No description available.

<p dir="ltr">Condition-based maintenance is a proactive maintenance strategy that prevents failures or diminished functionality in process systems through proper monitoring and management of process conditions. Despite being considered a mature maintenance management strategy in various industries, condition-based maintenance remains underutilized in pharmaceutical manufacturing. This situation needs to change, especially as the pharmaceutical industry continues to shift from batch to continuous manufacturing, where the implementation of CBM as a maintenance strategy assumes a greater importance.</p><p dir="ltr">This dissertation focused on addressing the challenges of implementing CBM in a continuous drug product manufacturing system. These challenges stem from the unique aspects of pharmaceutical drug product manufacturing, which includes the peculiar behavior of particulate materials and the evolutionary nature of pharmaceutical process development. The proposed solutions to address these challenges revolve around an innovative framework for the practical development of condition monitoring systems. Overall, this framework enables the incorporation of limited process knowledge in creating condition monitoring systems, which has the desired effect of empowering data-driven machine learning models.</p><p dir="ltr">A key feature of this framework is a formalized method to represent the process condition, which is usually vaguely defined in literature. This representation allows the proper mapping of preexisting condition monitoring systems, and the segmentation of the entire process condition model into smaller modules that have more manageable condition monitoring problems. Because this representation methodology is based on probabilistic graphical modelling, the smaller modules can then be holistically integrated via their probabilistic relationships, allowing the robust operation of the resulting condition monitoring system and the process it monitors.</p><p dir="ltr">Breaking down the process condition model into smaller segments is crucial for introducing novel fault detection capabilities, which enhances model prediction transparency and ensures prediction acceptance by a human operator. In this work, a methodology based on prediction probabilities was introduced for developing condition monitoring systems with novel fault detection capabilities. This approach relies on high-performing machine learning models capable of consistently classifying all the initially known conditions in the fault library with a high degree of certainty. Simplifying the condition monitoring problem through modularization facilitates this, as machine learning models tend to perform better on simpler systems. Performance indices were proposed to evaluate the novel fault detection capabilities of machine learning models, and a formal approach to managing novel faults was introduced.</p><p dir="ltr">Another benefit of modularization is the identification of condition monitoring blind spots. Applying it to the RC led to sensor development projects such as the virtual sensor for measuring granule flowability. This sensor concept was demonstrated successfully by using a data-driven model to predict granule flowability based on size and shape distribution measurements. With proper model selection and feature extraction guided by domain expertise, the resulting sensor achieved the best prediction performance reported in literature for granule flowability.</p><p dir="ltr">As a demonstration exercise in examining newly discovered faults, this work investigated a roll compaction phenomenon that is usually concealed from observation due to equipment design. This phenomenon results in the ribbon splitting along its thickness as it comes out of the rolls. In this work, important aspects of ribbon splitting were elucidated, particularly its predictability based on RC parameters and the composition of the powder blend used to form the ribbon. These findings have positive ramifications for the condition monitoring of the RC, as correspondence with industrial practitioners suggests that a split ribbon is desirable in some cases, despite being generally regarded as undesirable in the limited literature available on the subject.</p><p dir="ltr">Finally, this framework was primarily developed for the pharmaceutical dry granulation line, which consists of particle-based systems with a moderate level of complexity. However, it was also demonstrated to be feasible for the Tennessee Eastman Process (TEP), a more complex liquid-gas process system with a greater number of process faults, variables, and unit operations. Applying the framework resulted in machine learning models that yielded one of the best fault detection performances reported in literature for the TEP, while also introducing additional capabilities not yet normally reported in literature, such as fault diagnosis and novel fault detection.</p>

[pt] Contexto Injeção de Dependência (DI) é um mecanismo comumente aplicado para desacoplar classes de suas dependências com o objetivo de prover uma melhor modularização do software. No contexto de Java, a existência de uma especificação de DI e frameworks populares, como o Spring, facilitam o emprego de DI em projetos de software. Entretanto, más práticas de implementação de DI podem trazer más consequências, como maior acoplamento, dificultando alcançar o principal objetivo de DI. Apesar de a literatura sugerir a existência de anti-padrões de DI, não há uma documentação detalhada de tais más práticas. Em adição, não há evidência da ocorrência e da percepção de utilidade dos mesmos do ponto de vista de desenvovedores. Objetivos Nosso objetivo é revisar os anti-padrões de DI reportados com o objetivo de analisar sua completude e propor um novo catálogo de anti-padrões de DI para Java. Método Nós propomos um catálogo contendo 12 anti-padrões de DI para Java. Nós selecionamos 4 projetos open-source e 2 projetos closed-source que adotam um framework de DI e desenvolvemos uma ferramenta que analisa estaticamente a ocorrência dos anti-padrões de DI candidatos no código fonte das aplicações. Em adição, nós conduzimos uma pesquisa por meio de entrevistas face a face com três desenvolvedores experientes que regularmente aplicam DI em seus projetos. Nós estendemos a pesquisa com o objetivo de obter a percepção de um conjunto de 15 desenvolvedores experientes e novatos por meio de um questionário online Resultados Ao menos 9 anti-padrões de DI apareceram frequentemente nos projetos de software analisados. Em adição, a avaliação recebida dos desenvolvedores confirmaram a relevância do catálogo. Por fim, os respondentes expressaram o desejo de refatorar as instâncias de antipadrões de DI propostas. Conclusões O catálogo contém anti-padrões de DI que ocorrem na prática e são úteis. Compartilhar com praticantes da indústria os permitirá evitar a introdução de anti-padrões em seus projetos de software. / [en] Background Dependency Injection (DI) is a commonly applied mechanism to decouple classes from their dependencies in order to provide better modularization of software. In the context of Java, the availability of a DI specification and popular frameworks, such as Spring, facilitate DI usage in software projects. However, bad DI implementation practices can have negative consequences, such as increasing coupling, hindering the achievement of DI s main goal. Even though the literature suggests the existence of DI anti-patterns, there is no detailed documentation of such bad practices. Moreover, there is no evidence on their occurrence and perceived usefulness from the developer s point of view. Aims Our goal is to review the reported DI anti-patterns in order to analyze their completeness and to propose and evaluate a novel catalog of Java DI anti-patterns. Method We propose a catalog containing 12 Java DI anti-patterns. We selected 4 opensource and 2 closed-source software projects that adopt a DI framework and developed a tool to statically analyze the occurrence of the candidate DI anti-patterns within their source code. Also, we conducted a survey through face to face interviews with three experienced developers that regularly apply DI. We extended the survey in order to gather the perception of a set of 15 expert and novice developers through an online questionnaire. Results At least 9 different DI anti-patterns appeared frequently in the analyzed projects. In addition, the feedback received from the developers confirmed the relevance of the catalog. Besides, the respondents expressed their willingness to refactor instances of anti-patterns from source code. Conclusions The catalog contains Java DI anti-patterns that occur in practice and are useful. Sharing it with practitioners may help them to avoid such anti-patterns.

The term Industry 4.0, sometimes referred to as a buzzword, is today on everyone’s tongue and the benefits undeniably seem to be promising and have potential to revolutionize the manufacturing industry. But what does it really mean? From a high-level business perspective, the concept of Industry 4.0 most often demonstrates operational efficiency and promising business models but studies show that many companies either lack understanding for the concept and how it should be implemented or are dissatisfied with progress of already implemented solutions. Further, there is a perception that it is difficult to implement the concept without interference with the current production system.The purpose of this study is to interpret and outline the main characteristics and key components of the concept Industry 4.0 and further break down and conclude the potential benefits and enablers for a manufacturing company within the heavy automotive industry. In order to succeed, a case study has been performed at a manual final assembly production unit within the heavy automotive industry. Accordingly, the study intends to give a deeper understanding of the concept and specifically how manual assembly within an already existing manual production system will be affected. Thus outline the crucial enablers in order to successfully implement the concept of Industry 4.0 and be prepared to adapt to the future challenges of the industry. The case study, performed through observations and interviews, attacks the issue from two perspectives; current state and desired state. A theoretical framework is then used as a basis for analysis of the result in order to be able to further present the findings and conclusion of the study. Lastly, two proof of concept are performed to exemplify and support the findings. The study shows that succeeding with implementation of Industry 4.0 is not only about the related technology itself. Equally important parts to be considered and understood are the integration into the existing production system and design and purpose of the manual assembly process. Lastly the study shows that creating understanding and commitment in the organization by strategy, leadership, culture and competence is of greatest importance to succeed. / Begreppet Industri 4.0, ibland benämnt som modeord, är idag på allas tungor och fördelarna verkar onekligen lovande och tros ha potential att revolutionera tillverkningsindustrin. Men vad betyder det egentligen? Ur ett affärsperspektiv påvisar begreppet Industri 4.0 oftast ökad operativ effektivitet och lovande affärsmodeller men flera studier visar att många företag antingen saknar förståelse för konceptet och hur det ska implementeras eller är missnöjda med framstegen med redan implementerade lösningar. Vidare finns det en uppfattning att det är svårt att implementera konceptet utan störningar i det nuvarande produktionssystemet. Syftet med denna studie är att tolka och beskriva huvudegenskaperna och nyckelkomponenterna i konceptet Industri 4.0 och ytterligare bryta ner och konkludera de potentiella fördelarna och möjliggörarna för ett tillverkande företag inom den tunga bilindustrin. För att lyckas har en fallstudie utförts vid en manuell slutmonteringsenhet inom den tunga lastbilsindustrin. Studien avser på så sätt att ge en djupare förståelse för konceptet och specifikt hur manuell montering inom ett redan existerande manuellt produktionssystem kommer att påverkas. Alltså att kartlägga viktiga möjliggörare för att framgångsrikt kunna implementera konceptet Industri 4.0 och på så sätt vara beredd att ta sig an industrins framtida utmaningar. Fallstudien, utförd genom observationer och intervjuer, angriper frågan från två perspektiv; nuläge och önskat läge. Ett teoretiskt ramverk används sedan som underlag för analys av resultatet för att vidare kunna presentera rön och slutsats från studien. Slutligen utförs två experiment för att exemplifiera och stödja resultatet. Studien visar att en framgångsrik implementering av Industri 4.0 troligtvis inte bara handlar om den relaterade tekniken i sig. Lika viktiga delar som ska beaktas och förstås är integrationen i det befintliga produktionssystemet och utformningen och syftet med den manuella monteringsprocessen. Slutligen visar studien att det är av största vikt att skapa förståelse och engagemang i organisationen genom strategi, ledarskap, kultur och kompetens.

<p>The present work is focused on the synthesis of small-scale (modular processes) to produce olefins from light alkane resources in shale gas.</p> <p>Olefins, which are widely used to produce important chemicals and everyday consumer products, can be produced from light alkanes - ethane, propane, butanes etc. Shale gas is comprised of light alkanes in significant proportion; and is available in abundance. Meanwhile, shale gas wells are small sized in nature and are distributed over many different areas or regions. In this regard, using shale gas as raw material for olefin production would require expensive transportation infrastructure to move the gas from the wells or local gas gathering stations to large central processing facilities. This is because existing technologies for natural gas conversions are particularly suited for large-scale processing. One possible way to take advantage of the abundance of shale resource for olefins production is to place small-sized or modular processing plants at the well sites or local gas gathering stations.</p> <p>In this work, new process concepts are synthesized and studied towards developing simple technologies for on-site and modular processing of light alkane resources in shale gas for olefin production. Replacing steam with methane as diluent in conventional thermal cracking processes is proposed to eliminate front-end separation of methane from the shale gas processing scheme. Results from modeling studies showed that this is a promising approach. To eliminate the huge firebox volume associated with thermal cracking furnaces and allow for a compact cracking reactor system, the use of electricity to supply heat to the cracking reactor is considered. Synthesis efforts led to the development of two electrically powered reactor configurations that have improved energy efficiency and reduced carbon footprints over and compare to conventional thermal cracking furnace configurations.</p> <p>The ideas and results in the present work are radical in nature and could lead to a transformation in the utilization of light alkanes, natural gas and shale resources for the commercial production of fuels and chemicals.</p>

Le but essentiel de la thèse est de développer une ontologie juridique bien fondée pour l'utiliser dans le raisonnement à base des règles. Pour cela, une approche middle-out, collaborative et modulaire est proposée ou des ontologies fondationnelles et core ont été réutilisées pour simplifier le développement de l'ontologie. L’ontologie résultante est adoptée dans une approche homogène a base des ontologies pour formaliser la liste des règles juridiques du code pénal en utilisant le langage logique SWRL. / This thesis analyses the problem of building well-founded domain ontologies for reasoning and decision support purposes. Specifically, it discusses the building of legal ontologies for rule-based reasoning. In fact, building well-founded legal domain ontologies is considered as a difficult and complex process due to the complexity of the legal domain and the lack of methodologies. For this purpose, a novel middle-out approach called MIROCL is proposed. MIROCL tends to enhance the building process of well-founded domain ontologies by incorporating several support processes such as reuse, modularization, integration and learning. MIROCL is a novel modular middle-out approach for building well-founded domain ontologies. By applying the modularization process, a multi-layered modular architecture of the ontology is outlined. Thus, the intended ontology will be composed of four modules located at different abstraction levels. These modules are, from the most abstract to the most specific, UOM(Upper Ontology Module), COM(Core Ontology Module), DOM(Domain Ontology Module) and DSOM(Domain-Specific Ontology Module). The middle-out strategy is composed of two complementary strategies: top-down and bottom-up. The top-down tends to apply ODCM (Ontology-Driven Conceptual Modeling) and ontology reuse starting from the most abstract categories for building UOM and COM. Meanwhile, the bottom-up starts from textual resources, by applying ontology learning process, in order to extract the most specific categories for building DOM and DSOM. After building the different modules, an integration process is performed for composing the whole ontology. The MIROCL approach is applied in the criminal domain for modeling legal norms. A well-founded legal domain ontology called CriMOnto (Criminal Modular Ontology) is obtained. Therefore, CriMOnto has been used for modeling the procedural aspect of the legal norms by the integration with a logic rule language (SWRL). Finally, an hybrid approach is applied for building a rule-based system called CORBS. This system is grounded on CriMOnto and the set of formalized rules.