1,721,035 research outputs found
A Timed Petri Nets Model for Performance Evaluation of Intermodal Freight Transport Terminals
Full text linkThis paper presents a general modeling framework for Intermodal Freight Transport Terminals (IFTTs). The model allows simulating and evaluating the performance of such key elements of the intermodal transportation chain. Hence, it may be used by the decision maker to identify the IFTT bottlenecks, as well as to test different solutions to improve the IFTT dynamics. The proposed modeling framework is modular and based on timed Petri Nets (PNs), where places represent resources and capacities or conditions, transitions model inputs, flows, and activities into the terminal and tokens are intermodal transport units or the means on which they are transported. The model is able to represent the different types of existing IFTTs. Its effectiveness is tested first on an example from the literature and then on a real case study, the railroad inland terminal of a leading Italian intermodal logistics company, showing its ease of application. In the real case study, using the proposed formalism we test the as-is IFTT performance and evaluate alternative possible to-be improvements in order to identify and eliminate emerging criticalities in the terminal dynamics
Efficient Resource Planning of Intermodal Terminals under Uncertainty
No full textThis paper presents a decision support tool for the efficient resource planning and management of intermodal terminals under uncertainty, allowing to address the planning issue under imprecise or uncertain data (e.g., estimates on flows, resource utilization, operating conditions). The procedure consists of three steps: 1) the definition of a Timed Petri Net model of the terminal; 2) the computation of suitable performance indices to evaluate whether the current configuration is able to cope with a foreseen increase in the freight flows; 3) in the case of not satisfactory values of the indices at the previous step, the simulation of alternative planning solutions and the detection of the most efficient one via a cross efficiency fuzzy Data Envelopment Analysis technique. In order to test its effectiveness, the procedure is applied to a real case study. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved
Decision and Control Approaches for Enhancing the Resilience of Distribution Networks: a Survey
No full textRecently, the concept of resilience of electrical infrastructures has been introduced to quantify the ability of the grid to resist, adapt to, and rapidly recover after the occurrence of high-impact and low-probability (HILP) events. Various surveys discuss the state of the art on the resilience of distribution networks (DNs), which are a subsystem of the electrical infrastructure particularly susceptible to HILP events. It emerges that automation has a central role in guaranteeing and enhancing DNs resilience, although a classification of the existing contributions is missing. To fill this gap, in this paper we review the literature contributions regarding decision and control methods to enhance the resilience of DNs. We classify the reviewed approaches into tactical/strategic and operational level ones, we group them by the time of application and type, and finally we provide a detailed discussion and comparison of the available methods, highlighting open issues and future trends in this field
Logistics 4.0: A Matheuristics for the Integrated Vehicle Routing and Container Loading Problem
No full textThe increasing demand for freight transport requires logistic companies to improve their competitiveness by ensuring high service levels at limited costs. This paper investigates the problem of defining delivery plans with the aim to support logistic companies in reducing planning times and freight delivery costs. In delivery planning, given a set of delivery requests, both the routes and load configurations of Transport Units (TUs) are to be established. In the literature, this problem is defined as Three-dimensional Loading Capacitated Vehicle Routing Problem with Time Windows (3LCVRPTW). However, these problems are generally tackled separately and referred to as the vehicle routing problem and the container loading problem, respectively. Moreover, only a few contributions present solution approaches for real logistic systems, and these methods are mainly based on heuristics. In this work, we define a novel matheuristic algorithm for the integrated solution of the vehicle routing problem and container loading problem. The proposed method is suitable for real logistic applications and combines the advantages of exact solutions with the rapidity of heuristics. The approach aims at minimizing the total travel costs and the clients' time windows violations in the routes' definition, while optimizing the configuration of the cargo inside each TU. The developed matheuristic algorithm is tested both on a well-known literature benchmark and on a real dataset provided by the Italian company Elettric80. The obtained results show that the proposed method succeeds in determining in a short computational time both feasible routes and loading plans, minimizing the related costs while fulfilling logistics constraints
An Integrated Model Predictive Control Method for the Rescheduling of Metro Traffic with Backup Trains
No full textIn large cities, metro lines are often saturated and impacted by sudden events to the point that some stations in the network become overcrowded and multiple trains are seriously delayed, causing the increase of passengers' waiting time. This disservice can be reduced by rescheduling the metro traffic and by adding backup trains in storage lines to be used when the service level largely decreases. In this paper, a novel control strategy, called Integrated Model Predictive Control, is proposed that combines both timetable rescheduling and backup trains allocation. In particular, a state-space model is adopted to describe the evolution of the train traffic dynamics and the model predictive control method is applied to obtain an optimal controller such that the rescheduled departure time and headway deviations from the nominal timetable are minimized. In the case where no feasible controller exists because of extensive delays, we propose an event-triggered process to automatically add backup trains into the operation plan such that the timetable can recover quickly. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed control method
Process Re-engineering Based on Colored Petri Nets: the Case of an Italian Textile Company
No full textBusiness process re-engineering is crucial for manufacturing companies to improve their productivity and efficiency. The identification of the main criticalities affecting the production processes and the implementation of effective re-engineering solutions can significantly reduce the company losses. However, such actions can be unsuccessful if suitable preliminary investigations on the effectiveness of the solutions are not performed. This paper proposes an integrated process re-engineering technique that allows to: identify workflows via the Unified Modeling Language; model and simulate the business process via Colored Petri Nets (CPNs); detect bottlenecks and waste sources through the Value Stream Mapping tool; rank the impact of the detected criticalities via a mathematical formulation of the Genba-Shikumi lean philosophy; simulate the re-engineering actions and evaluate their effectiveness using the CPN model. The aim is to offer an intuitive tool for strategic decision making, deployable at a managerial level in a digital twin approach. The proposed technique is tested on a textile company located in Southern Italy, showing its effectiveness in removing inefficiencies and ensuring the continuous improvement of the production process
An adaptive constrained clustering approach for real-time fault detection of industrial systems
No full textA Semi-Supervised Learning Approach for Fault Detection and Diagnosis in Complex Mechanical Systems
No full textThe integration of artificial intelligence in mechanical fault detection and diagnosis (FDD) helps to increase reliability, reduce costs, and improve the overall performance of mechanical systems in Industry 4.0 applications. Most interesting industrial applications nowadays come from dynamic environments where data are generated continuously over time and where the labeled data are scarce and expensive. Therefore, semi-supervised learning (SSL) can be particularly useful in FDD because faults may be rare or difficult to identify, and may not be fully represented in the labeled data. By using a combination of labeled and unlabeled data, SSL can help to identify these rare or difficult-to-detect faults, leading to more effective FDD. In this paper, graph-based SSL relying on label propagation is combined with conventional classification algorithms to detect potential failures in complex mechanical systems. Experimental results on realistic pneumatic and hydraulic systems from the related literature show that the proposed method can effectively enlarge the labeled datasets and interestingly identify different types of non-nominal conditions with higher accuracy compared to baseline methodologies
A mathematical model for the optimal configuration of automated storage systems with sliding trays
No full textThis work aims at contributing to the advancement of Logistics 4.0, focusing on the management of the storage of goods. The goal is to solve the complex problem of efficiently and rapidly configuring Vertical Lift Modules (VLMs) with sliding trays in automated warehouses. This problem is still barely discussed in the related literature and most contributions mainly focus on the optimization of the VLM throughput instead of trays allocation and respective items configuration. To fill this gap, this work proposes a novel mathematical model that allows to properly represent and solve this complex problem, taking into account practical logistic constraints. The problem is defined as a mixed integer non-linear programming model, which is validated on realistic scenarios. Further, a scalability analysis is performed to evaluate its performance even in complex scenarios. The obtained results demonstrate the effectiveness of the model in defining space efficient configurations in short computation time
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