1,294 research outputs found

    Exploiting Process Algebras and BPM Techniques for Guaranteeing Success of Distributed Activities

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    The communications and collaborations among activities, pro- cesses, or systems, in general, are the base of complex sys- tems defined as distributed systems. Given the increasing complexity of their structure, interactions, and functionali- ties, many research areas are interested in providing mod- elling techniques and verification capabilities to guarantee their correctness and satisfaction of properties. In particular, the formal methods community provides robust verification techniques to prove system properties. However, most ap- proaches rely on manually designed formal models, making the analysis process challenging because it requires an expert in the field. On the other hand, the BPM community pro- vides a widely used graphical notation (i.e., BPMN) to design internal behaviour and interactions of complex distributed systems that can be enhanced with additional features (e.g., privacy technologies). Furthermore, BPM uses process min- ing techniques to automatically discover these models from events observation. However, verifying properties and ex- pected behaviour, especially in collaborations, still needs a solid methodology. This thesis aims at exploiting the features of the formal meth- ods and BPM communities to provide approaches that en- able formal verification over distributed systems. In this con- text, we propose two approaches. The modelling-based ap- proach starts from BPMN models and produces process al- gebra specifications to enable formal verification of system properties, including privacy-related ones. The process mining- based approach starts from logs observations to automati- xv cally generate process algebra specifications to enable veri- fication capabilities

    Systemic Circular Economy Solutions for Fiber Reinforced Composites

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    This open access book provides an overview of the work undertaken within the FiberEUse project, which developed solutions enhancing the profitability of composite recycling and reuse in value-added products, with a cross-sectorial approach. Glass and carbon fiber reinforced polymers, or composites, are increasingly used as structural materials in many manufacturing sectors like transport, constructions and energy due to their better lightweight and corrosion resistance compared to metals. However, composite recycling is still a challenge since no significant added value in the recycling and reprocessing of composites is demonstrated. FiberEUse developed innovative solutions and business models towards sustainable Circular Economy solutions for post-use composite-made products. Three strategies are presented, namely mechanical recycling of short fibers, thermal recycling of long fibers and modular car parts design for sustainable disassembly and remanufacturing. The validation of the FiberEUse approach within eight industrial demonstrators shows the potentials towards new Circular Economy value-chains for composite materials

    Measuring the impact of COVID-19 on hospital care pathways

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    Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted

    Explainable Predictive and Prescriptive Process Analytics of customizable business KPIs

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    Recent years have witnessed a growing adoption of machine learning techniques for business improvement across various fields. Among other emerging applications, organizations are exploiting opportunities to improve the performance of their business processes by using predictive models for runtime monitoring. Predictive analytics leverages machine learning and data analytics techniques to predict the future outcome of a process based on historical data. Therefore, the goal of predictive analytics is to identify future trends, and discover potential issues and anomalies in the process before they occur, allowing organizations to take proactive measures to prevent them from happening, optimizing the overall performance of the process. Prescriptive analytics systems go beyond purely predictive ones, by not only generating predictions but also advising the user if and how to intervene in a running process in order to improve the outcome of a process, which can be defined in various ways depending on the business goals; this can involve measuring process-specific Key Performance Indicators (KPIs), such as costs, execution times, or customer satisfaction, and using this data to make informed decisions about how to optimize the process. This Ph.D. thesis research work has focused on predictive and prescriptive analytics, with particular emphasis on providing predictions and recommendations that are explainable and comprehensible to process actors. In fact, while the priority remains on giving accurate predictions and recommendations, the process actors need to be provided with an explanation of the reasons why a given process execution is predicted to behave in a certain way and they need to be convinced that the recommended actions are the most suitable ones to maximize the KPI of interest; otherwise, users would not trust and follow the provided predictions and recommendations, and the predictive technology would not be adopted.Recent years have witnessed a growing adoption of machine learning techniques for business improvement across various fields. Among other emerging applications, organizations are exploiting opportunities to improve the performance of their business processes by using predictive models for runtime monitoring. Predictive analytics leverages machine learning and data analytics techniques to predict the future outcome of a process based on historical data. Therefore, the goal of predictive analytics is to identify future trends, and discover potential issues and anomalies in the process before they occur, allowing organizations to take proactive measures to prevent them from happening, optimizing the overall performance of the process. Prescriptive analytics systems go beyond purely predictive ones, by not only generating predictions but also advising the user if and how to intervene in a running process in order to improve the outcome of a process, which can be defined in various ways depending on the business goals; this can involve measuring process-specific Key Performance Indicators (KPIs), such as costs, execution times, or customer satisfaction, and using this data to make informed decisions about how to optimize the process. This Ph.D. thesis research work has focused on predictive and prescriptive analytics, with particular emphasis on providing predictions and recommendations that are explainable and comprehensible to process actors. In fact, while the priority remains on giving accurate predictions and recommendations, the process actors need to be provided with an explanation of the reasons why a given process execution is predicted to behave in a certain way and they need to be convinced that the recommended actions are the most suitable ones to maximize the KPI of interest; otherwise, users would not trust and follow the provided predictions and recommendations, and the predictive technology would not be adopted

    Responsible Composition and Optimization of Integration Processes under Correctness Preserving Guarantees

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    Enterprise Application Integration deals with the problem of connecting heterogeneous applications, and is the centerpiece of current on-premise, cloud and device integration scenarios. For integration scenarios, structurally correct composition of patterns into processes and improvements of integration processes are crucial. In order to achieve this, we formalize compositions of integration patterns based on their characteristics, and describe optimization strategies that help to reduce the model complexity, and improve the process execution efficiency using design time techniques. Using the formalism of timed DB-nets - a refinement of Petri nets - we model integration logic features such as control- and data flow, transactional data storage, compensation and exception handling, and time aspects that are present in reoccurring solutions as separate integration patterns. We then propose a realization of optimization strategies using graph rewriting, and prove that the optimizations we consider preserve both structural and functional correctness. We evaluate the improvements on a real-world catalog of pattern compositions, containing over 900 integration processes, and illustrate the correctness properties in case studies based on two of these processes.Comment: 37 page

    Circular Tutelage: a Sustainable Approach Toward Remediation and Enhancement of Endangered Areas

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    Nowadays, one of the most important topics in the public dialogue concerns the concept of sustainability and its application in everyday life, given the urgence to reduce or counteract the negative effects partly caused by human activities. Fighting poverty, eradicating hunger and malnutrition, increasing the quality of life, protecting and restoring biodiversity, ensuring access to energy sources are just some of the goals for sustainable development included in the United Nations Organization's 2030 Agenda. Every country is called to make its contribution to jointly face these great challenges, rising from the awareness that the planet's resources are limited, unequally distributed and their exploitation often involves the alteration of delicate environmental balances. In the present work, a very productive transitional area prone to suffer from pollution and dangerous algal blooms, has been studied in order to propose methodologies and solutions which, if adopted, can contribute not only to mitigate environmental damages but also to provide new tools that can contribute to the development of local populations in a circular economy perspective. In particular, research has been carried out aimed at the development of solutions for the environmental restoration of ecosystems threatened by human pressure, proposing highly circular and sustainable processes based on the use of biomass from wastes or by-products. The proposed production processes are aimed at exploiting and valorizing these wastes, avoiding the compromission of the hygiene and quality of the ecosystem. In addition to the environmental sustainability also the economic and social one are considered in the proposed solutions. The area is characterized by a semi-enclosed lagoon structure, depths of up to two meters, over 25 km2. This area alone is responsible for the production of 55% of all clams produced in Italy, with over fifty million euros in turnover; essentially a collective heritage for the cities and economies that depend precisely on mussel farming and supporting activities. In order to mitigate the effects related to the excessive presence of algal biomass in the area, a cost / benefit analysis was carried out to determine the possibility of exploit this biomass as a secondary raw material for the production of market goods such as biofuels, drugs, supplements, and much more. The possibilities for economic exploitations of the biomass would in fact make the collection of this component from the environment advantageous and would avoid negative phenomena in the aquatic environment. The feasibility of the proposed solutions was also accompanied by a foresight analysis in which possible social dynamics were considered which have led, in the past, to the failure of a project whose mission was to safeguard and improve the conditions of the lagoon. In order to carry out the feasibility study, in addition to the composition of the constituent elements of algae determination, their possible contamination by various classes of pollutants, whose presence could constitute an obstacle to their exploitation, was also studied. The thesis also considers another voluminous waste biomass present in the lagoon, namely byproduct seashells which constitute a process waste from the bivalves that are produced in the lagoon and which, unfortunately, are often illegally discharged into the canals or deployed in landfill and classified as special waste. Landfilling not only has an economic impact on small fishing businesses but also reduces the sustainability of aquaculture activities, which according to many, will be a key sector for development in the coming years. Hence, the shell of the clam essentially consists of calcium carbonate and can be used as a constituent of soil conditioners and fertilizers for agricultural purposes or as an adsorbent material in biofilters and in environmental bioremediation methodologies.Oggigiorno, una delle tematiche di maggior rilievo nel dialogo comune riguarda il concetto di sostenibilità e della sua applicazione nel quotidiano per rispondere all’esigenza di ridurre o contrastare vari effetti negativi in parte causati dalle attività umane. Contrastare la povertà, eradicare la fame e la malnutrizione, tutelare e ripristinare la biodiversità, sicurezza energetica, sono solo alcuni degli obiettivi per lo sviluppo sostenibile presenti nell’Agenda 2030 dell’Organizzazione delle Nazioni Unite. Ogni Paese è chiamato a fornire il suo contributo per affrontare in comune queste grandi sfide, nate dalla consapevolezza che le risorse del pianeta sono limitate, distribuite iniquamente e il loro sfruttamento spesso comporta l’alterazione di delicati equilibri ambientali. Nel presente lavoro di tesi si è studiato un ecosistema di transizione molto produttivo, ma fragile, per proporre metodologie e soluzioni che se adottate possano contribuire non solo a mitigare i danni ambientali, ma anche a fornire nuovi strumenti che possano contribuire allo sviluppo delle popolazioni locali in un’ottica di economia circolare. In particolare, si sono effettuate ricerche orientate allo sviluppo di soluzioni per il ripristino ambientale di ecosistemi minacciati dalla pressione antropica, proponendo processi altamente circolari e sostenibili basati sull’utilizzo di biomasse provenienti da scarti o sottoprodotti. I processi produttivi proposti sono orientati a sfruttare e valorizzare questi scarti evitando che compromettano l’igiene e la qualità degli ecosistemi in cui essi sono presenti o in cui vengono riversati. In questo ambito si sono approfonditi argomenti propri della sfera sociale ed economica, per garantire oltre alla sostenibilità ambientale anche quella economica e sociale delle soluzioni proposte. La zona è caratterizzata da una struttura lagunare semichiusa, fondali profondi massimo due metri e complessivamente è uno specchio d’acqua di 25 km2. Quest’area sola è responsabile per la produzione del 55% di tutte le vongole prodotte in Italia, con oltre cinquanta milioni di euro di volume d’affari; sostanzialmente un patrimonio collettivo per le città e le economie che dipendono appunto dalle attività di mitilicoltura e dalle attività consortili e coadiuvanti. Allo scopo di mitigare gli effetti legati alla presenza eccessiva di biomassa algale nella zona, si è svolta una analisi costi / benefici per determinare la possibilità di sfruttare al meglio tale biomassa come materia prima seconda per la produzione di oggetti e beni di consumo, come biocombustibili, farmaci, integratori e tanto altro. La possibilità di sfruttare economicamente la biomassa renderebbe infatti vantaggiosa la raccolta di questa componente dall’ambiente. La realizzabilità delle soluzioni proposte è stata inoltre corredata da un’analisi in previsione in cui si sono considerate possibili dinamiche sociali che hanno portato, in passato, al fallimento di un progetto che aveva la missione di salvaguardare e migliorare le condizioni della laguna. inoltre, è stata studiata la composizione degli elementi costitutivi di alghe e anche la loro possibile contaminazione da parte di varie classi di inquinanti la cui presenza potrebbe costituire un ostacolo per il loro sfruttamento. Nella tesi viene inoltre considerata anche un’altra voluminosa biomassa di scarto presente nella laguna, “il capulerio” che costituisce uno scarto di lavorazione dei bivalvi prodotti. Lo smaltimento in discarica non solo incide economicamente sulle piccole imprese di pescatori, ma riduce la sostenibilità delle attività di acquacultura. In un’ottica di sostenibilità e circolarità, il guscio delle conchiglie è costituito da carbonato di calcio e può trovare impiego come costituente di ammendanti e fertilizzanti per scopi agricoli o come materiale adsorbente in biofiltri e in altre metodologie di bioremediazione ambientale

    Productivity and flexibility improvement of assembly lines for high-mix low-volume production. A white goods industry case

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    Las tendencias globales de la personalización e individualización en masa impulsan la producción industrial en serie corta y variada; y por tanto una gran variedad de productos en pequeñas cantidades. Por ello, la customización en masa precisa de sistemas de ensamblaje que sean a la vez altamente productivos y flexibles, a diferencia de la tradicional oposición entre ambas características. La llamada cuarta revolución industrial trae diversas tecnologías habilitadoras que podrían ser útiles para abordar este problema. Sin embargo, las metodologías para implementar el ensamblaje 4.0 todavía no han sido resueltas. De hecho, para aprovechar todas las ventajas potenciales de la Industria 4.0, es necesario contar con un nivel previo de excelencia operacional y un análisis holístico de los sistemas productivos. Esta tesis tiene como objetivo entender y definir cómo mejorar la productividad y la flexibilidad de las operaciones de montaje en serie corta y variada.Esta meta se ha dividido en tres objetivos. El primer objetivo consiste en comprender las relaciones entre la Industria 4.0 y las operaciones de ensamblaje, así como sus implicaciones para los operarios. El segundo objetivo consiste en desarrollar una metodología y las herramientas necesarias para evaluar el rendimiento de diferentes configuraciones de cadenas de ensamblaje. El último objetivo consiste en el diseño de sistemas de ensamblaje que permitan incrementar su productividad al menos un 25 %, produciendo en serie corta y variada, mediante la combinación de puestos de montaje manual y estaciones automatizadas.Para abordar la fase de comprensión y definición del problema, se llevó a cabo una revisión bibliográfica sistemática y se desarrolló un marco conceptual para el Ensamblaje 4.0. Se desarrollaron, verificaron y validaron dos herramientas de evaluación del rendimiento: un modelo matemático analítico y varios modelos de simulación por eventos discretos. Para la verificación, y como punto de partida para los análisis, se ha utilizado un caso de estudio industrial de un fabricante global de electrodomésticos. Se han empleado múltiples escenarios de simulación y técnicas de diseño de experimentos para investigar tres cuestiones clave.En primer lugar, se identificaron los factores más críticos para el rendimiento de líneas de montaje manuales multi-modelo. En segundo lugar, se analizó el rendimiento de líneas de montaje semiautomáticas paralelas con operarios móviles en comparación con líneas semiautomáticas o manuales con operarios fijos, empleando diversos escenarios de demanda en serie corta y variada. Por último, se investigó el uso de trenes milkrun para la logística interna de líneas de ensamblaje multi-modelo bajo la influencia de perturbaciones.Los resultados de las simulaciones muestran que las líneas paralelas con operarios móviles pueden superar a las de operarios fijos en cualquier escenario de demanda, alcanzando como mínimo el objetivo de mejorar la productividad en un 25% o más. También permiten reducir cómodamente el número de operarios trabajando en la línea sin afectar negativamente al equilibrado de la misma, posibilitando la producción eficiente de bajo volumen. Los resultados de las simulaciones de logística interna indican que los milkrun pueden proteger las líneas de ensamblaje de las perturbaciones originadas en procesos aguas arriba.Futuras líneas de investigación en base a los resultados obtenidos en esta tesis podrían incluir la expansión e integración de los modelos de simulación actuales para analizar las cadenas de montaje paralelas con operarios móviles incorporando logística, averías y mantenimiento, problemas de control de calidad y políticas de gestión de los retrabajos. Otra línea podría ser el uso de diferentes herramienta para el análisis del desempeño como, por ejemplo, técnicas de programación de la producción que permitan evaluar el desempeño operacional de diferentes configuraciones de cadenas de montaje con operarios móviles, tanto en términos de automatización como de organización en planta. Podrían incorporarse tecnologías de la Industria 4.0 a los modelos de simulación para evaluar su impacto operacional global ¿como cobots para ensamblaje o para la manipulación de materiales, realidad aumentada para el apoyo cognitivo a los operarios, o AGVs para la conducciónde los trenes milkrun. Por último, el trabajo presentado en esta tesis acerca las líneas de ensamblaje semiautomáticas con operarios móviles a su implementación industrial.<br /

    An agent-based simulator for quantifying the cost of uncertainty in production systems

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    Product-mix problems, where a range of products that generate different incomes compete for a limited set of production resources, are key to the success of many organisations. In their deterministic forms, these are simple optimisation problems; however, the consideration of stochasticity may turn them into analytically and/or computationally intractable problems. Thus, simulation becomes a powerful approach for providing efficient solutions to real-world productmix problems. In this paper, we develop a simulator for exploring the cost of uncertainty in these production systems using Petri nets and agent-based techniques. Specifically, we implement a stochastic version of Goldratt’s PQ problem that incorporates uncertainty in the volume and mix of customer demand. Through statistics, we derive regression models that link the net profit to the level of variability in the volume and mix. While the net profit decreases as uncertainty grows, we find that the system is able to effectively accommodate a certain level of variability when using a Drum-Buffer-Rope mechanism. In this regard, we reveal that the system is more robust to mix than to volume uncertainty. Later, we analyse the cost-benefit trade-off of uncertainty reduction, which has important implications for professionals. This analysis may help them optimise the profitability of investments. In this regard, we observe that mitigating volume uncertainty should be given higher consideration when the costs of reducing variability are low, while the efforts are best concentrated on alleviating mix uncertainty under high costs.This article was financially supported by the State Research Agency of the Spanish Ministry of Science and Innovation (MCIN/AEI/ 10.13039/50110 0 011033), via the project SPUR, with grant ref. PID2020–117021GB-I00. In addition, the authors greatly appreciate the valuable and constructive feedback received from the Editorial team of this journal and two anonymous reviewers in the different stages of the review process
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