Decision making in inventory control by using artificial neural networks

Cevallos-Torres, Lorenzo; Botto-Tobar, Miguel; Cadena, Angela Diaz; León-Granizo, Oscar

doi:10.37868/sei.v4i1.id150

Cited by 3 publications

(3 citation statements)

References 1 publication

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“…1) Backup copy of the "Mobility" database: As a first step, the backup of the "Mobility" Database was carried out, which is part of a larger research project, originally this database is hosted in the services of AWS (Amazon Web Service) and has information of the trajectories of the objects in the movement of certain days and hours in which the data collection was carried out [18].…”

Section: H Methodological Design Of the Researchmentioning

confidence: 99%

Predictive Algorithms Analysis to Improve Sustainable Mobility

León-Granizo

Botto-Tobar

2022

JOIV : Int. J. Inform. Visualization

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The work is based on carrying out a comparative analysis of 3 prediction algorithms (Linear Regression, Neural Networks, and KNN), which allow the study of information on georeferential coordinates of moving objects, since through an exhaustive study it will be possible to know the predictions of each one. of them and then proceed to comply with the main objective that is to implement the algorithm with greater accuracy and effectiveness, making use of open Source tools that allow working with Machine Learning and thus be able to analyze the forecasts of traffic congestion that is formed in the surroundings of the University of Guayaquil, because this generates a great inconvenience for students and administrative personnel who belong to this institution and diminish an improvement in sustainable mobility. The methodology used is the Waterfall methodology, as it is a linear model of simple implementation, where each phase of the project was emphasized, allowing possible disorientation of the results to be managed and achieving the development of the proposed project without any inconvenience.

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Section: H Methodological Design Of the Researchmentioning

confidence: 99%

Predictive Algorithms Analysis to Improve Sustainable Mobility

León-Granizo

Botto-Tobar

2022

JOIV : Int. J. Inform. Visualization

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“…Moreover, they are cost-efficient and simple to manufacture [16]. Statistical tools are predominantly used for stock management, such as the Monte Carlo simulation method [17]. Also, the supply chain of the products plays a vital role in stock management.…”

Section: Introductionmentioning

confidence: 99%

Conductive Polymer-Based Interactive Shelving System for Real-Time Inventory Management

Sikkandhar,

Lim,

Damalerio

et al. 2023

Sensors

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Stockouts constitute a major challenge in the retail industry. Stockouts are caused by errors related to manual stockkeeping and by the misplacement of items on shelves. Such errors account for up to 4% of lost sales. Real-time inventory management systems for misplaced items or missing stock detection in retail stores are limited. Accordingly, a conductive polymer-based interactive shelving system for real-time inventory management is developed. The system comprises an 80 × 48 sensor array fabricated by screen-printing a piezoresistive carbon-based conductive polymer layer onto gold interdigitated electrodes deposited on a flexible substrate. Each sensing pixel has dimensions of 5 mm × 5 mm and a sensing area of 4 mm × 4 mm. The sensor mat can detect the shape and weight features of stockkeeping units (SKUs), which can then be analyzed by a TensorFlow model for SKU identification. The developed system is characterized for functional resistance range, uniformity, repeatability, and durability. The accuracy of SKU identification achieved using shape features only and the accuracy of SKU identification achieved using both shape and weight features is 95% and 99.2%, respectively. The key novelty of the work is the development of a deep learning-embedded interactive smart shelving system for retail inventory management by using the shape and weight features of SKU. Also, the developed system helps to detect the SKU if they are stacked one over the other. Furthermore, multiple sensor mats implemented on various shelves in a retail store can be modularized and integrated for monitoring under the control of a single PC. Accordingly, the proposed retail inventory tracking system can facilitate the development of automated “humanless” shops.

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“…Recently, both work on inventory management and process optimization work are present in the literature, even more so in the beverage sector. However, for the most part, medium and large companies are approached, or more robust (and not so accessible) technologies are used (Abu Zwaida et al, 2021;Cevallos-Torres et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Process Optimization: A Beverage Distributor Using Organizational Tools and Modeling Via Petri Nets

Almeida¹

2022

Proceedings of the 4th International Conference on Advanced Research in Applied Science and Engineering

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In the face of a competitive scenario, quality management assumes an important role by presenting itself as a strategy capable of helping organizations to achieve the expected results. In this context, the present work analyzes the processes of a small beverage distributor, in order to find bottlenecks and propose improvement solutions. The concepts and theories are based on organizational tools and on the stages of the planning phase of the PDCA cycle: problem identification, observation, analysis and, finally, the action plan. The study begins with the identification of the problem through technical visits and interviews with the manager. Then, in the observation phase, organizational tools were applied to improve processes and reduce losses. Finally, the organization and standardization of data contributed to improving inventory management, managing the billing process of the company and drawing up future strategic plans using technologies for data management and scenario simulation. The simulations used Petri Nets, a structure defined in the literature, for their representation and application. This case study is a demonstration of the management optimization potential of a small entrepreneur, in the Brazilian market, where the recovery of control of its processes during the pandemic period is demonstrated.

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Decision making in inventory control by using artificial neural networks

Cited by 3 publications

References 1 publication

Predictive Algorithms Analysis to Improve Sustainable Mobility

Predictive Algorithms Analysis to Improve Sustainable Mobility

Conductive Polymer-Based Interactive Shelving System for Real-Time Inventory Management

Process Optimization: A Beverage Distributor Using Organizational Tools and Modeling Via Petri Nets

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