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Digital manufacturing has been challenged by the manufacturing industry to rationalize different ways to connect and exchange information and knowledge across different phases of manufacturing systems. One of the Industry 4.0 pillars is the horizontal and vertical integration with intelligent and self-adaptive systems. For this to be possible, the manufacturing industry applies an extensive range of software tools, such as GRAI, CIMOSA, MO2GO, ARIS, SCADA, MES, ERP, CAD, and CAM. Individually, each one performs its function to support the manufacturing process. However, when these multiple tools operate together using technical standards, some misinterpretation and mistake gaps are identified due to a lack of machine-to-machine (M2M) communication and users’ interpretation. This is recognized as a semantic interoperability problem. Semantic technologies, such as ontologies, have been proven to be a promising way to overcome semantic interoperability obstacles. Based on this context, this study is proposing a conceptual framework based on semantic technologies to create a solution to the horizontal and vertical integration and semantic interoperability obstacle. MANUMATE is the framework proposed, and it consists of three artifacts, 1) reference ontologies, 2) requirements, and 3) application ontology, and two processes, 1) ontology specialization and 2) information application. The MANUMATE framework is applied to two experimental case studies to validate the conceptual solution in two different applications, in the context of a long-life package for the beverages industry. These case studies help elucidate how the application of the framework could improve the information and knowledge exchange by providing a standard way to represent information among different stakeholders in the productive process. A discussion about the results is presented, revealing the benefits and limitations of the solution.

Digital manufacturing has been challenged by the manufacturing industry to rationalise different ways to connect and to exchange information and knowledge across the manufacturing systems. One of the main pillars of the Industry 4.0 concept is the horizontal and vertical integration with intelligent and self-adaptive systems. For this to be possible, the manufacturing industry applies an extensive range of software tools to aid its activities, such as SCADA, MES, ERP, 3D CAD, CAM, and so on. Individually, each one performs its function to support the manufacturing process. However, these software tools do not have an effective integration and interoperation, since they present different database structures, variables that have the same information with different names and data structures, and closed systems. Thus, it has been identified semantic interoperability issues (misinterpretations and mistakes) in view of the information heterogeneity from multiple perspectives and their relationships across the manufacturing process. In this context, this paper aims to present a discussion of interoperability issues across the manufacturing systems, as well as to introduce possible solutions according to the related works. a holistic approach is critical factors for long-term competitiveness solutions. The literature points out that the solution to this problem may be in the application of semantic technologies. These have the potential to provide solutions that are more comprehensive than the industrial approaches that have been applied through the formalization of information so that knowledge can be shared among multiple domains.

A parametrização de controladores é um problema constantemente estudado, tanto para aplicações na área industrial, quanto acadêmica. A utilização da otimização multiobjetivo, apoiada por metaheurísticas no auxílio a esta tarefa tem sido cada vez mais comum, visto que possibilita a obtenção de múltiplas soluções de maneira mais simples e rápida, quando confrontada por métodos clássicos. Neste artigo, o Algoritmo Genético de Classificação Não Dominada II (NSGA-II) é utilizado para a obtenção dos ganhos de um controlador Proporcional-Integral-Derivativo (PID) cujo propósito é estabilizar um sistema não linear aeropêndulo, identificado por um modelo Hammerstein-Wiener. O conjunto de soluções obtido pelo algoritmo NSGA-II mostrou-se inviável para análise e simulação individual devido à sua elevada quantidade, de modo que o método de auxílio à tomada de decisão multicritério Processo Analítico Hierárquico (AHP), foi adotado, a solução apontada como preferencial pelo método AHP apresentou rápido tempo de estabilização e mínimo de sobressinal.