Inventory Requirements Research Articles

Simultaneous enhancement of tritium burn efficiency and fusion power with low-tritium spin-polarized fuel

Abstract This study demonstrates that using spin-polarized deuterium-tritium (D-T) fuel with more deuterium than tritium can increase tritium burn efficiency (TBE) by at least an order of magnitude without compromising fusion power output, compared to unpolarized fuel. Although previous studies show that a low tritium fraction can enhance TBE, this strategy resulted in reduced fusion power density. The surprising improvement in TBE at fixed power reported here is due to the TBE increasing nonlinearly with decreasing tritium fraction but the fusion power density increasing roughly linearly with D-T cross section. A study is performed for an ARC-like tokamak producing 481 MW of fusion power with unpolarized 53:47 D-T fuel, finding the minimum startup tritium inventory ($I_{\mathrm{startup,min}}$) is 0.69 kg. By spin-polarizing half of the fuel and using a 60:40 D-T mix, $I_{\mathrm{startup,min}}$ is reduced to 0.08 kg, and fully spin-polarizing the fuel with a 63:37 D-T mix further reduces $I_{\mathrm{startup,min}}$ to 0.03 kg. Some ARC-like scenarios {are predicted to} achieve plasma ignition with relatively modest spin polarization. These findings indicate that, with advancements in helium divertor pumping efficiency, TBE values of approximately 10-40\% could be achieved using low-tritium-fraction and spin-polarized fuel with minimal power loss. This would dramatically lower tritium startup inventory requirements and reduce the amount of on-site tritium. More generally than just for spin-polarized fuels, {increased} plasma performance can be used to increase TBE. This strongly motivates the development of spin-polarized fuels and low-tritium-fraction operation for burning plasmas.

Developing Service Line Inventories: Guidance for Utilities With Limited Lead Lines

Key TakeawaysIn the United States, all community and nontransient noncommunity water systems are required to submit an inventory describing the location and makeup of all service lines in their service areas.While the material can be designated as lead, galvanized requiring replacement, nonlead, or unknown, the last two designations require additional steps to be taken in the proposed Lead and Copper Rule Improvements (LCRI).Some utilities have few or no lead service lines, and this inventory requirement, issued by the US Environmental Protection Agency (EPA), may be burdensome to those utilities.This article demonstrates the methodology in EPA's proposed LCRI for verification of construction material, and an alternate validation procedure is proposed.

Analisis Pengadaan Persediaan Bahan Baku Pada Umkm Otr Laundry Dengan Menerapkan Metode Perhitungan Economic Order Quantity (EOQ)

This study aims to determine and analyze the control of the main raw material inventory at OTR Laundry with an inventory management policy using the Economic Order Quantity (EOQ) method. The study focuses on inventory management at OTR Laundry located at Jalan Ciseke, Jatinangor, Sumedang. This study uses a quantitative approach. Primary data in this study were obtained through in-depth interviews with the owner of OTR Laundry and direct observation in the field. Secondary data were obtained from inventory records and the company's financial reports. Data collection techniques used were interviews, observations, and documentation. Data analysis was carried out by calculating optimal inventory requirements using the EOQ method and comparing them with the inventory policy implemented by OTR Laundry. The calculation results show a comparison between the total cost of fragrance inventory calculated based on the OTR Laundry policy and the EOQ calculation method. Savings using the EOQ method compared to the OTR Laundry policy on inventory cost expenditure amounted to Rp313,764. The results of this study are expected to provide recommendations for OTR Laundry in increasing the efficiency of managing the main raw material inventory and reducing operational costs.

Exponential smoothing method against the gradient boosting machine learning algorithm-based model for materials forecasting to minimize inventory

The optimization of resources and reduction of costs through efficient inventory management are paramount to organizational success. This study undertakes a comparative analysis of two distinct forecasting methodologies, Exponential Smoothing (ES) and Gradient Boosting (GB), within the framework of materials forecasting aimed at inventory minimization. Our study introduces innovation by methodically scrutinizing these approaches within a unified framework, shedding light on their merits and shortcomings. This comparative analysis gives practitioners a practical roadmap for the optimal forecasting strategy to streamline inventory management operations. Methodologies are evaluated based on their efficiency in predicting material demand, encompassing metrics such as accuracy, computational efficiency, and suitability across various inventory management scenarios. Response surface methodology entails refining processes to modify factorial variables’ configurations to attain a desired peak or trough in response. The SPSS results show that the ES method has 43.20%, surpassing the accuracy of the inventory optimization model, which stood at 65.08%. The response surface methodology results show that 45.20% profit was achieved for the variable and operational cost process parameters. This research seeks to unveil the traces of each method, facilitating decision-makers in selecting an optimal forecasting strategy tailored to their specific inventory management requirements. The analysis shows that the ES method surpasses the accuracy of the GB machine learning for material forecasting to minimize inventory.

HARMONIC ANALYSISIN INVENTORY MANAGEMENT IN LOGISTICSAND SUPPLY CHAINS

The article examines the possibilities of using harmonic analysis apparatus while planning the need in stocks of various categories. The issues of improving material planning (forecasting) are currently quite relevant applied tasks in business, and are also of interest in terms of developing the theory of logistics and supply chain management. Among the approaches to planning the need for inventory, a wide range of statistical theory methods are used in practice, among which two large groups can be distinguished, such as one-parameter time series analysis models for goods of stable and relatively stable demand, as well as correlation and regression models for chaotic consumption stocks. Most of the goods sold to end consumers have a seasonal component, which may not always be explicitly expressed in statistics. However, due to change of seasons, regular fluctuations in the values of consumption from the warehouse, around the average chronological or trend, may necessitate regular recalculation of the main parameters of inventory management models, such as maximum, insurance, threshold inventory levels, etc. In addition, sales statistics may contain fluctuations of a higher order if the stocks sold have life cycles of interest in goods on the market, which can also be attributed to periodic or quasi-periodic processes. One of the methods to formalize such cyclic processes can be trigonometric approximation or harmonic analysis, when the values of a time series are represented as terms of a Fourier series (harmonics) having corresponding amplitudes and phases. The article compares the effectiveness (accuracy) of forecasts of inventory requirements made using harmonic analysis and traditional time series extrapolation methods.

Inventory Management System for MSMEs

This inquire about points to create a web-based stock framework that centers on reasonableness, user-friendliness, and usefulness custom-made to desires of Miniaturized scale, Little, and Medium Ventures (MSMEs). Through in-depth analysis of MSMEs' specific inventory management requirements, the system not only provides a comprehensive solution for stock management but also integrates the Apriori algorithm for associative analysis of inventory data. The system's development adopts an Agile approach, allowing flexible adaptation to changing needs throughout the development process. Key features include efficient stock management, intuitive Point of Sales (POS) transaction recording, and customizable inventory reporting. The implementation of this system is expected to enhance MSMEs' efficiency in inventory management, provide insightful data to support more informed decision-making, and positively contribute to strengthening competitiveness and growth in the dynamic and competitive business environment.

Leveraging Compliance to Design a Minimally Invasive, Expandable Interbody Cage Capable of Customized Anatomical Fit for Spinal Fusion Surgery

Abstract As spinal fusion surgery continues to transition to less invasive techniques, there remains an unmet need for ever smaller and more complex interbody cages to meet the unique needs of this difficult surgery. This work focuses on the hypothesis that this need can be met using the inherent advantages of compliant mechanisms in a way no previous device has. Deployable Euler Spiral Connectors optimized using a gradient based optimization algorithm were used as the foundation for a device that can stow to a very small size for device insertion then bilaterally deploy to a substantially larger device footprint. Additionally, a continuously adjustable lordotic angle was achieved using the same device so as to result in a customized anatomical fit while potentially reducing hospital inventory requirements. Several tests including finite element analysis, compression testing, shear testing, and deployment in a cadaver were performed as initial verification and validation that the concept device performs reasonably well under typical testing paradigms used for interbody cages.

Analysis of obstacles to lowering demurrage at grain terminals in South Korea

This study aimed to analyze the obstacles to lowering demurrage at a grain terminal. After conducting in-depth interviews with working-level staff in grain terminal, 12 factors were selected to derive key factors for reducing demurrage. The Consistent Fuzzy Preference Relations methodology, which can extract experts’ knowledge and experiences, was employed to rank the obstacles in lowering demurrage. The analysis showed that the number one factor was “inventory requirements of grain shippers” (with an importance of 0.097), followed by “capacity of storage facilities” and “port congestion” as the second and third factors, respectively. As for sub-factors, “climate (e.g., typhoon, rain, etc.)” and “ship size” were ranked 11th and 12th, respectively. The analysis indicates that experts recognized factors that can be changed by shippers and that are difficult to control as more important obstacles than cost-related factors. The findings of this study provide the working-staff of ports, grain terminals, and the government implications for reducing demurrage.

Towards inventory control excellence: An innovative approach based on a web-based platform.

Inventory management in educational institutions presents unique challenges due to the diverse sources of information and the need for improved team collaboration. This research aims to enhance inventory processes in educational institutions by leveraging information technology to optimize efficiency and ensure data integrity and reliability. The study employed a five-phase methodology to develop a web-based inventory optimization system. The initial phase involved a comprehensive analysis of inventory requirements, considering multiple data sources and team needs. Subsequently, in the planning phase, requirements were prioritized, and tasks with corresponding deadlines were established.The implementation phase adhered to the requirements outlined in the planning phase, utilizing appropriate information technologies to ensure efficient and reliable operation. A thorough system review was conducted to assess the achievement of each requirement's objectives, with necessary adjustments made as needed. Finally, following the completion of the previous phases, the developed software was deployed, and additional testing was conducted to ensure proper functionality. Following the implementation of the web-based system, significant improvements were observed: an 85.51% increase in efficiency for goods searches, streamlining the process and reducing location times; a 90.31% enhancement in goods registration, ensuring greater accuracy and data reliability; an 83.11% improvement in annual goods report generation, simplifying reporting and offering a clearer view of the inventory. Overall, the inventory process experienced an 86.31% improvement, leading to enhanced efficiency and collaboration among administrative and teaching staff. The utilization of information technology reduced inventory processing times and ensured the uniqueness and reliability of information. This research focuses specifically on optimizing inventory management in educational institutions through information technology. The study's uniqueness lies in its tailored web-based system designed to address the specific needs of educational institutions. The results demonstrate the effectiveness of this approach and its positive impact on inventory management.

Web-Based Coffee Inventory Application

This study aims to gain insights into the inventory requirements of a coffee shop, develop and deploy a web-based application to enhance inventory management efficiency and assess the effects of this implementation on the coffee shop's operational processes. The methodology employed encompasses a blend of qualitative and quantitative techniques for data collecting, encompassing interviews, observations, and system testing. These methods are utilized to develop a comprehensive comprehension of the current inventory system and evaluate the efficacy of the recently built web application. The findings indicate that implementing the application resulted in a substantial enhancement in inventory management. This condition was achieved through the provision of real-time inventory tracking, a reduction in errors associated with manual recording, and an overall improvement in operational efficiency. The coffee shop workers responded positively to the product, highlighting its user-friendly nature and time-saving capabilities. Nevertheless, the study posits that forthcoming research should contemplate integrating elements such as predictive analytics to enhance stock management capabilities and develop a mobile iteration to augment flexibility and user-friendliness. This study provides additional evidence to reinforce the importance of implementing digital transformations in small-scale enterprises to address prevalent operational obstacles.

Improved benders-and-price algorithm for the multi-product assembly routing problem with time windows: A domain decomposition strategy for the benders-master model

To meet the optimization requirements of many-to-one assembly systems comprising a plant and multiple suppliers, the multi-product assembly routing problem with time windows (MPARPTW) is investigated in this study. Besides optimizing the assembly of different types of products in a plant to satisfy the periodic market demand within a specific planning horizon, MPARPTW factors in the vehicle routes for collecting many components from suppliers to meet the inventory requirements that are imposed by the production. The MPARPTW is formulated as a mixed-integer linear programming model to minimize the setup, production, transportation, and inventory costs. The model is solved using an improved Benders-and-Price algorithm that combines Benders decomposition and branch-and-price algorithm. The MPARPTW model is decomposed into a lot-sizing Benders-master (BM) model and a vehicle-routing Benders-sub (BS) model. A domain decomposition strategy is developed in this study to further decompose the BM model, thereby generating Benders cuts efficiently and increasing the convergence speed. Numerical experiments are designed to test the performance of the proposed algorithm. Within a limited maximum computing time (compared with the off-the-shelf solver), the improved algorithm reduces the average cost and computing time by 0.6% and 59.3%, respectively. The significance of the proposed model and algorithm in determining the plant investment directions is demonstrated. Moreover, compared with the conventional algorithm, the improved algorithm exhibits overall improvements. In large-scale instances, the cost is reduced by 1.8% on average and 4.2% maximum. The computing time yields average and maximum reductions of 35.2% and 76.0%, respectively.

The Role of Predictive Analytics in Inventory Management

The use of predictive analytics has emerged as a game-changing instrument in the field of stock management. This tool provides a data-driven strategy to optimise stock levels, reduce costs, and improve operational efficiency. The purpose of this abstract is to investigate the role that predictive analytics plays in revolutionising how inventory management processes are carried out. This is accomplished by using historical data, statistical algorithms, and machine learning approaches to estimate future inventory requirements. At its foundation, predictive analytics is doing an analysis of previous inventory data, sales trends, and external variables in order to forecast future demand with a high degree of precision. When it comes to inventory management, traditional methods sometimes rely on static models and gut reactions, which may result in problems such as overstocking or stockouts. Alternatively, predictive analytics offers a dynamic and data-informed viewpoint, which enables firms to alter their inventory strategy in a proactive manner as necessary. Companies are able to estimate demand changes based on seasonality, market trends, promotions, and other factors when they integrate predictive models into their operations. This results in more accurate inventory planning.

Informing Methane Emissions Inventories Using Facility Aerial Measurements at Midstream Natural Gas Facilities.

Increased interest in greenhouse gas (GHG) emissions, including recent legislative action and voluntary programs, has increased attention on quantifying and ultimately reducing methane emissions from the natural gas supply chain. While inventories used for public or corporate GHG policies have traditionally utilized bottom-up (BU) methods to estimate emissions, the validity of such inventories has been questioned. Therefore, there is attention on utilizing full-facility measurements using airborne, satellite, or drone (top-down (TD)) techniques to inform, improve, or validate inventories. This study utilized full-facility estimates from two independent TD methods at 15 midstream natural gas facilities in the U.S.A., which were compared with a contemporaneous daily inventory assembled by the facility operator, employing comprehensive inventory methods. Estimates from the two TD methods statistically agreed in 2 of 28 paired measurements. Operator inventories, which included extensions to capture sources beyond regular inventory requirements and integration of local measurements, estimated significantly lower emissions than the TD estimates for 40 of 43 paired comparisons. Significant disagreement was observed at most facilities, both between the two TD methods and between the TD estimates and operator inventory. These findings have two implications. First, improving inventory estimates will require additional on-site or ground-based diagnostic screening and measurement of all sources. Second, the TD full-facility measurement methods need to undergo further testing, characterization, and potential improvement specifically tailored for complex midstream facilities.

Concrete 3D Printing: Process Parameters for Process Control, Monitoring and Diagnosis in Automation and Construction

In Singapore, there is an increasing need for independence from manpower within the Building and Construction (B&C) Industry. Prefabricated Prefinished Volumetric Construction (PPVC) production is mainly driven by benefits in environmental pollution reduction, improved productivity, quality control, and customizability. However, overall cost savings have been counterbalanced by new cost drivers like modular precast moulds, transportation, hoisting, manufacturing & holding yards, and supervision costs. The highly modular requirements for PPVC places additive manufacturing in an advantageous position, due to its high customizability, low volume manufacturing capabilities for a faster manufacturing response time, faster production changeovers, and lower inventory requirements. However, C3DP has only just begun to move away from its early-stage development, where there is a need to closely evaluate the process parameters across buildability, extrudability, and pumpability aspects. As many parameters have been identified as having considerable influence on C3DP processes, monitoring systems for feedback applications seem to be an inevitable step forward to automation in construction. This paper has presented a broad analysis of the challenges posed to C3DP and feedback systems, stressing the admission of process parameters to correct multiple modes of failure.

Dynamic growth model for oak stands in Moscow, Russia

The most objective information about the state of Moscow’s forests is provided by long-term observation data on permanent trial plots. Such data makes it possible to identify changes in forest stands under the influence of recreationists, environmental pollution, and climate change. Long-term observational data are particularly valuable in modeling forest stand growth and productivity. The goal of the study is to develop a dynamic model of the growth of oak stands in Moscow based on long-term observation data. The modelling data were obtained from 7 plots of the permanent sample plot network established by the Forest Experimental Station of the Russian State Agrarian University – Moscow Timiryazev Agricultural Academy. There are a total of 42 inventories and the number of inventories per plot range from 3 to 9. Inventories were carried out between 1927 and 2009. We used three initial state variables for prediction, as in many studies. Taking into account the peculiarities of the inventory of forest stands in Russia, the mean height, quadratic mean diameter and number of trees per hectare were used as initial variables. All obtained models meet the requirements for forest inventory in Russia in terms of error values of stand attributes. The model in this study provides a simple and reliable system for predicting the growth and yield of Moscow oak stands.

Application of financial theories to inventory accounting: analytical approach and financial analysis

This research paper presents an analysis of the application of financial theories to inventory reporting within an analytical approach and financial analysis framework. This article explores how we can apply the latest financial theories, fundamental financial principles such as forecasting product sales, forecasting inventory requirements, determining optimal supply levels, inventory cycle, and discounted cash flow analysis to inventory reporting. Overall, this article examines the application of financial theories to improve the effective regulation and financial orientation of inventory reporting in business practice. This provides the basis for companies to take better actions and make faster financial decisions.

The Inventory Routing Problem Under Uncertainty

In the inventory routing problem, the supplier acts as a central decision maker who determines the replenishment quantities and also, the delivery times and routes to all retailers. In “Inventory Routing Problem Under Uncertainty”, Cui et al. develop a novel framework for the uncertain inventory routing problem and allow ambiguity in the probability distribution of each retailer's uncertain demand. Adopting a service-level viewpoint, they minimize the risk of uncertain inventory levels violating a prespecified acceptable range. They quantify that risk using a new decision criterion, the service violation index, that accounts for how often and how severely the inventory requirement is violated. The solutions proposed here are adaptive in the sense that they vary with the realization of uncertain demand. They provide algorithms to solve the problem exactly and then, demonstrate the superiority of their solutions by comparing them with several benchmarks.

배전반 불량 검사공정의 재설계와 생산정보시스템 구축에 관한 사례연구

Purpose: If material or product defects occur, additional products must be reproduced to the extent of the number of products carrying the defects. The reproduction of additional products requires re-establishing material inventory and understanding product requirements. This study introduces realistic material requirement planning and production delay minimization methods by considering the occurrence of defects.BRMethods: The study presents a reengineering method for quality control, process control, and production tracking and proposes traceability management processes to minimize material requirement planning and production delays. We proposed an improved work process that enables real-time information sharing between the production, material, and quality control departments to reduce production delays and enhance work efficiency.BRResults: This study devised a production information system applying reengineering. The developed system was applied to H company’s switchboard production to increase production efficiency.BRConclusion: As a result of applying the production information system, reflecting the improved work process to share standardized information for the switchboard production system of H company, information that was not previously shared in an integrated manner was shared, thereby accelerating business decision-making. In addition, based on the occurrence of defects, reproduction and inventory management were automatically updated, enabling accurate production management.

Current requirements for inventory in healthcare organizations

The article discusses the content of two federal standards “Events after the reporting date” — for commercial organizations and for public sector organizations. Similar methodological approaches have been identified in the recognition, accounting and reporting of events after the reporting date. The list of issues requiring inclusion in the accounting policy of the organization in terms of events after the reporting date is considered. It is shown that events after the reporting date are a consequence of the organization’s work in a risky environment. This requires the identification and regular monitoring of risks. Based on the consideration of the risk system inherent in medical organizations, recommendations are given on the disclosure of information about risk factors and their consequences in the context of economic sanctions.

Substation Equipment Spare Parts’ Inventory Prediction Model Based on Remaining Useful Life

A large variety of high-value substation relay protection equipment occupies a considerable amount of inventory space and capital in electric power companies. To improve this problem, this study proposes an inventory prediction model based on the remaining useful life (RUL) of equipment. The model acquires the RUL data of equipment by using the support vector regression (SVR) algorithm, and then, by taking this data as the main factor and the environmental factors and human factors during the operation of equipment as secondary factors, the model can realize the prediction of relay protection equipment in the substation. At the same time, the nature of the enterprise and the requirements for safety inventory are considered. The comparison of calculation results and error analysis, as well as the calculation time, all indicate that the RUL-based inventory forecasting is the best one. This model not only has high prediction accuracy but also has strong stability and portability. The model can provide a strong decision basis for improving the inventory management of the enterprise, enhancing the resource allocation capability, and formulating the spare parts procurement plan under the condition that the spare parts inventory reaches the safety stock.