Inventory Management Process Research Articles

Utilization of IoT and database system of central warehouse project in the pharmaceutical industry

This study aims to develop an MRPII device that utilizes internet technology for inventory management control processes, using case studies from pharmacutical companies in Indonesia. The research was conducted using field observation methods and system development, then comparing the manual system and MRPII. An internet-based inventory management system was created by integrating the warehouse’s material database into each material code via a QR. code. The study found that implementing the MRP II system design increases work effectiveness and reduces the risk of errors that frequently occur in conventional systems. Moreover, using the MRPII can facilitate the audit process and establish transparency in the inventory management process. Data processed using IoT is generated faster and more accurately as company operations improve quality, reduce unnecessary activities, and make it easier to organize materials and run administrative and technical processes in inventory management; it is measured based on reach, workforce requirements, supply, and handling time. In the industrial world, the MRPII database system has the potential to evolve into several more complex and comprehensive systems. It has broad integration and can assist humans working across all lines, particularly in the data processing system.

Red Blood Cell (RBC) Antigen Confirmation Workflow – A Positive Impact at an Academic Medical Center

Abstract Introduction/Objective Introduction: Blood group antigens, present on the surface of red blood cells (RBCs), play a crucial role in transfusion medicine. These antigens are recognized serologically and form the basis of RBC phenotyping. Understanding the significance of antigen-negative RBCs is essential for mitigating the risk of hemolytic transfusion reactions and hemolytic disease of the fetus and newborn (HDFN). This study aims to assess the impact of implementing a new RBC antigen confirmation workflow on transfusion service efficiency and patient outcomes. Methods/Case Report Method: The study involved collaboration between our Transfusion Services Department (TS), the Blood Center supplier, and the Apheresis department. A comprehensive review of historical practices and FDA recommendations regarding RBC antigen labeling was conducted. Changes were implemented to streamline antigen confirmation testing and labeling processes. The impact on TS workload, turnaround time, and patient care metrics was evaluated. Results (if a Case Study enter NA) Results: Implementation of the new RBC antigen confirmation workflow led to a significant reduction in antigen confirmation tests performed by TS, with a 607% decrease observed from 2020 to 2023. Concurrently, the workload for reference lab workups increased by 337% over the same period. This shift in workload distribution allowed TS staff to focus more on patient reference workup cases and case review. The improved workflow efficiency resulted in enhanced turnaround times for providing patients with antigen-negative RBCs, ultimately improving the patient experience. Conclusion Conclusion: The adoption of the new RBC antigen confirmation workflow has resulted in compliance with FDA labeling requirements, efficient utilization of TS staff resources, and decreased turnaround times for blood delivery. These improvements have positively impacted patient care by ensuring timely access to compatible blood products. Future steps include developing reports to track turnaround time for patients with special blood product needs and continuing collaboration with the blood supplier and the Apheresis department to optimize inventory management and transfusion processes.

INTELLIGENT INFORMATION TECHNOLOGIES FOR PROACTIVE ENTERPRISE MANAGEMENT

Industrial enterprises are essential to a country’s economy, providing diverse, high-quality goods, technologies, and services. To remain sustainable and efficient amidst rising production demands and stiff competition, these enterprises must adopt innovative management techniques. Each enterprise has a mission, resources, technologies, and strategies to achieve its varied goals, with dominant economic goals like income, profitability, and market share interlinked and affecting one another. A competitive enterprise’s overall goal should align its growth with market trends while proactively managing its operations. Proactive management involves either passively aligning with market trends or actively influencing them by introducing new products and services. The mismatch between an enterprise’s growth and market trends can flag potential problems or crises, underscoring proactive management’s role in preempting issues. This strategy, though simple, is vital for an enterprise’s survival, sustainable operation, and efficient growth in a fiercely competitive environment with escalating production of quality goods and services. Therefore, an urgent issue is developing an information platform based on appropriate mathematical models and methods that facilitate the implementation of proactive management of industrial enterprises and create the basis for predicting possible problems in production and taking measures to prevent them. Integrating advanced technologies like Artificial Intelligence, Big Data Analytics, and the Internet of Things enhances the proactive management system’s capability. These technologies enable real-time data collection and analysis, providing enterprises with critical insights and allowing them to anticipate market shifts and operational challenges. By leveraging these tools, enterprises can make more informed decisions, streamline their processes, and achieve higher operational resilience and flexibility. Industry 4.0 and 5.0 can significantly support Ukrainian manufacturing during the war. Thanks to automation and robotics, it is possible to maintain production even in the face of limited access to labour or hazardous working conditions. Artificial intelligence and advanced analytical systems can help optimise logistics, inventory management, and production processes despite disruptions caused by military actions. In conclusion, proactive management is not just a strategic choice but a need for industrial enterprises aiming to thrive in today’s fast-paced and highly competitive market. By incorporating cutting-edge technologies and adopting a forward-thinking approach, enterprises can ensure long-term sustainability, improved performance, and a better competitive edge. Keywords: proactive management, information modelling, industrial enterprise, artificial intelligence, Industry 4.0 / 5.0.

Probabilistic Inventory Models and Productivity of Selected Manufacturing Firms in Port Harcourt

This study examines the relationship between probabilistic inventory models and productivity of selected manufacturing firms in port Harcourt. Correlational survey research design was adopted for this study as this study seek to determine the relationship between the two variables. The population of this study is thirty-two (32) manufacturing companies in Rivers State which are registered with the Rivers State branch of Manufacturers Association of Nigeria (MAN). This gave us a total of ninety-two (92) for the study. Structured questionnaire instrument title” Probabilistic inventory models and productivity of selected manufacturing firms in Port Harcourt. questionnaire was developed on five- point likert scale. The result of the Cronbach's Alpha reliability test indicates .800 which is above .70 which implies that the items are reliable. Pearson product moment correlation was used to test the hypotheses using SPSS (statistical package social sciences). The study revealed that there is a significant relationship between Continuous Review Models and Productivity of manufacturing firms in Port Harcourt, Rivers State. There is a significant relationship between Periodic Review Models and Productivity of manufacturing firms in Port Harcourt, Rivers State. There is a significant relationship between Single-Period Models and Productivity of manufacturing firms in Port Harcourt, Rivers State. The study concluded that Probabilistic inventory models play a crucial role in optimizing inventory management for manufacturing firms. The study recommended that Manufacturing firms in Port Harcourt should consider implementing probabilistic inventory models such as continuous review, periodic review, and single-period models to optimize their inventory management processes.

The Functionality of Financial Control Activities in a Decentralised Basic Education Program in Uganda

Financial control activities are critical in enhancing financial accountability. This article aimed at determining the functionality of financial control activities in decentralised basic education programmes. It sought to investigate how control activities in the Universal Primary Education programme (UPE) affect the internal controls and subsequently financial accountability of the grant. The researchers conducted an exploratory review of the literature and used semi-structured interviews to collect primary data. The findings focused on physical controls in the UPE capitation grant. Under physical controls, emphasis was placed on mechanisms for securing cash and inventory. The findings revealed that physical control of the custody of cash in UPE schools is weak. This puts other school assets at risk of burglary by individuals who may get to know that there is cash in the office. The weak physical controls create an urge for the head teachers to divert resources. A scrutiny of the inventory management process exposed some gaps affecting the entire physical control system. The inventory management system is heavily compromised. Given the foregoing findings, we can argue that the financial control activities in this UPE programme are dysfunctional. The functionality of financial control activities will be enhanced if the physical control activities are strengthened and all the receipts and inventories are properly recorded. Keywords: Functionality, Financial Control, Decentralised Basic Education System and Financial Accountability

Neural Network Sales Revolution Outperforms Exponential Smoothing

This research addresses the challenges faced by food manufacturing companies, focusing on UD. XYZ as a case study. With fluctuating sales levels causing raw material buildup and shortages, the study proposes an improved sales forecasting method to enhance raw material control. By comparing Artificial Neural Network (ANN) and Double Exponential Smoothing Holts, the research aims to optimize inventory management and production processes. Results indicate ANN's superiority over Holts, with an accuracy rate of 0.118 compared to 11.639. The ANN model accurately forecasts sales for the upcoming twelve-month period, highlighting a decline from July 2023 to May 2024. Implementing advanced forecasting methods can mitigate raw material-related risks and enhance operational efficiency for companies like UD. XYZ. Highlight: Enhanced sales prediction methods crucial for inventory planning. Artificial Neural Network outperforms traditional forecasting techniques. Improved forecasting mitigates raw material shortages and excesses. Keywoard: Sales forecasting, Artificial Neural Network, Raw material control, Inventory management, Production optimization.

Proposal of Set of Optimization Criteria and Their Specific Calculation for Effective Inventory Management in an Industrial Enterprise

Currently, there are many mathematical models and tools for inventory management and optimization. Based on the literature review, the authors conclude that inventory management tools and models are mostly one-sided and focused on the cost aspect of the inventory management process. The research goal was to propose a set of criteria for inventory optimization as a basis for the development of an inventory management model whose structure would consider both the economic aspect and the stochasticity of demand and the reliability of delivery. Optimization criteria are based on extensive analyses of influences and correlations between logistic chain subsystems in relation to inventory. The interactions of the subsystems are then mathematically expressed, which represents the main output of the created set of optimization criteria. The defined criteria can be used as a basis for creating a new optimization model of inventory management.

A STUDY ON OUTBOUND CUSTOMER COMPLAINT DUE TO INVENTORY VARIANCES AT APOLLO TIRES NDC1

This study defines into outbound customer complaints arising from inventory variances at Apollo Tyres NDC1, with the primary objective of understanding and addressing the underlying issues. Through a secondary objective, it aims to identify root causes, assess customer impact, apply the DMAIC methodology, and evaluate improvement measures. Using a structured approach, the study examines factors contributing to inventory variances and their implications on customer satisfaction and loyalty metrics. By implementing the DMAIC framework, inventory management processes are systematically analysed to identify areas for improvement. Improvement measures, including macro implementation, wall-to-wall audits, and the proposed Outbound Integrated Optimization and Navigation System (OIONS), show promising results in reducing inventory variances and mitigating customer complaint.

A Comprehensive Analysis of Inventory Management and Its Potential Implications on Financial Reports

Abstract: Inventory management plays a pivotal role in businesses' operational efficiency and financial success, encompassing processes aimed at maintaining optimal stock levels while minimizing costs and meeting customer demand. This paper presents a comprehensive analysis of inventory management practices, focusing on their impact on financial performance, challenges, opportunities, and best practices. Through a literature review, the study examines existing research on inventory management, highlighting its significant positive relationship with organizational performance. The research methodology includes correlation analysis, descriptive statistics, questionnaire analysis, and hypothesis testing to explore the intricate dynamics of inventory management. Findings reveal a strong correlation between efficient inventory management practices and improved financial metrics, emphasizing the importance of implementing advanced inventory management systems, enhancing forecasting accuracy, and fostering collaboration within supply chains. The study concludes with practical recommendations for businesses seeking to optimize their inventory management processes and enhance financial performance in today's competitive marketplace

Procurement process and shortages of essential medicines in public health facilities: A qualitative study from Nepal.

Ensuring access to essential medicines remains a formidable challenge in Nepal. The specific reasons for the shortage of essential medicines within Nepal have not been extensively investigated. This study addresses challenges associated with access to essential medicines, procurement process difficulties, and functionality of inventory management systems at different levels of public health facilities. Fifty-nine semi-structured in-depth interviews were conducted with health managers and service providers at provincial and local levels in six randomly selected districts of Bagmati province, Nepal. Interviews were audiotaped and transcribed verbatim, and the results were analyzed using the inductive approach and were later mapped within the four domains of "Procurement of essential medicines". The major barriers for the effective management of essential medicines included delays in the procurement process, primarily locally, leading to frequent stock-out of essential drugs, particularly at the health post level. Additionally, challenges arise from storage problems, mainly due to insufficient storage space and the need to manage additional comorbidities related to COVID-19. Other identified challenges encompass the absence of training on logistics management information systems, a lack of information technology resources in primary health facilities, inadequate qualified human resources to operate the IT system, and insufficient power backup. Moreover, unrealistic demand estimation from the service points, inadequate transportation costs, and manual inventory management systems further contributed to the complex landscape of challenges. This study identified procurement delays as the primary cause of essential medicine shortages in Bagmati Province, Nepal. We recommend implementing comprehensive procurement guidelines, collaborative training, and dedicated budgets to address this issue. Improving the procurement and inventory management process in low-resource settings requires a well-trained workforce, suitable storage spaces, and enhanced coordinated administrative tiers within health facilities at different levels to ensure the year-round availability of essential medicines in these settings.

SIAPIK PELATIHAN PENGELOLAAN KEUANGAN BERBASIS APLIKASI SI-APIK BAGI PELAKU USAHA PETANI GARAM DI DESA KETEWEL

Loloan salt farmers in Ketewel village are a small business consisting of six people whose production focus is making salt through processing local resources. Salt farmers' knowledge of digital-based financial management is still low. Farmers often use income from sales of salt for personal needs. This will certainly have an impact on unstable cash flow in the business. To reduce the occurrence of unstable cash flows, daily financial recording must be carried out using currently available technology. The role of technology in financial processes is to reduce human errors and increase efficiency, assist inventory management processes, increase data accessibility and security, speed up payment processes and income tracking, and optimize expenses and reduce operational costs. The method used in this village project is in the form of discussions and providing training to salt farmers regarding digitalization-based financial management. The results of this village project activity were able to increase salt farmers' knowledge regarding digitized financial management which includes how to record business through the SI-APIK application. Keywords: Financial Management ; SIAPIK ; Salt Farmers ; Desa Ketewel

Inventory Management System

This research paper presents a comprehensive analysis of inventory management systems tailored specifically for general stores, focusing on software solutions. The paper discusses the challenges faced by general store owners in managing inventory effectively and proposes a solution-oriented approach to optimize inventory management processes. Through a case study, various software options are evaluated, considering factors such as cost, features, scalability, and user-friendliness. The research aims to provide valuable insights and recommendations for general store owners to enhance their inventory management practices and streamline operations

Leveraging K-Nearest Neighbors for Enhanced Fruit Classification and Quality Assessment

This study investigates the application of the K-Nearest Neighbors (KNN) algorithm for fruit classification and quality assessment, aiming to enhance agricultural practices through machine learning. Employing a comprehensive dataset that encapsulates various fruit attributes such as size, weight, sweetness, crunchiness, juiciness, ripeness, acidity, and quality, the research leverages a 5-fold cross-validation method to ensure the reliability and generalizability of the KNN model's performance. The findings reveal that the KNN algorithm demonstrates high accuracy, precision, recall, and F1-Score across all metrics, indicating its efficacy in classifying fruits and predicting their quality accurately. These results not only validate the algorithm's potential in agricultural applications but also align with existing research on machine learning's capability to tackle complex classification problems. The study's discussions extend to the practical implications of implementing a KNN-based model in the agricultural sector, highlighting the possibility of revolutionizing quality control and inventory management processes. Moreover, the research contributes to the field by confirming the hypothesis regarding the effectiveness of KNN in agricultural settings and lays the foundation for future explorations that could integrate multiple machine learning techniques for enhanced outcomes. Recommendations for subsequent studies include expanding the dataset and exploring algorithmic synergies, aiming to further the advancements in agricultural technology and machine learning applications.

Implementation of Productivity Improvement Techniques in Wood Industry

Abstract: In Industries, it is very important to save time and money in manufacturing products, because there is lots of competition in the industrial world. The main objective of this study is to improve productivity of the wood industry by implementing different types of productivity improvement techniques such as 5S, Lean Manufacturing, JIT, TQM, 6 Sigma, Kanban, Jidoka and PDCA, etc. Improvement can be done by above techniques and by observing the working process cycle and study of the machineries, time study, identifying the problems during process, process analysis, study of inventory management process, and make the solution on the based problems. The purpose of this study is to eliminate the wastes and reduce the idle times in industry.

Design of Inventory Information Systems at CV Company. Web-Based Berjaya Jaya Abadi

This research focuses on the design and implementation of a web-based inventory management system for CV. Berjaya Jaya Abadi company. Inventory management plays a crucial role in the efficient operation of businesses, particularly in ensuring optimal stock levels, minimizing costs, and improving overall productivity. The proposed system aims to streamline inventory-related processes by providing real-time access to inventory data, facilitating inventory tracking, and automating inventory management tasks. Utilizing web-based technology offers the advantage of accessibility from anywhere with an internet connection, allowing employees to manage inventory remotely and enhancing collaboration among team members. The system will include features such as inventory tracking, stock level monitoring, order management, and reporting functionalities to provide comprehensive support for inventory management tasks. By implementing this web-based inventory system, CV. Berjaya Jaya Abadi can expect improved efficiency, accuracy, and visibility in their inventory management processes, ultimately leading to better decision-making and business performance.

Two Lot-Sizing Algorithms for Minimizing Inventory Cost and Their Software Implementation

Effective inventory management is crucial for businesses to balance minimizing holding costs while optimizing ordering strategies. Monthly or sporadic orders over time may lead to high ordering or holding costs, respectively. In this study, we introduce two novel algorithms designed to optimize ordering replenishment quantities, minimizing total replenishment, and holding costs over a planning horizon for both partially loaded and fully loaded trucks. The novelty of the first algorithm is that it extends the classical Wagner–Whitin approach by incorporating various additional cost elements, stock retention considerations, and warehouse capacity constraints, making it more suitable for real-world problems. The second algorithm presented in this study is a variation of the first algorithm, with its contribution being that it incorporates the requirement of several suppliers to receive order quantities that regard only fully loaded trucks. These two algorithms are implemented in Python, creating the software tool called “Inventory Cost Minimizing tool” (ICM). This tool takes relevant data inputs and outputs optimal order timing and quantities, minimizing total costs. This research offers practical and novel solutions for businesses seeking to streamline their inventory management processes and reduce overall expenses.

Augmented reality in smart retail for inventory management

The ever-growing complexity of supply chains and the dynamic nature of modern business environments demand innovative solutions for efficient and cost-effective inventory management. This paper introduces a novel approach to address these challenges through the integration of augmented reality (AR) technology. Our proposed system leverages AR to enhance the accuracy, speed and adaptability of inventory management processes while maintaining a focus on cost-effectiveness. By overlaying digital information onto the physical world, AR transforms the way inventory is monitored, tracked and updated. The system utilises wearable AR devices, such as smart glasses, to provide real-time insights into inventory levels, product locations and order fulfilment status. This not only reduces manual errors but also significantly improves the overall efficiency of inventory-related tasks. To validate the effectiveness of our approach, we conducted a series of simulations and case studies across diverse industries. The results demonstrate notable improvements in inventory accuracy, order fulfilment speed and overall operational efficiency. The proposed AR-based inventory management system emerges as a viable and cost-effective solution, poised to revolutionise traditional inventory management practices in the contemporary business landscape.

Econometric Study: E-commerce Adoption on Inventory Management for Manufacturing Companies in Nigeria

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 accuracy, storage optimization, inventory holding costs, supplier reliability, inventory audit frequency, obsolete inventory and inventory replenishment. The explosion of e-commerce in the logistics sector has posed a challenge that must be effectively managed to susstain the volume of goods across long distances, the interface between e-commerce and in particular inventory management, for instance via stocks and warehousing has become so important to be overlooked. The study was carried out in Nigeria and the population of the study include staff of 20 manufacturing companies listed on the Nigerian Stock Exchange as at 2023. Simple random sampling technique was used to select 718 respondents. Data was collected through a structured questionnaire and was analysed using both one sample t-test analysis and multivariant regression analysis. E-commerce has positive and significant effect on stockout frequency (P = .000), inventory turnover rate (P=0.000), demand forecasting accuracy (P=0.000), storage optimization (P=0.000) and inventory replenishment (P=0.000). The findings revealed significant improvements in inventory accuracy, reduced stockout frequency, increased inventory turnover rate, and improved demand forecasting accuracy. Evidently, these findings imply that the adoption of e-commerce is essential in optimizing inventory management processes and thus recommends that manufacturing companies should further utilize digital tools to enable better forecasting in inventory management and efficient stock handling.

IMPLEMENTASI AGILE DEVELOPMENT BERBASIS WEB BASED PADA SISTEM INVENTORY

The inventory management at the Aeng store causes errors in the recognition of revenue and inventory calculation, making process inefficient and incurring losses. The purpose of this research is to analyze the needs required by Aeng Stores as well as design the application of the inventory system of good that can facilitate in carrying out the recording of sales and purchase reports, recording inventory reports, and recording supplier data. The test method used is the Black Box, which tests the software based on its external appearance and functionality, not the source code of the program. The results of this study show that applying Agile Development Method to inventory management brings many benefits. These include making inventory management processes more efficient, improving inventory accuracy, reducing excessive costs, and increasing responsiveness in a rapidly changing business environment. The conclusions derived from the tests that have been carried out, using Agile Development Method can be a fairly effective and efficient way for the Aeng Store to manage store inventory.

Enhancing the Online Shopping Experience of Consumers through Artificial Intelligence

Artificial intelligence (AI) has revolutionized the online shopping experience for consumers. With AI-powered technologies, businesses can offer personalized recommendations based on consumers' browsing and purchase history. This creates a more tailored and convenient shopping experience, saving consumers time and effort. Additionally, AI can assist in fraud detection and prevention, ensuring secure transactions and building trust with customers. Moreover, AI chatbots are increasingly being used to provide instant and accurate customer support, answering queries and resolving issues promptly. As technology continues to advance, AI will play an even more significant role in enhancing the online shopping experience.AI can analyze vast amounts of data and identify patterns, enabling businesses to optimize their inventory management and supply chain processes. By predicting demand and optimizing product availability, AI helps reduce stock outs and overstocks, leading to increased customer satisfaction. AI-powered virtual try-on technology is also gaining popularity, allowing consumers to virtually try on clothing, accessories, and even makeup before making a purchase. This helps them make more informed buying decisions and reduces the likelihood of returns. Overall, AI is transforming the online shopping landscape by improving personalization, security, customer support, and product discovery, making the experience more enjoyable and efficient for consumers.