Logistics as a competitive advantage in retail organizations

Retail plays an important role in the trade sector of the Brazilian economy, with net operating revenues of nearly BRL 1.7 trillion and more than 7 million workers in 2018, according to the latest Annual Trade Survey from the Brazilian Institute of Geography and Statistics. The entry of large multinational companies into the Brazilian retail market, where it is worth highlighting Amazon, has negatively impacted the market of Brazilian retail companies, which still use archaic methods and disqualified labor in their operations and processes. Amazon provides better logistics services that directly add value to the quality of products offered through a leaner and more profitable supply chain. Additionally, the behavioral changes brought about by Covid-19 have made consumers more satisfied with online shopping experiences than with visits to physical stores. The increase in internet shopping and the reduction of visits to sales outlets has caused a migration of consumption to digital media, which may generate long-term transformations in the strategies of companies. Thus, the objective of this research is to provide a conceptual proposal of the use of logistics as a competitive advantage in retail organizations, considering the best management practices for the logistics sector. As a research methodology, a systematic literature review was adopted, based on the PRISMA protocol, allowing the identification of 94 records, 12 of which were included in the literature review, due to their adherence to the researched theme. The main contribution of this paper is the development of a conceptual proposal for the use of logistics as a competitive advantage in retail organizations, comprising five aspects: Information Systems, Application of KPIs aligned with the Strategic Objectives of the Organization, Creating Value for Products, Modern Management Concept and, Need for Organizations to recognize the Benefits and Advantages of Logistics

A Search Strategy of Level-Based Flooding for the Internet of Things

This paper deals with the query problem in the Internet of Things (IoT). Flooding is an important query strategy. However, original flooding is prone to cause heavy network loads. To address this problem, we propose a variant of flooding, called Level-Based Flooding (LBF). With LBF, the whole network is divided into several levels according to the distances (i.e., hops) between the sensor nodes and the sink node. The sink node knows the level information of each node. Query packets are broadcast in the network according to the levels of nodes. Upon receiving a query packet, sensor nodes decide how to process it according to the percentage of neighbors that have processed it. When the target node receives the query packet, it sends its data back to the sink node via random walk. We show by extensive simulations that the performance of LBF in terms of cost and latency is much better than that of original flooding, and LBF can be used in IoT of different scales

Sistema de informação gerencial como ferramenta para tomada de decisão: um estudo de caso em uma distribuidora de energia elétrica do nordeste brasileiro

No âmbito empresarial, na atual era da informação, é verificada a importância que se atribui aos Sistemas de Informações Gerenciais (SIG), uma vez que as informações quando de lá são colhidas servem de subsídios para os gestores na confecção de relatórios gerenciais, trazendo-lhes segurança para uma eventual tomada de decisão. Sendo assim, o objetivo principal desse estudo foi verificar como o SIG de uma empresa de energia elétrica, situada no nordeste do Brasil, contribui para tomada de decisão dos seus gestores. Para tal, realizou-se uma pesquisa descritiva, de natureza qualitativa e que foi organizada em um estudo de caso, no qual coletou-se, por meio de um roteiro de entrevistas disponível no correio eletrônico da empresa, respostas de 6 (seis) gestores de departamentos diferentes. As principais evidências apontam que o SIG contribui para tomada de decisões importantes na distribuidora, tais como melhor comunicação entre as estações, gestão de recursos financeiros, proporcionam ações corretivas para indicadores que estão fora de meta e melhoram a gestão de resultados. Ademais, essas decisões impactam diretamente em um melhor atendimento aos clientes, na otimização do uso dos recursos financeiros excedentes, na redução de custos e no aumento da produtividade dos colaboradores

Sistema de informação: benefícios auferidos com a implantação de um sistema WMS em um centro de distribuição do setor têxtil em Natal/RN

Os sistemas de informações (SI) vêm sendo largamente utilizados nas organizações como vantagem competitiva, auxiliando os gestores em suas tomadas de decisão. Um dos SI que gerencia de forma eficiente e eficaz um centro de distribuição (CD) é denominado WMS (Warehouse Management System). O presente trabalho tem como objetivo geral descrever as melhorias advindas da implantação de um sistema de gerenciamento de CD, tendo como foco a área de processamento de mercadorias em uma grande empresa do setor têxtil em Natal/RN. Associado ao objetivo geral, o estudo também pretende analisar o fluxo das mercadorias e analisar o sistema de informação gerencial atual da empresa estudada. Como resultados verificou-se a redução no lead time das mercadorias em 24%, o aumento da produtividade dos funcionários e a melhora na gestão do CD. Outro ponto de destaque foi a eliminação de locais predeterminados para as mercadorias, otimizando o processo e o deslocamento dos colaboradores

The integration of supply chain value stream mapping and discrete event simulation for lead time reduction of warehouse operations in a pharmaceutical organization

The supply chain lead time build-up that occurs due to inventory handling inside the warehouse that comprises of a set of waiting time, queuing time, and unwanted delays creates difficulties in meeting demand shocks and third party stakeholder requirements. These problems consistently prevail and tend to evolve no matter how sophisticated production planning is done. In that case, a pharmaceutical warehouse supply chain inventory would be a real challenge to study or map to find out ways for further improvements. In this research, a Malaysian pharmaceutical company’s warehouse was considered for the study. After a detailed field work and literature gap inferences, a case study approach was considered to be the best methodology for this study. It was applied to find effective ways to introduce lean integrated simulation modelling using Supply Chain Value Stream Mapping (SCVSM) and Discrete Event Simulation (DES) to capture, record, analyze, and reduce inventory waiting time, delays, queues and other wastes for a selected particular product family. After several lean suggestions in the future state SCVSM, the results of this study show that there is a considerable improvement in the warehouse lead time. The production lead time and total process time has decreased by 51.43% and 44.41 % respectively. The total value-added time has increased by 29.21 % the non-value added time has decreased by 31.86 %. In the second segment, there was a 20.22 % increase in the value-added time and a 23.17 % decrease in the non-value added time. DES models were then developed to replicate the entire operations for the purpose of present and future state simulation along with the suggestions for improvements. This study proved to possess strong managerial and practical implications that shall help in better decision making by deeply understanding the supply chain activities that occur as discrete events inside a warehouse

Self-healing radio maps of wireless networks for indoor positioning

Programa Doutoral em Telecomunicações MAP-tele das Universidades do Minho, Aveiro e PortoA Indústria 4.0 está a impulsionar a mudança para novas formas de produção e otimização em tempo real nos espaços industriais que beneficiam das capacidades da Internet of Things (IoT) nomeadamente, a localização de veículos para monitorização e optimização de processos. Normalmente os espaços industriais possuem uma infraestrutura Wi-Fi que pode ser usada para localizar pessoas, bens ou veículos, sendo uma oportunidade para aumentar a produtividade. Os mapas de rádio são importantes para os sistemas de posicionamento baseados em Wi-Fi, porque representam o ambiente de rádio e são usados para estimar uma posição. Os mapas de rádio são constituídos por amostras Wi-Fi recolhidas em posições conhecidas e degradam-se ao longo do tempo devido a vários fatores, por exemplo, efeitos de propagação, adição/remoção de APs, entre outros. O processo de construção do mapa de rádio costuma ser exigente em termos de tempo e recursos humanos, constituindo um desafio considerável. Os veículos, que operam em ambientes industriais podem ser explorados para auxiliar na construção de mapas de rádio, desde que seja possível localizá-los e rastreá-los. O objetivo principal desta tese é desenvolver um sistema de posicionamento para veículos industriais com mapas de rádio auto-regenerativos (capaz de manter os mapas de rádio atualizados). Os veículos são localizados através da fusão sensorial de Wi-Fi com sensores de movimento, que permitem anotar novas amostras Wi-Fi para o mapa de rádio auto-regenerativo. São propostas duas abordagens de fusão sensorial, baseadas em Loose Coupling e Tight Coupling, para a localização dos veículos. A abordagem Tight Coupling inclui uma métrica de confiança para determinar quando é que as amostras de Wi-Fi devem ser anotadas. Deste modo, esta solução não requer calibração nem esforço humano para a construção e manutenção do mapa de rádio. Os resultados obtidos em experiências sugerem que esta solução tem potencial para a IoT e a Indústria 4.0, especialmente em serviços de localização, mas também na monitorização, suporte à navegação autónoma, e interconectividade.Industry 4.0 is driving change for new forms of production and real-time optimization in factories, which benefit from the Industrial Internet of Things (IoT) capabilities to locate industrial vehicles for monitoring, improving safety, and operations. Most industrial environments have a Wi-Fi infrastructure that can be exploited to locate people, assets, or vehicles, providing an opportunity for enhancing productivity and interconnectivity. Radio maps are important for Wi-Fi-based Indoor Position Systems (IPSs) since they represent the radio environment and are used to estimate a position. Radio maps comprise a set of Wi- Fi samples collected at known positions, and degrade over time due to several aspects, e.g., propagation effects, addition/removal of Access Points (APs), among others, hence they should be periodically updated to maintain the IPS performance. The process to build and maintain radio maps is usually time-consuming and demanding in terms of human resources, thus being challenging to perform. Vehicles, commonly present in industrial environments, can be explored to help build and maintain radio maps, as long as it is possible to locate and track them. The main objective of this thesis is to develop an IPS for industrial vehicles with self-healing radio maps (capable of keeping radio maps up to date). Vehicles are tracked using sensor fusion of Wi-Fi with motion sensors, which allows to annotate new Wi-Fi samples to build the self-healing radio maps. Two sensor fusion approaches based on Loose Coupling and Tight Coupling are proposed to track vehicles. The Tight Coupling approach includes a reliability metric to determine when Wi-Fi samples should be annotated. As a result, this solution does not depend on any calibration or human effort to build and maintain the radio map. Results obtained in real-world experiments suggest that this solution has potential for IoT and Industry 4.0, especially in location services, but also in monitoring and analytics, supporting autonomous navigation, and interconnectivity between devices.MAP-Tele Doctoral Programme scientific committee and the FCT (Fundação para a Ciência e Tecnologia) for the PhD grant (PD/BD/137401/2018

Indoor Positioning and Navigation

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot