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Journal articles on the topic 'Accuracy of inventory'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Ernst, Ricardo, José-Luis Guerrero, and Alan Roshwalb. "Maintaining Inventory System Accuracy." International Journal of Purchasing and Materials Management 28, no. 3 (1992): 33–37. http://dx.doi.org/10.1111/j.1745-493x.1992.tb00569.x.

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2

Kumar Kande, Santosh. "The Role of Asset Inventory Accuracy in Vulnerability Remediation Effectiveness." International Journal of Science and Research (IJSR) 13, no. 3 (2024): 1953–55. https://doi.org/10.21275/sr241225091008.

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3

Campos, Iury A. S., and Rickardo L. R. Gomes. "Materials Management Practices for Reducing Warehouse Inventory Levels in A Metallurgical Industry: A Case Study." International Journal Of Engineering Research And Development 20, no. 03 (2024): 174–79. https://doi.org/10.5281/zenodo.10865831.

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In the current scenario of intense competitiveness among companies, the inventory management area iscurrently perceived as strategic for achieving global goals within organizations, given that inventoriesrepresent a significant portion of the assets and capital invested in materials. Therefore, the investigation aimsto explore the application of inventory management tools in a metallurgical industry, seeking to understand howthe control of material inventory levels is conducted, while evaluating performance indicators and achievedoutcomes. For the development of this study, analyses of Warehou

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4

Long, Brian G., Greg Andrews, You-Gan Wang, and Suharsono. "Sampling accuracy of reef resource inventory technique." Coral Reefs 23, no. 3 (2004): 378–85. http://dx.doi.org/10.1007/s00338-004-0403-0.

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5

Jamila, Zainab. "Warehouse Automation and Inventory Accuracy in Nigeria." International Journal of Supply Chain and Logistics 9, no. 2 (2025): 53–62. https://doi.org/10.47941/ijscl.2532.

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Purpose: The purpose of this article was to analyze warehouse automation and inventory accuracy in Nigeria. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Recent studies in Nigeria indicate that warehouse automation improves inventor

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Borecki, Tomasz, Bogdan Brzeziecki, Edward Stępień, and Roman Wójcik. "Development of forest inventory methods in multifunctional forest management." Folia Forestalia Polonica, Series A - Forestry 57 (2) (December 1, 2015): 120–25. https://doi.org/10.1515/ffp-2015-0012.

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The demand for wide range and precise information on forests promotes continuous development of forest inventory methods, owing to the fact that compilation of reliable data is prerequisite not only for improving forest management schedules but also planning land use and natural environment management. In the reality of contemporary forestry, a requirement to improve forest inventory methods stems from obligation to acquire information on broadly understood issues of forestry as well as the protection of nature and environment. The paper points out to the essential steps, as said by the author

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Arifin, Rinei, and Siti Zubaidah Ismail. "Investigation of Inventory Record Accuracy in Product-Service System." Journal of Modern Manufacturing Systems and Technology 2 (March 26, 2019): 93–105. http://dx.doi.org/10.15282/jmmst.v2i1.1806.

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In this paper we examine Product-Service System (PSS) in manufacturing industries application to inventory control in Malaysian Elaeis Guineensis or known as palm oil industries. We are particularly interested in the record of inventory accuracy for palm oil tree, fresh fruit bunch (FFB) and palm oil. If the inventory is uncontrolled or not accurate, the production will face problems to meet customers demand. We focus not just on inventory activities themselves, but also the key linkages between production, market, supply chain, and oil production. These linkages are examined using generic mod

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8

Lin, Chen-Miao, Bingxuan Lin, and Henry Schwarzbach. "How does inventory management affect analyst forecast accuracy." Pressacademia 8, no. 1 (2019): 17–27. http://dx.doi.org/10.17261/pressacademia.2019.1012.

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9

Hardgrave, Bill C., John Aloysius, and Sandeep Goyal. "Does RFID improve inventory accuracy? A preliminary analysis." International Journal of RF Technologies: Research and Applications 1, no. 1 (2009): 44–56. http://dx.doi.org/10.1080/17545730802338333.

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10

Sudarmi, Elisabeth, and Widodo Sunaryo. "Enhancing Inventory Accuracy and Operational Performance with ERP." Sinergi International Journal of Logistics 2, no. 2 (2024): 1–14. https://doi.org/10.61194/sijl.v2i2.622.

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This narrative review explores the role of Enterprise Resource Planning (ERP) systems in enhancing inventory management across industries. Drawing from empirical studies, theoretical reviews, and case applications over the past 15 years, it highlights how ERP systems improve operational efficiency, inventory accuracy, and supply chain responsiveness. Key benefits include real-time data access, reduced manual errors, automation, and integration, with technologies like IoT and machine learning further supporting decision-making and coordination. Despite these advantages, challenges such as high

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11

Olha Shapoval. "Methodology for assessing the accuracy of inventory results." International Journal of Science and Research Archive 16, no. 1 (2025): 223–29. https://doi.org/10.30574/ijsra.2025.16.1.2002.

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This article highlights the need to develop an objective methodology for evaluating the accuracy of inventory results, given the crucial roles that reliable data play in financial reporting and inventory management. The relevance of this research is also motivated by the persistent low levels of accuracy, which have led to significant financial losses and wasted energy. This work will develop a statistically based, technology-supported approach to inventory accuracy assessment that can pinpoint all types of errors quantitative, qualitative, and document-related in real-time. The novelty of the

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12

Grīnvalds, Ainārs. "The Accuracy of Standwise Forest Inventory in Mature Stands." Proceedings of the Latvia University of Agriculture 32, no. 1 (2014): 2–8. http://dx.doi.org/10.2478/plua-2014-0007.

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Abstract Traditionally forest resources are estimated in each compartment or stand with ocular standwise forest inventory. However, this inventory technique has shortages with measurement accuracy. In the study the accuracy of the standwise forest inventory was estimated by comparing the growing stock volume of the standwise inventory with the accurate (instrumental) re-measurements. Comparison was done with 4515 mature stands of pine (Pinus sylvestris L.), spruce (Picea abies (L.) Karst.), birch (Betula spp.), aspen (Populus tremula L.) and black alder (Alnus glutinosa L.). The stands’ measur

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13

Tundura, Lilian. "Effect of Inventory Control Strategies on Inventory Record Accuracy in Kenya Power Company, Nakuru." Journal of Investment and Management 5, no. 5 (2016): 82. http://dx.doi.org/10.11648/j.jim.20160505.16.

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14

Sreerambabu, Dr J., Mr M. Mohammed Riyaz, Mr D. Rajkumar, and Mr Tamilarasan D. "College Hostel Inventory Management System." International Journal for Research in Applied Science and Engineering Technology 11, no. 8 (2023): 560–66. http://dx.doi.org/10.22214/ijraset.2023.55009.

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Abstract: The Hostel Inventory Management System introduces an innovative web and Android application to revolutionize hostel inventory operations, maximizing efficiency, streamlining processes, and enabling data-driven decision-making. The userfriendly interface empowers administrators to manage inventory seamlessly, with real-time data recording and transparent stock management. The manual mess bill calculation is simplified using distribution reports, reducing errors, and enhancing billing accuracy, and resident satisfaction. Comprehensive reporting on purchases, distributions, and stock le

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15

Ayantoyinbo, Dosunmu, and Omorinde. "Econometric Study: E-commerce Adoption on Inventory Management for Manufacturing Companies in Nigeria." South Asian Journal of Social Studies and Economics 21, no. 4 (2024): 10–21. http://dx.doi.org/10.9734/sajsse/2024/v21i4796.

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The study examined the effect of Business-to-Business E-commerce adoption on inventory management using manufacturing companies in Nigeria under the category of consumer goods as a case study. Inefficient inventory management leading to a rise in costs and a decrease in customer satisfaction level is one of the major challenges encountered by Nigerian manufacturing companies but this can be resolved through the implementation of e-commerce hence the study focussed on inventory management variables which are; inventory accuracy, stockout frequency, inventory turnover rate, demand forecasting ac

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16

Murgaš, Vlastimil, Ivan Sačkov, Maroš Sedliak, Daniel Tunák, and František Chudý. "Assessing horizontal accuracy of inventory plots in forests with different mix of tree species composition and development stage." Journal of Forest Science 64, No. 11 (2018): 478–85. http://dx.doi.org/10.17221/92/2018-jfs.

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Global navigation satellite systems (GNSS) have a wide range of applications in forest industry, including forest inventory. In this study, the horizontal accuracy of 45 inventory plots in different forest environments and 5 inventory plots under open sky conditions were examined. The inventory plots were located using a mapping-grade GNSS receiver during leaf-on season in 2017. True coordinates of the plot centres were acquired using a survey-grade GNSS receiver during leaf-off season in 2018. A study was conducted across a range of forest conditions in the forest unit Vígľaš, which is locate

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17

Ahirwar, Aarti. "AI-Powered Inventory Solutions: Enhancing Accuracy and Efficiency in Supply Chains." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem51068.

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In today’s rapidly changing business environment, traditional inventory management practices are proving inadequate in addressing dynamic market demands and supply chain disruptions. This research paper explores the transformative potential of Artificial Intelligence (AI) in revolutionizing inventory management systems across manufacturing and retail industries. It critically analyzes how AI tools—such as machine learning, predictive analytics, automation, and digital twins—enhance inventory accuracy, forecasting precision, and overall operational efficiency. Through case studies involving glo

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18

Iverson, Grant L., and Ronald Remick. "Diagnostic Accuracy of the British Columbia Major Depression Inventory." Psychological Reports 95, no. 3_suppl (2004): 1241–47. http://dx.doi.org/10.2466/pr0.95.3f.1241-1247.

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The purpose of this study was to examine the diagnostic accuracy and clinical usefulness of the British Columbia Major Depression Inventory. Participants were 62 patients with depression referred by their psychiatrist or family physician, 19 general medical outpatients with no psychiatric problems referred by their family physicians, and 49 community control subjects. Mean age for the control subjects was 50.2 yr. ( SD = 11.8), and mean education was 14.6 yr. ( SD = 2.8). Approximately 59% were women. Mean age for the patients with depression was 41.1 yr. ( SD = 12.5), and mean education was 1

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19

IVERSON, GRANT L. "DIAGNOSTIC ACCURACY OF THE BRITISH COLUMBIA MAJOR DEPRESSION INVENTORY." Psychological Reports 95, no. 7 (2004): 1241. http://dx.doi.org/10.2466/pr0.95.7.1241-1247.

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20

Kitahara, Fumiaki, Nobuya Mizoue, Tsuyoshi Kajisa, Takuhiko Murakami, and Shigejiro Yoshida. "Positional Accuracy of National Forest Inventory Plots in Japan." Journal of Forest Planning 15, no. 2 (2010): 73–79. http://dx.doi.org/10.20659/jfp.15.2_73.

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21

Wickramasinghe, N., D. Dissanayake, and G. Abeywardena. "Diagnostic accuracy of the Maslach Burnout Inventory-Student Survey." International Journal of Psychophysiology 131 (October 2018): S94—S95. http://dx.doi.org/10.1016/j.ijpsycho.2018.07.264.

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22

Hellström, Daniel, and Mathias Wiberg. "Improving inventory accuracy using RFID technology: a case study." Assembly Automation 30, no. 4 (2010): 345–51. http://dx.doi.org/10.1108/01445151011075807.

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23

Deepika, O. "Inventory Backorder Prediction." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (2023): 763–66. http://dx.doi.org/10.22214/ijraset.2023.53461.

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Abstract: Product going to out of stock is a common problem in supply and chain scenario that comes under unpredictable risk in demand and supply. We aim to use Machine Learning predictive models in area of the business processes in decision making. By predicting products, backorder predictive models provides flexibility to decision authority, better clarity in the process, and helps in maintaining greater accuracy. The machine learning models that are tree based are chosen to predict material backordering. The backorders of products are predicted in this project by considering various models.

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24

R, Parthiban, Bincy S, Ilamathi D, and Deva Priya T. "Automated Inventory Tracking and Alert System." Journal of Electrical Engineering and Automation 6, no. 4 (2025): 300–314. https://doi.org/10.36548/jeea.2024.4.003.

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The research is on inventory management systems, focusing on IoT-based solutions, RFID technology, and machine learning applications. The study examines various systems, including automated inventory tracking, real-time monitoring, and predictive analytics for demand forecasting. The survey highlights the benefits of these systems, such as improved inventory accuracy, reduced stockouts, and enhanced customer satisfaction. However, it also discusses challenges and limitations, including dependency on network connectivity, initial setup costs, and data accuracy concerns. This survey provides a c

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25

Mohd Mahzan, Iman Haddad Qaisara Dhia, and Khai Loon Lee. "Elimination of Misconduct in Manual Counting Process as an Improvement of Inventory Accuracy in A Manufacturing Company." International Journal of Industrial Management 10 (March 5, 2021): 140–50. http://dx.doi.org/10.15282/ijim.10.1.2021.6051.

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Managing inventory is crucial especially for manufacturing companies as it has a direct influence on profits of the company. In order to have an efficient inventory management, inventory accuracy need to be achieved and this can be achieved by leveraging technologies and techniques that can minimize the human error. The objective of this study is to investigate the factors affecting inventory inaccuracy in Factory 21 of ABC manufacturing company. This study reveals that the inventory inaccuracy is influenced by the order received in the factory, which is due to the human misconduct during the

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26

Jannah, Ghina Raodatul, Andi Ghizzania Sirih Bittara, Alvin Mas Udin, Asmaul Husna Nasrullah, and Fhatiah Adiba. "The Determination of Electronic Goods Inventory at Rahmah Store Using the Fuzzy Tsukamoto Method." Media of Computer Science 1, no. 2 (2024): 91–98. https://doi.org/10.69616/mcs.v1i2.204.

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Toko Rahmah is faced with the challenge of determining the optimal inventory of electronic goods to avoid excess or shortage of inventory. The uncertainty of demand and large sales often leads to inefficient inventory management. This study aims to apply the Tsukamoto fuzzy method in determining the optimal inventory of electronic goods at Toko Rahmah. Using this method will increase the accuracy of managing inventory and reduce the risk of excess or shortage of inventory. Therefore, in this study, the Tsukamoto fuzzy method is used to model and overcome the uncertainty of electronic goods inv

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27

Gattani,, Ayush. "A Study on Smart Inventory Management in E-Commerce Warehousing: A Six Sigma-Based Process Improvement Framework." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–7. https://doi.org/10.55041/isjem03971.

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Abstract: The rapid rise of e-commerce has increased pressure on warehousing operations, where inventory accuracy is crucial for timely order fulfillment and cost control. Despite advanced Warehouse Management Systems (WMS), issues like misplacements, bin overstuffing, and picking errors persist. This study applies the Six Sigma DMAIC framework to analyze and improve inventory accuracy in e-commerce warehousing, using insights from a leading Indian e-commerce company and simulated operational data. Key issues were identified using Pareto analysis, with inventory misplacement accounting for ove

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28

Pal, Subharun. "Advancements in AI-Enhanced Just-In-Time Inventory: Elevating Demand Forecasting Accuracy." International Journal for Research in Applied Science and Engineering Technology 11, no. 11 (2023): 282–89. http://dx.doi.org/10.22214/ijraset.2023.56503.

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The landscape of global supply chains is undergoing a transformation characterized by increasing complexity and the need for agile response to demand fluctuations. At the forefront of addressing these challenges is the strategic alignment of inventory levels with volatile demand, a task that has become more sophisticated within the Just-In-Time (JIT) inventory management paradigm. This paper explores the integration of Artificial Intelligence (AI) into JIT systems, with a focus on enhancing the accuracy of demand forecasting—a critical component for inventory optimization. We present a groundb

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Deivanayagampillai, Nagarajan, Thangavel Bhuvaneswari, and Yasothei Suppiah. "Intelligent inventory prediction: A machine learning framework using random forest for inventory forecasting." Edelweiss Applied Science and Technology 9, no. 4 (2025): 1795–807. https://doi.org/10.55214/25768484.v9i4.6383.

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This study proposes a machine learning-based inventory forecasting strategy using random forest classifiers to improve demand prediction and anomaly detection in retail sales. It aims to address the limitations of traditional inventory management by capturing nonlinear demand dynamics and interdependencies. The model is developed and validated using real-world inventory data, with the United Kingdom as the primary market. Data preprocessing includes handling 135,080 missing CustomerID fields, 1,454 missing Description fields, and correcting anomalies in Quantity and Unit Price. The random fore

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30

Nwaiku, Mitaire Sunday, and Jones Ejechi. "Inventory Management Practices and Organizational Productivity in Nigerian Manufacturing Firms." Journal of Entrepreneurship and Business 10, no. 2 (2022): 1–16. http://dx.doi.org/10.17687/jeb.v10i2.863.

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This study examined the relationship between inventory management practices and productivity of selected manufacturing firms in Nigeria. The inventory management practices examined include inventory record accuracy, lean inventory system, buffer stock management and Information and Communication Technology. In addition, organizational productivity was measured along two dimensions namely: organizational effectiveness and organizational efficiency. A survey research design was adopted for the study. The population of the study comprises employees in the following departments – commercial, finan

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Rizad Md Sapry, Hairul, Lorio L’ wiey Anak Tawi, Abd Rahman Ahmad, and Shathees Baskaran. "The Effectiveness of MRP System to Forecast the Accuracy Inventory Requirement." International Journal of Engineering & Technology 7, no. 4.1 (2018): 90. http://dx.doi.org/10.14419/ijet.v7i4.1.28232.

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The implementation of MRP systems play a crucial role in today's manufacturing process in providing valuable information not only to both marketing and manufacturing team, but the organization as a whole. Yet, MRP system does not possess the capability of doing everything. There are few limitations within MRP system in relation to flexibility and adaptability to the changes of the external environment. The objective of the study is to investigate the capability of MRP system in providing an accurate forecast for the inventory requirement. The study was conducted through a qualitative case stud

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32

Fouad, Nadya A., and Jo-Ida C. Hansen. "Cross-Cultural Predictive Accuracy of the Strong-Campbell Interest Inventory." Measurement and Evaluation in Counseling and Development 20, no. 1 (1987): 3–10. http://dx.doi.org/10.1080/07481756.1987.12022842.

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33

Swanson, Jane L., Paul A. Gore, Wade Leuwerke, Catalina D’Achiardi, Jorie Hitch Edwards, and Jared Edwards. "Accuracy in Recalling Interest Inventory Information at Three Time Intervals." Measurement and Evaluation in Counseling and Development 38, no. 4 (2006): 236–46. http://dx.doi.org/10.1080/07481756.2006.11909785.

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34

Hand, Cynthia G., Robert P. Archer, Richard W. Handel, and Johnathan D. Forbey. "The Classification Accuracy of the Minnesota Multiphasic Personality Inventory–Adolescent." Assessment 14, no. 1 (2007): 80–85. http://dx.doi.org/10.1177/1073191106291815.

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35

Uçkun, Canan, Fikri Karaesmen, and Selçuk Savaş. "Investment in improved inventory accuracy in a decentralized supply chain." International Journal of Production Economics 113, no. 2 (2008): 546–66. http://dx.doi.org/10.1016/j.ijpe.2007.10.012.

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Taghavi, M., S. Cautenet, and J. Arteta. "Impact of a highly detailed emission inventory on modeling accuracy." Atmospheric Research 74, no. 1-4 (2005): 65–88. http://dx.doi.org/10.1016/j.atmosres.2004.06.007.

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37

Kovyazin, V. F., O. A. Pasko, O. Y. Lepikhina, and V. E. Trushnikov. "Assessment of the forest land inventory accuracy using aerial laser scanning." Geodesy and Cartography 984, no. 6 (2022): 54–63. http://dx.doi.org/10.22389/0016-7126-2022-984-6-54-63.

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The use of forest resources in the context of globalized markets and implementing new technologies, enhanced competition and increasing environmental restrictions require reliable information. The method of aerial laser scanning opens up great prospects for the state inventory of forests. It is successfully used in many sectors of the economy, but it has not been worked out for state forest inventory. The purpose of the study is assessing the possibility of using aerial laser scanning within the framework of current regulations. The object of the study is a forest area of 11 840 hectares in th

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38

Lestari, Widia, Bachtiar Efendi, and Wiwin Handoko. "ANALISIS DAN PERANCANGAN SISTEM INVENTORY BERBASIS WEB DI PT. AGRO PUTRA LESTARI." J-Com (Journal of Computer) 4, no. 3 (2024): 319–28. https://doi.org/10.33330/j-com.v4i3.3311.

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industry. PT. Agro Putra Lestari experienced problems in the process of recording incoming and outgoing goods as well as checking stock of goods which was still done manually. This manual process is prone to errors and data redundancy which can cause major problems in inventory management. Therefore, it is necessary to develop a web-based inventory system to overcome this problem. This inventory system was designed using the CodeIgniter 3 framework to build dynamic, fast and easy web applications, and uses MySQL as the data storage medium. Data collection techniques through direct observation

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Olugbenga Ayomide, Madamidola, Daramola Oladunni Abosede, Akintola Kolawole Gabriel, Akinwonmi, Akintoba Emmanuel, and Adeboje, Olawale Timothy. "A Framework for an IoT-enabled Intelligent Inventory Management System." International Journal of Advances in Engineering and Management 6, no. 10 (2024): 234–43. https://doi.org/10.35629/5252-0610234243.

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The rapid advancement of Internet of Things (IoT) technology has opened new frontiers in inventory management by enabling real-time, data-driven decision-making. This paper presents a comprehensive framework for an IoT-enabled intelligent inventory management system (IIMS) that integrates weight sensors, Radio Frequency Identification (RFID), computer vision, and neurofuzzy logic for optimizing inventory control. The proposed system aims to enhance inventory monitoring accuracy, automate item identification and placement verification, and optimize reorder levels. Weight sensors track inventory

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Usman, Syahrul, Jeffry Jeffry, and Firman Aziz. "FORECASTING PENGENDALIAN PERSEDIAAN SUKU CADANG MENGGUNAKAN METODE NAIVE." AL-ULUM: JURNAL SAINS DAN TEKNOLOGI 8, no. 1 (2022): 47. http://dx.doi.org/10.31602/ajst.v8i1.8840.

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Inventory control is an important thing that must be considered by every business actor, especially in the retail sector, too much inventory results in increased and inefficient sales time and can even result inlosses. the need to estimate demand and inventory Stock is very necessary to minimize over stock and also under stock to reduce the risk of loss, the ability of retail business actors to predict demand is certainly very helpful in carrying out good inventory management, utilization of transaction data in a certain amount using machine learning methods can be one approach to see consumer

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Prastiya, Denny Suci, and Rossi Septy Wahyuni. "Artificial Neural Network Model For Optimization of Forecasting Material Inventory." Jurnal Teknik Industri 25, no. 2 (2024): 173–88. http://dx.doi.org/10.22219/jtiumm.vol25.no2.173-188.

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The increasing competition in the fast-moving consumer goods (FMCG) industry leads to demand fluctuations, negatively impacting the accuracy of demand forecasts and determining optimal lot sizes in material inventory planning. Many companies struggle to adopt appropriate forecasting models, resulting in poor accuracy and higher material costs. This study aims to develop an integrated model for forecasting and material planning using simulation. The artificial neural network (ANN) method is proposed to improve forecasting accuracy, with performance evaluated through mean percentage error (MAPE)

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Michael William Tjia, David, and Jackri Hendrik. "Web-Based Inventory System Design Using Rapid Application Development Method at PT. ALFA SCORPII." Journal of Artificial Intelligence and Engineering Applications (JAIEA) 4, no. 3 (2025): 2151–56. https://doi.org/10.59934/jaiea.v4i3.1121.

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This study designs a web-based inventory system for PT. Alfa Scorpii using the Rapid Application Development (RAD) method. The previous manual system led to data errors and slow processes. The new system features real-time recording, multi-level approval, and role-based access management. Implementation results show improved accuracy and efficiency. This paper discusses the RAD stages, system design, and suggestions for future development. The web-based inventory system at PT. Alfa Scorpii using the RAD method improves the efficiency and accuracy of inventory management.

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Tarish, Hiba A. "Optimized computational techniques-based inventory control process in supply chain management." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (2021): 374–82. http://dx.doi.org/10.17762/turcomat.v12i6.1402.

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Now-a-days, supply chain management is one of the crucial factors in business for identifying the flow of goods, raw material storage, movement of products and inventory process so on. The main aim of the supply chain management process is to provide the valuable business services, infrastructure, logistic control and inventory control to the business for improving the business. Among the various supply chain factors, inventory control is one of the difficult tasks in supply chain management process because of high cost inventory, consistent stockouts, low rate of inventory turnover, high valu

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Lei, Tengfei, Rita Yi Man Li, Nuttapong Jotikastira, Haiyan Fu, and Cong Wang. "Prediction for the Inventory Management Chaotic Complexity System Based on the Deep Neural Network Algorithm." Complexity 2023 (May 12, 2023): 1–11. http://dx.doi.org/10.1155/2023/9369888.

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Precise inventory prediction is the key to goods inventory and safety management. Accurate inventory prediction improves enterprises’ production efficiency. It is also essential to control costs and optimize the supply chain’s performance. Nevertheless, the complex inventory data are often chaotic and nonlinear; high data complexity raises the accuracy prediction difficulty. This study simulated inventory records by using the dynamics inventory management system. Four deep neural network models trained the data: short-term memory neural network (LSTM), convolutional neural network-long short-t

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Manurung, Kiki Hariani, and Julius Santony. "Simulasi Pengadaan Barang menggunakan Metode Monte Carlo." Jurnal Sistim Informasi dan Teknologi 1, no. 3 (2019): 7–11. http://dx.doi.org/10.35134/jsisfotek.v1i3.3.

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Inventory is a very important aspect for the development of a company. Inventory management is needed to determine the inventory of goods needed within a certain period so that market demand can be fulfilled. The data used in this study are inventory data from 2016 to 2018. Data processing in this study uses the Monte Carlo algorithm to predict procurement data. In accelerating data processing, this research applies a Web-based program with the PHP (Hypertext Processor) programming language. The results of testing this method are to obtain predictions of the supply of goods in a certain period

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Li, Yue, Yonglin Zhang, Jinxiang Cheng, et al. "Comparative Analysis, Use Recommendations, and Application Cases of Methods for Develop Ship Emission Inventories." Atmosphere 13, no. 8 (2022): 1224. http://dx.doi.org/10.3390/atmos13081224.

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Ship exhaust emissions have been considered as a significant source of air pollution that has an adverse impact on the global climate and human health. It is of vital importance to create an accurate ship emission inventory for the purpose of formulating effective control measures. A wide range of inventory compilation methods have been proposed around the globe, and there has long been a pressing need to analyze and compare these methods in depth. This study sorted out and categorized inventory compilation methods of ship emissions in recent decades. Five main methods were compared and analyz

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Singh, Navdeep. "Leveraging AI and Blockchain to Automate Inventory Auditing: Enhancing Accuracy and Compliance." International Journal for Research in Applied Science and Engineering Technology 11, no. 12 (2023): 1239–47. http://dx.doi.org/10.22214/ijraset.2023.57565.

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Abstract: This paper presents an in-depth exploration of the integration of Artificial Intelligence (AI) and Blockchain technologies in inventory auditing. It delves into the transformative potential of these technologies to enhance accuracy, efficiency, and transparency in auditing processes. The study systematically examines various aspects, including the theoretical framework of AI and Blockchain, their synergistic application in inventory auditing, and the implications for compliance and regulatory standards. Industry-specific case studies are analysed to demonstrate practical applications

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Sitorus, Zulham, Irwan Syahputra, Chairul Indra Angkat, and Dewi Sartika. "Implementation of K-Means Clustering for Inventory Projection." International Journal of Science, Technology & Management 5, no. 3 (2024): 673–78. http://dx.doi.org/10.46729/ijstm.v5i3.856.

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Inventory forecasting is crucial in effective supply chain management and cost reduction. However, traditional forecasting techniques face significant challenges due to the complexity and variability of demand patterns. This study explores the use of K-means clustering, a data-driven approach that can improve inventory forecasting accuracy. By grouping inventory items based on their unique demand profiles, we can create personalized forecasting models for each cluster. This technique enhances demand estimation, helping businesses make informed decisions and optimize their inventory. Our resear

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Saumil R Patel. "Multi-Modal product recognition in retail environments: Enhancing accuracy through integrated vision and OCR approaches." World Journal of Advanced Research and Reviews 25, no. 1 (2025): 1837–44. https://doi.org/10.30574/wjarr.2025.25.1.0122.

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This research presents a transformative artificial intelligence solution that addresses critical operational challenges in modern retail environments. Our integrated system combines advanced computer vision and text recognition technologies to automate product identification, inventory tracking, and checkout processes. In response to the retail industry's pressing needs for automation amid labor shortages and rising operational costs, we developed and implemented a comprehensive solution that demonstrates significant business value. The system achieved a 94.6% accuracy rate in product recognit

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He, Wei. "An Inventory Controlled Supply Chain Model Based on Improved BP Neural Network." Discrete Dynamics in Nature and Society 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/537675.

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Inventory control is a key factor for reducing supply chain cost and increasing customer satisfaction. However, prediction of inventory level is a challenging task for managers. As one of the widely used techniques for inventory control, standard BP neural network has such problems as low convergence rate and poor prediction accuracy. Aiming at these problems, a new fast convergent BP neural network model for predicting inventory level is developed in this paper. By adding an error offset, this paper deduces the new chain propagation rule and the new weight formula. This paper also applies the

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