1,720,978 research outputs found
A reference model for distributed decision making adopting a multi agent approach
Get PDFDuring the last years the decision making processes is evolving becoming more and more distributed and asynchronous. In order to support decision-makers who are not at the same place at the same time are defined cooperation processes and a set of models able to support designers of Cooperative decision support framework. One of this, proposed in this thesis, is a Reference Model to build Multi Agent System able to represent complex and distributed system composed by several intelligent collaborative entities. Following this definition, it is possible define like collaborative network a lot of complex system such as:
1. Flexible Manufacturing Systems (FMSs) that are defined by Ciliers (Ciliers P., 1998) as complex systems in which the knowledge of the system elements composition and the interaction between the environment and the system, is not enough to understand the system functioning;
2. Industrial Clusters (ICs) that can be defined as socioeconomic entities characterized by a social community of people and a population of economic agents localized in close proximity in a specific geographic region that interact to reach similar outcomes (Marshall, 1925);
3. Supply Chains (SCs), network of suppliers, factories, warehouses, distribution centres and retailers that operate in integrated manner (Fox, 1992) with the same aim of reducing inventory and costs, adding value, extending resource and accelerating the time to market.
4. Healthcare Systems, composed by several entities interacting in a great number of critical processes. The internal dynamics of an hospital represents a complex non-linear structure hard to manage in centralized way (Harper 2002).
The above mentioned list represents only a part of the numerousness examples of system that can be represented as collaborative networks and that need to be managed in distributed manner due to complexity and to great amount of information necessary to take any kind of decision. There are not many models able to represent and manage this kind of distributed systems, Petri nets represent one of this but present some limits due to: (i) the model become too large and complex even for a modest size problem (Wang J., Deng Y., 1999); (ii) the difficulty to make even a little change to a previously built model.
The Multi Agent System (MAS) approach aim to overcome these limits of rigidity and computing complexity trough: (i) the possibility to solve complex problem solving a set of easier local problems; (ii) the opportunity to change some problem parameters or to substitute any system element without discard entirely the original model. The MAS are widely studied in literature like method able to represent dynamic and distributed system with several decision makers having different information domains. It is possible to observe a lack in investigate the problem solving ability of intelligent agents in a multi-agent setting and a variety of representation methods. The difficulty of apply this model approach reside into the activity of architecture design used by the system elements to speak and act. The number and the kind of relations among the system entities became the most important indicator of the model's complexity. For this reason the outcome of my researches can be presented as a reference model integrating two types of approach for the models creation in the MAS field. The main scope is to provide the guidelines able to support the designer in the system modelling like MAS, indicating also in which scenario is more convenient to adopt an approach oriented to Operation Research (OR) technique or another one. The Reference Model is evaluated and validated thanks to several application in different contests, some of whom are mentioned at the beginning of this abstract
Digital and Sustainable Transition in Textile Industry through Internet of Things Technologies: A Pakistani Case Study
No full textThe textile industry, a vital contributor to Pakistan’s economy, faces pressing challenges in transitioning towards sustainability amid global environmental concerns. This manuscript presents a comprehensive case study on the implementation of IoT-driven strategies in the Pakistani textile sector to achieve digital and sustainable transformation. The findings reveal that the implementation of IoT technologies facilitated real-time environmental monitoring, enabling compliance with regulatory standards, and fostering sustainable manufacturing practices. Ultimately, this manuscript offers valuable insights into the transformative potential of IoT technologies in driving sustainable practices in the textile industry. The case study serves as a benchmark for other textile-producing regions aiming to embark on a digital and sustainable journey. These findings hold significant implications for the ongoing dialogue on sustainable industrial development, providing valuable direction for policymakers and stakeholders in shaping a more resilient and ecologically conscious future. Future research should prioritize addressing issues like data confidentiality and interoperability while adhering to standard requirements. Additionally, exploring analytics and machine learning methods for predictive maintenance, optimized performance, and operational improvement is crucial. © 2024 by the authors
Critical Infrastructures Overview: Past, Present and Future
No full textIndustrialized societies depend on the proper functioning of a whole range of technological infrastructures, such as electricity, road and railway networks and telecommunications which, due to their importance, are generically referred to as critical infrastructures (CIs). Technical failures, natural disasters and malicious events, if not terrorist, could have devastating effects on these infrastructures. The events of the last few years have accelerated efforts to identify and designate CIs at national and European levels and have reinforced concerns about increasing their protection in sensitive sectors for the safety of the individual and the community. The aim of this research is to provide the basic elements to understand the issue along with the reasons for its importance both at national, European and international level. In particular, after analyzing the origin of the problem, a systematic literature review is carried out to study the current research around future perspectives relating to the management of Cis, with particular focus on three research questions: RQ1 “What types of risk assessment methods are used to manage CIs?”, RQ2 “What are the environmental risk mitigation strategies for CIs?” and RQ3 “What is the role of the human factor in the prevention of risks for CIs?”. The results aim to be guidelines for decision makers and researchers interested in this topic
Optimizing public investments: A Sustainable Economic, Environmental, and Social Investment Multi-criteria Decision Model (SEESIM)
No full textOne of the most important aspects for the economic and social growth of a country is high efficiency of public investments. This imperative has never been more critical, especially in the context of Europe and Italy, where the integration of environmental, economic, and social goals is essential to address the multifaceted challenges of the 21st century. This research introduces the Sustainable Economic, Environmental, and Social Investment Model (SEESIM), a novel multi-criteria decision-making framework designed to ensure the sustainability of projects as their validity over time, especially from a National Recovery and Resilience Plan perspective. Utilizing the Analytic Hierarchy Process (AHP), SEESIM integrates environmental, economic, and social criteria as useful tool to evaluate a project in the post-funding phase, ensuring a balanced approach to efficiency and sustainability. The model is adaptable to various regional contexts, providing a transparent and replicable methodology for assessing the impacts and costs of public investments. An experimental scenario demonstrates SEESIM's utility in guiding investment decisions, highlighting its potential to significantly enhance the effectiveness of public resources in achieving long-term sustainability goals. SEESIM represents a pivotal advancement in sustainable development strategies, offering a comprehensive tool for integrating multi-dimensional sustainability criteria into public investment decisions
An application of Project Management techniques for the estimation of processing times in industrial projects with a high degree of innovation
Get PDFDuring the last few years, both industrial and academic people have questioned the usefulness of Project Management (PM) tools in manufacturing field. Despite several applications arising from PM now known like time management, risk management, budgeting, scheduling and others, these tools appear to be barely used where industrial projects are characterized by a high degree of innovation. Throughout history the great uncertainty about innovative projects duration obliged project managers to overestimate processing time as precautionary behaviour. This conduct often precludes new project opportunities for companies, decreasing their competitiveness. To overcome this limit, this work wants to develop a hybrid methodology to estimate as accurately as possible individual durations of activities belonging to a complex process. That kind of intervention lead to minimize possible costs for wrong estimations and maximize enterprises competitiveness. For this purpose, the authors combine some statistical tools used in Project management as Program Evaluation and Review Technique (PERT), Critical Path Method (CPM) and the parametric estimation with physical models used in manufacturing field, validating the obtained results in a real manufacturing case study. Through this research, authors put in evidence the possibility to adopt these techniques to well-known procedures employed to make products never realized before, for which no previous accurate data are available so far. This study highlights how it would be possible to reduce the effect of precautionary behaviors, supporting companies to accept a higher number of projects to be developed in a time range
A metaworld: Implications, opportunities and risks of the metaverse
No full textCyberspace has continued to change throughout the 1990s and 2000s, when the Internet became widely used. The concept of a massive, integrated, sustainable, and interconnected cyber world is the heart of the metaverse. The aim of the metaverse is to create a digital world that is analogous to the existing world. Thus, the most recent metaverse development is investigated in light of cutting-edge technologies and metaverse ecosystems. To this end, a pilot survey to provide a first overview of upcoming challenges and opportunities of the metaverse is presented. The results provide researchers with a direction for future study as well as potential applications in the metaverse
Super smart society: Proposal of an innovative digicircular internet platform towards a more sustainable, resilient, and human-centric future
No full textThe challenge of the circular economy affects not only the production systems, but increasingly concerns industrial sectors, lifestyles, and the habits of every citizen. Soon, companies and citizens will collaborate more and more for projects aimed at favoring the improvement of the recovery of materials. Starting from the premise, the present research aims to propose a holistic approach for a collaboration model to purse a digital circular economy. In this sense, it is necessary to critically rethink the culture of production going beyond the culture of waste to its reuse for the creation of new “supply chains”. Considering the above, the research aims to focus on the coffee supply chain considering that coffee is the second-largest beverage consumed around the world and the second largest traded commodity after petroleum. The basic idea is a reconfiguration of the supply chain making it more sustainable and more digitized than it is today. Thus, the aim of the research is to ‘design’ an integrated physical internet platform –PRISMA Platform (Physical internet RegeneratIve Sustainable MAterials) - to make the spent coffee grounds (SCGs) recovery activity with almost no waste
A day ahead energy load forecasting: Machine learning based model application on an Italian large enterprise
No full textElectric energy costs reduction is a critical aspect for industrial enterprise management. Short-term load forecast is a very important activity both for enterprises and for electric grid manager. Applying a short-term load forecasting method, enterprises can cut energy costs. Furthermore, such an application contributes to the reduction of grid manager interventions to minimize imbalance problems. In this context, industrial sites able to self-produce more than their energy need, have to adopt suitable load forecasting systems both to control energy consumption and to limit dispatching burden due to the feed of power into the grid. Correlation between industrial site energy consumption and industrial productions has encouraged the authors to develop a methodology that provide short-term electric load forecasting, based on machine learning, applicable in a generalized manner using available production plan data. To develop such a complex model, a tool composed of several parts has been implemented. Forecasting model structure is composed of 2 parts, one for prediction and one for imbalance calculation. Neural networks have been used in prediction phases because of their possibility to manage large dataset and to find nonlinear correlation between available variables. Application of developed methodology on real industrial gathered data has provided important results. Forecasting method, although calculated imbalances have reached high values, has led to get around 28% saving on balancing costs compared to enterprise previously applied forecasting method
Towards a Sustainable Digital Manufacturing: A State of Art
No full textIn an era where consumers increasingly demand transparency and sustainability in food production, this study introduces a mobile application tailored for the coffee supply chain. The goal of the study is to enhance the entire coffee production process by integrating technologies such as blockchain, RFID, and barcodes to improve transparency, traceability, and operational efficiency. The application tracks and records data from farm inspection to export, covering coffee variety, environmental conditions, and supplier actions. It manages logistics with real-time updates on quantities, destinations, and delivery times, which supports better decision-making and fosters consumer trust through verifiable information. By improving coordination, reducing fraud, and optimizing quality control, the app aims to cut costs by up to 20%, reduce inventory carrying costs by 15-25%, and boost crop productivity by up to 15%. Furthermore, it supports precision agriculture, aligns with Just-In-Time principles, and promotes sustainability while ensuring compliance with ISO 9001 and ISO 14001 standards
Optimal sizing and location of a fast charging infrastructure network for urban areas
No full textIn this paper, we deal with the design of a sustainable network of charging stations for electric vehicles circulating in an urban area. The major obstacles to E-Mobility (EM) development are still to be found into heated debates both in the scientific and industrial field and into a lacking of a widespread, accessible and homogeneous recharge infrastructure for the electric vehicles. In this work, we face the problem known as location optimization of charging stations and offer a heuristic method to design a sustainable infrastructure for the electric vehicles charging into urban contexts. In particular, the research can help mayors and governors of cities to take decisions concerning the number, the type and the placement of charging stations, taking into account the estimated hourly demand of charging services. Obviously, the design of an appropriate network includes the definition of all the needed costs to build the infrastructure and then the analysis of economic sustainability of the network basing on the revenues coming from estimated demand. The profitability of single charging stations is one of the main criteria to choose for the installation of a station. In this study we assume homogeneous pricing policy like in a monopoly scenario among charging stations. Future research can investigate on the effect of different prices applied by stations in the network design
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