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Rapidly growing population and increasing amount of shipments induced by the e-commerce are two of the main reasons for the constantly rising urban freight traffic. Cities are therefore overwhelmed by a growing stream of goods and the available infrastructure, shared between people and goods traffic, often reached its maximum capacity. Phenomena such as traffic congestion, pollution and lack of space are direct consequences of this trend and their impact on the quality of life in the city is not negligible. City administrations are keen to evaluate innovative city logistics concepts and adopt alternative solutions, to overcome the challenges posed by such a dynamic environment, constrained in existing infrastructure. In this paper, a heuristic method based on the utility analysis is presented. Thanks to a modular approach accounting for stakeholders´ requirements, possible different scenarios and available technologies, the development of new city logistic concepts is supported. The proposed method is then applied to a case study concerning the city of Reutlingen (Germany). Results are presented and a brief discussion leads to the conclusion.
The high system flexibility necessary for the full automation of complex and unstructured tasks leads to increased technological complexity, thus to higher costs and lower performance. In this paper, after an introduction to the different dimensions of flexibility, a method for flexible modular configuration and evaluation of systems of systems is introduced. The method starts from process requirements and, considering factors such as feasibility, development costs, market potential and effective impact on the current processes, enables the evaluation of a flexible systems of systems equipped with the needed functionalities before its actual development. This allows setting the focus on those aspects of flexibility that add market value to the system, thus promoting the efficient development of systems addressed to interested customers in intralogistics. An example of application of the method is given and discussed.
According to several surveys and statistics, the great majority of companies previously not accustomed to automation are piloting solutions to automate business processes. Those accustomed to automation also attempt to introduce more of it, focusing on automation-unfriendly processes that remained manual. However, when the decision on what and whether to automate is not trivial for evident reasons, even industry leaders may get stuck on an overwhelming question: where to begin automating? The question remains too often unanswered as state-of-the-art methods fail to consider the whole picture. This paper introduces a holistic approach to the decision-making for investments in automation. The method supports the iterative analysis and evaluation of operative processes, providing tools for a quantitative approach to the decision-making. Thanks to the method, a large pool of processes can be first considered and then filtered out in order to select the one that yields the best value for the automation in the specific context. After introducing the method, a case study is reported for validation before the discussion.
The EU funded project RobLog recently developed a system able to autonomously unload coffee sacks from a standard container. Being the first of its kind, a further development is needed in order for the system to be competitive against manual labor. Financing this development entails a risk, hence a justified skepticism, which can be overcome by the longsighted view of the existing market potential. This paper presents a method to estimate the market potential of autonomous unloading systems for heavy deformable goods. Starting from the analysis of the coffee trade, first the current coffee traffic is investigated in order to calculate the number of autonomous systems needed to handle the imported sacks; Results are validated and the method is extended for the calculation of the potential of other market segments, where the same unloading technology can be applied.
Reacting to ever-changing business environments, in the last decade complex systems of systems accomplished giant leaps forward leading to great technological flexibility. However, this dimension of flexibility is often limited by the rigidity of super-ordinated planning systems. Especially when hybrid teams of automated and human resources are in place, the dynamic assignment of tasks taking into account ergonomics remains a challenge. After exposing a gap in the state of the art on the topic, this paper presents an approach to include ergonomics in dynamic resource allocation models. Combining and complementing existing approaches, the presented method monitors the actual ergonomic burden of the resources during a shift and it provides a linear optimization model to steer the resource allocation process.
According to a recent survey the great majority of players in logistics are planning to adopt one or more robotic solutions until 2019. Technical solutions for automation of processes in logistics are often available as a market-ready product, but the lack of standardization and skepticism towards long term investments are often the reasons why these solutions are not implemented on a large scale. This paper is set to bridge the gap between the world of technologies and the one of applications in order to help investors, robot producers and system integrators to decide on which branch of logistics to set their focus. The three main branches Courier Express Parcel (CEP), contract logistics and production logistics are briefly defined and distinguished through their characteristic factors and parameters. Then a method based on the analysis of three parameters (operative costs, required performance and flexibility) in the three branches is set to identify the most convenient branch of logistics for investing in new technologies, namely the one in which the risk of investment is lower, the return is higher and faster. The conclusion of the method shows that higher labor costs, strict regulations and higher standardization make the production logistics the most suitable branch for investments in emerging automation solutions.
Evaluation of human-robot order picking systems considering the evolution of object detection
(2022)
The automation of intralogistic processes is a major trend, but order picking, one of the core and most cost-intensive tasks in this field, remains mostly manual due to the flexibility required during picking. Reacting to its hard physical and ergonomic strain, the automation of this process is however highly relevant. Robotic picking system would enable the automation of this process from a technical point of view, but the necessity for the system to evolve in time, due to dynamics of logistic environments, faces operations with new challenges that are hardly treated in literature. This unknown scares potential investors, hindering the application of technically feasible solutions. In this paper, a model for the evaluation of the additional cost of training of automated systems during operations is presented, that also considers the savings enabled by the system after its evolution. The proposed approach, that considers different parameters such as capacity, ergonomics and cost, is validated with a case study and discussed.
The paper focuses on a recently introduced paradigm for the logistic process of picking, with respect to the man-to-goods and goods-to-man concept: the robot to-goods. First the task and system architecture of the fast deployable autonomous commissioning system are described, then the economic efficiency of the system is analysed in a real business case scenario using a simplified method, which is explained and discussed. The clearly positive net present value of the investment and the short payback period obtained in the business case prove how the robot-to-goods paradigm for the commissioning process, implemented through the automation of the forklift platform, is economically attractive for small and medium size enterprises.
Latest advancements in new technologies have made it possible to fully automate the in-plant material flow of small load carriers between the warehouse and the production or assembly line. However, none of methods available in literature fully addresses the planning and dimensioning problem of a logistic system based on these new autonomous technologies. This paper is set to present a method to estimate the fleet size of the new logistic system. After an overview on the state of the art, the method based on combinatorics and probability theory will be explained. A short discussion and suggestions for forthcoming research will conclude the paper.
Powered by e-commerce and vital in the manufacturing industry, intralogistics became an increasingly important and labour-intensive process. In highly standardized automation-friendly environments, such as the automotive sector, most of efficiently automatable intralogistics tasks have already been automated. Due to aging population in EU and ergonomic regulations, the urge to automate intralogistics tasks became consistent also where product and process standardization is lower. That is the case of the production line or cell material supply process, where an increasing number of product variants and individually customized products combined with the necessary ability of reacting to changes in market conditions led to smaller and more frequent replenishment to the points of use in the production plant and to the chaotic addition of production cells in shop floor layout. This led in turn to inevitable traffic growth with unforeseeable related delays and increased level of safety threats and accidents. In this paper, we use the structured approach of the Quality Interaction Function Deployment to analyse the process of supply of assembly lines, seeking the most efficient combination of automation and manual labour, satisfying all stakeholders´ requirements. Results are presented and discussed.