Sustainable supply chain management in the digitalisation era: The impact of Automated Guided Vehicles

Internationalization of markets and climate change introduce multifaceted challenges for modern supply chain (SC) management in the today's digitalisation era. On the other hand, Automated Guided Vehicle (AGV) systems have reached an age of maturity that allows for their utilization towards tackling dynamic market conditions and aligning SC management focus with sustainability considerations. However, extant research only myopically tackles the sustainability potential of AGVs, focusing more on addressing network optimization problems and less on developing integrated and systematic methodological approaches for promoting economic, environmental and social sustainability. To that end, the present study provides a critical taxonomy of key decisions for facilitating the adoption of AGV systems into SC design and planning, as these are mapped on the relevant strategic, tactical and operational levels of the natural hierarchy. We then propose the Sustainable Supply Chain Cube (S2C2), a conceptual tool that integrates sustainable SC management with the proposed hierarchical decision-making framework for AGVs. Market opportunities and the potential of integrating AGVs into a SC context with the use of the S2C2 tool are further discussed

Towards the development of a smart flying sensor: illustration in the field of precision agriculture

Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying sensor based on an unmanned aerial vehicle (UAV). The concept of smart remote sensing is illustrated and its performance tested for the task of mapping the volume of grain inside a trailer during forage harvesting. Novelty lies in: (1) the development of a position-estimation method with time delay compensation based on inertial measurement unit (IMU) sensors and image processing; (2) a method to build a 3D map using information obtained from a regular camera; and (3) the design and implementation of a path-following control algorithm using model predictive control (MPC). Experimental results on a lab-scale system validate the effectiveness of the proposed methodology

Autonomous Unmanned Ground Vehicles for Urban Logistics: Optimization of Last Mile Delivery Operations

In an era dominated by ongoing urbanization and rising e-commerce, the efficient delivery of goods within cities becomes a major challenge. As a new element of urban logistics, we discuss the potential of autonomous unmanned ground vehicles (AUGV) regarding the last mile delivery of shipments to customers. We propose an optimization model to minimize the delivery costs of urban shipments using AUGV. Simultaneously, best locations from a set of existing stations are selected for AUGV positioning and optimal route determination. With our developed Location Routing Problem, we provide decision support for parcel service providers, city authorities, and other relevant decision makers. Regarding the Green Information Systems domain, we tackle the lack of solution-oriented research addressing a more sustainable and locally emission free supply of goods within urban areas

Towards a cloud‑based automated surveillance system using wireless technologies

Cloud Computing can bring multiple benefits for Smart Cities. It permits the easy creation of centralized knowledge bases, thus straightforwardly enabling that multiple embedded systems (such as sensor or control devices) can have a collaborative, shared intelligence. In addition to this, thanks to its vast computing power, complex tasks can be done over low-spec devices just by offloading computation to the cloud, with the additional advantage of saving energy. In this work, cloud’s capabilities are exploited to implement and test a cloud-based surveillance system. Using a shared, 3D symbolic world model, different devices have a complete knowledge of all the elements, people and intruders in a certain open area or inside a building. The implementation of a volumetric, 3D, object-oriented, cloud-based world model (including semantic information) is novel as far as we know. Very simple devices (orange Pi) can send RGBD streams (using kinect cameras) to the cloud, where all the processing is distributed and done thanks to its inherent scalability. A proof-of-concept experiment is done in this paper in a testing lab with multiple cameras connected to the cloud with 802.11ac wireless technology. Our results show that this kind of surveillance system is possible currently, and that trends indicate that it can be improved at a short term to produce high performance vigilance system using low-speed devices. In addition, this proof-of-concept claims that many interesting opportunities and challenges arise, for example, when mobile watch robots and fixed cameras would act as a team for carrying out complex collaborative surveillance strategies.Ministerio de Economía y Competitividad TEC2016-77785-PJunta de Andalucía P12-TIC-130

Industry 4.0 technologies within the logistics sector: the key role of innovative start-ups

The goal of the study is to analyze the 4.0 innovation in the logistics sector. First, it is provided a view of Industry 4.0 technologies, followed by a focus on Logistics 4.0 technologies as theoretical background. Then, through a patent analysis, the study analyzes in details the logistics sector in order to pursue and to demonstrate where is the origin of innovation in the sector

The influence of logistics innovations on management of freight-transportation processes

Time is one of the main factors, and it affects the decision of costumers while choosing a particular transportation company. Every stage of logistics processes takes a particular period. That is why almost every firm thinks about the ways of decreasing the time wastes in order to maximize the profit of business. The objective of this research is to explore how different logistics innovations can affect freight transportation processes and save operational time. To achieve this goal and explore the topic more deeply, a list of articles published in worldwide databases related to this domain was analyzed and interpreted. The survey on freight transportation was used to get a better knowledge of today’s situation of freight systems. Based on the result of this article, it is suggested that new ideas for the management of companies in this sphere are suggested. The findings of this research can help Kazakhstan’s logistics companies to develop better strategies and to adopt innovative logistics technologies into freight transportation. They can make them become innovation-based logistics service providers.- (undefined

Robotized sorting systems: Large-scale scheduling under real-time conditions with limited lookahead

A major drawback of most automated warehousing solutions is that fixedly installed hardware makes them inflexible and hardly scalable. In the recent years, numerous robotized warehousing solutions have been innovated, which are more adaptable to varying capacity situations. In this paper, we consider robotized sorting systems where autonomous mobile robots load individual pieces of stock keeping units (SKUs) at a loading station, drive to the collection points temporarily associated with the orders demanding the pieces, and autonomously release them, e.g., by tilting a tray mounted on top of each robot. In these systems, a huge number of products approach the loading station with an interarrival time of very few seconds, so that we face a very challenging scheduling environment in which the following operational decisions must be taken in real time: First, since pieces of the same SKU are interchangeable among orders with a demand for this specific SKU, we have to assign pieces to suitable orders. Furthermore, each order has to be temporarily assigned to a collection point. Finally, we have to match robots and transport jobs, where pieces have to be delivered between loading station and selected collection points. These interdependent decisions become even more involved, since we (typically) do not posses complete knowledge on the arrival sequence but have merely a restricted lookahead of the next approaching products. In this paper, we show that even in such a fierce environment sophisticated optimization, based on a novel two-step multiple-scenario approach applied under real-time conditions, can be a serviceable tool to significantly improve the sortation throughput

ZASTOSOWANIE SZTUCZNEJ INTELIGENCJI W ZAUTOMATYZOWANYCH CENTRACH LOGISTYCZNYCH

The paper deals with the problem of works transport organization in logistic center with the use of artificial intelligence algorithms. The presented approach is based on non-changeable path during travel along a given loop. The ordered set of containers requesting transport service was determined by fuzzy logic, while the sequence of containers in a loop was optimized by genetic algorithms. A solution for semi-autonomous transport vehicles wherein the control system informs the driver about optimal route was presented. The obtained solution was verified by a computer simulation.Artykuł dotyczy problematyki sterowania transportem wewnątrzzakładowym w zautomatyzowanych centrach logistycznych z zastosowaniem metod sztucznej inteligencji. Zaprezentowane podejście zakłada predykcję niezmiennej trasy  przejazdu środka transportu. Kolejność zbioru regałów wymagających obsługi transportowej jest determinowana przez logikę rozmytą, natomiast do optymalizacja trasy przejazdu wykorzystano algorytmy genetyczne. Zaprezentowano koncepcję środka transportu, w którym system sterowania informuje kierowcę dokąd ma jechać. Uzyskane rozwiązanie zostało zweryfikowane z wykorzystaniem metod symulacji komputerowej