRY ALERTS” is illustrates the designing and implementation of a Current Stock Monitoring Management System with expiry alert system. The primary aim of is to improve accuracy and enhance safety and efficiency in the pharmaceutical store. Today management is one of the most essential features of all form. The Management provides sophistication toper form any kind of task in a particular form. This is pharmacy management system; it is used to manage most pharmacy related activities in the pharmacy. computerized system designed for user to manage the stock inventory and monitoring the stock facility. The stand alone stock inventory system provides alert of expire date and minimum quantity of each product and also searching algorithm technique applied in this system. Are search and analysis on the current system and searching technique was done to get better understanding of the system. The RAD methodology was used in this project development implements iterative development which is suitable for standalone applications requirements that changes from time to time. Testing is done every phase of the development life cycle to make sure that the system working properly.

Perhitungan Pengendalian Persediaan Fast Moving Spare Part Dengan Metode Min-Max Stock

Maintenance is an effort to maintain a heavy equipment unit to keep it in good condition. One of the techniques to maintain unit performance is by carrying out maintenance management which is a combination of various activities such as monitoring, scheduling, repairing, and inventory control. One part of maintenance management is inventory management which aims to ensure the availability of spare parts in the warehouse so that it can increase the efficiency of maintenance time. The purpose of this study is to calculate the supply of fast-moving spare parts, especially oil filters and diesel filters using the Min-Max Stock method at PT Armada Hada Graha Basecamp Kelontong. The research used a comparative quantitative method utilizing spare parts usage data from January to March 2022 and inventory stock data on March 2022. From the calculation results it can be concluded that the percentage of filter inventory between the minimum and maximum stock values ​​is 7%. It happens due to several factors, namely, materials, methods, machines, and the environment.

Goods Inventory System Using Visual Basic.Net at PT. Mitra New Grain with Waterfall Method

This research is motivated by the process of making raw material inventory stocks that still use paper and have not been connected to the database. The problems that arise in the company are regarding the stock of goods, the process of reporting incoming and outgoing goods is still by handwriting which results in calculation errors and differences between physical data and record data. The design of this raw material information system uses the Visual Basic.Net programming language and SQL Server as a database. The system development model used is the waterfall model, analysis and design using diagrams contained in UML. While data collection techniques use research methods by means of observation, interviews, and literature studies. The purpose of this research is to design a raw material inventory information system that can support all incoming and outgoing inventory activities in the company. The result of this research is a desktop-based inventory system application that can assist in processing inventory data and reporting data.

Analisis Sistem Informasi Inventory Menggunakan Metode Single Moving Averange Pada PT. Inkolanggeng Makmur Jakarta

Analisis Sistem Informasi Inventory Menggunakan Metode Single Moving Averange Pada PT. Inkolanggeng Makmur Jakarta

Assessing the city-level material stocks in landfills and the landfill mining potential of China

Landfill mining has become an emerging issue in urban metabolism research and environmental remediation practices. Comprehensive understanding of the quantity and distribution of material stocks in landfills, as well as identifying hotspots of landfill mining potential, is of crucial importance. However, high-resolution datasets and systematic analytical tools remain insufficient. This study established a time-series landfill material stock inventory at prefecture level in China. An evaluation system for mining potential of landfills at prefecture level was then constructed using an integrated expert scoring and entropy weight method, based on ten indicators across five dimensions, including environmental impact, energy recovery, resource cycling, economic cost, and social aspect. The results show that over the past twenty years, the material stock in landfills was 2321.07 Tg (106 tons) in China, among which, soil-like materials, ash & stone and plastic & rubber were the three largest fractions, accounting for 61.06 wt%, 18.96 wt%, and 12.69 wt% of the total stock. Regional differences in landfill mining potential were found to be significant, with South China presenting the largest mining potential, while Southwest China showed the lowest. Cities with better economic development in China show the possibility to have greater landfill mining potential. This study established a methodology for the assessment of landfill mining potential for China or other countries, and provided scientific evidences for formulating regional-specific policies on landfill mining in China.

PENERAPAN LEAN HEALTHCARE DALAM PENGELOLAAN MANAJEMEN KEPERAWATAN DI RAWAT INAP DHAHA RSUD GAMBIRAN KOTA KEDIRI

Introduction & aim: Lean is a new breakthrough in the era of digitalization which is a process improvement method used to improve service products, high use of consumables (hereinafter referred to as BHP) in hospitals, stock inventory of drugs and medical devices in the treatment room every month and found a buildup of inventory of consumables. This community service aimed to identify the application of lean healthcare applications in the BHP inventory for nursing management. Method of Activity: In finding the root of the problem using fishbone diagrams, the scoring method was to prioritize issues to be resolved using SWOT Analysis. This community service was conducted in the Dhaha inpatient room of Gambiran Hospital, Kediri City with 22 medical and 2 non-medical personnel. Results: The application of lean healthcare in the Dhaha inpatient room, material management, pharmaceutical supplies, and household logistics was carried out continuously according to what nurses needed. However, after the implementation of lean healthcare, it begins with the implementation of 5S which regulates supplies according to patient needs, assigns items that are always used in patient services according to nurses every shift not every room, and puts or parks in places that are easy to reach. Efficient from inventory adjustments in the inpatient room in the form of Rp. 1,035,566. Discussion: The implementation of Lean Health Care "KANBAN" is an important thing to do sustainably because quality service is also obtained from effective and efficient services including inventory management.

Waterfall Model Inventory Information System at Alvinda Store Karawang

Stock name is a process for calculating incoming and outgoing goods by inventory bookkeeping records. Manual calculations will take a very long time, and the risk of error is very high, so the presentation of the inventory report is hampered because it does not match the predetermined time. The stock opname information system with the Waterfall method can make it easier to accurately calculate the amount of stock inventory and can minimize the counting time to be faster. So that inventory reports can be generated quickly, accurately and on time.

Assessment of the resource base of Rumex tianschanicus Losinsk. in the mountain regions of southeastern Kazakhstan

Inventory of stock economically valuable plant species is one of the urgent tasks in the regional cadastral assessing of plant resources. The results of this will be applied to conduct state monitoring and the flora cadastre in the Republic of Kazakhstan. Genus Rumex L. belongs to Polygonaceae Juss. family and represented by 27 species in the flora of Kazakhstan including 15 medicinal which used in folk and official medicine. For the first time undertaken a cadastre assessment of current ecological state of the flora and plant resources in Almaty region, the stocks of plant raw material of the valuable medicinal Rumex tianschanicus, have been identified and taken into account in 2021-2022 years on the 3 floristic territories (24. Dzhungarsky Alatau, 25. Zailiysky Kungei Alatau, 25a. Ketmen-Terskey Alatau) and 4 administrative (Eskeldinsky, Kegensky, Raiymbeksky, Uigursky) districts. The resource survey of the territories carried out by a route-reconnaissance method using generally accepted resource-study and geobotanical methods. On the surveyed territory the total operational reserve of air-dry underground part of Rumex tianschanicus was 169.5 tons on 113.3 hectares with a total volume of possible annual harvesting of 17.0 tons of air-dry plant raw materials. For commercial harvesting thickets were isolated ridges of Ketmen (Uigur district) and Terskey Alatau (Raiymbek district) which located within 25a floristic region in the southeast of the Almaty region.

Earthquake Scenarios for Quito, Ecuador; Cali, Colombia; and Santiago De Los Caballeros, Dominican Republic

Abstract Earthquake risk associated with Quito, Ecuador; Cali, Colombia; and Santiago de los Caballeros, Dominican Republic is examined by generating a set of hypothetical earthquake scenarios considering seismic sources, recent seismicity, and major historical earthquakes recorded in the vicinity. In this study, particular focus is given to the development of earthquake scenarios for use in emergency planning in each city as well as stimulating discussion with respect to addressing the gaps in current understanding of built stock inventory and their vulnerability when subjected to strong shaking. Exposure and vulnerability models from the Global Earthquake Model foundation, hazard and local site information available for the cities, and the U.S. Geological Survey near-real-time products are utilized to estimate potential consequences for postearthquake response planning. Results showed that the historic city centers remain the most susceptible to experiencing severe damage resulting in widespread casualties. Similarly, the scenarios highlight areas susceptible to shaking induced ground failure hazards, which may pose additional challenges when responding to such earthquakes. Moderate earthquakes originating from nearby seismic sources, for example, Quito fault system for Quito or the Septentrional fault zone in the case of Santiago de Los Caballeros, could potentially be of greater consequence in terms of direct economic impact and disruption to the city when compared to very large distant subduction interface earthquakes.

A sustainable pollution control fuzzy production inventory model with imperfect and breakable items through Pontryagin Maximum principle

In present world the major cause of global warming and climate change are emission of carbon and greenhouse gas. Governments and policymakers around the world want to put their best efforts to control the pollution and climate change to save our environment. To reduce greenhouse gas emissions Government and policymakers takes carbon tax policy on carbon emission. Also in real world uncertainty is a pervasive phenomenon. Humans have a significant ability to make logical decisions based on uncertain information. For this purpose, we are developing a pollution control fuzzy production inventory model with imperfect and break-ability items under preservation technology investment and carbon tax policy. In this model, the break-ability rate is dependent on inventory level as the break-ability rate of breakable items depends on the collected stress of inventory stock level. Here the unit production cost is dependent on raw material cost, wear-tear cost and development cost. Carbon emission is controlled by investing in carbon reduction technology and a fraction of product items are imperfect. In this study demand of the product depends on selling price and inventory stock level of product. Finally, this optimal control problem solved by using Pontryagin Maximum principle and the optimal results are illustrated graphically and numerically using MATLAB software. Subsequently, some sensitivity analysis is investigated as the impact of parameters on total profit.