Detalhes
Nome
António BaptistaCargo
Investigador AuxiliarDesde
03 abril 2023
Nacionalidade
PortugalCentro
Centro de Engenharia de Sistemas EmpresariaisContactos
+351222094398
antonio.baptista@inesctec.pt
2024
Autores
Pecas, P; Lopes, J; Jorge, D; Sahul, AK; Baptista, AJ; Leiter, M;
Publicação
ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS-PRODUCTION MANAGEMENT SYSTEMS FOR VOLATILE, UNCERTAIN, COMPLEX, AND AMBIGUOUS ENVIRONMENTS, APMS 2024, PT III
Abstract
Lean and green (L&G) manufacturing in Industry 4.0 (I4.0) has brought many advantages in manufacturing industries by minimizing waste and maximizing efficiency with integration of renewable energy sources and sustainable materials. Multi-layer Stream Mapping (MSM) is a new framework for the performance assessment of complex manufacturing processes. MSM is used for multi-domain analysis of manufacturing processes to assess resources, and processes, that are used to identify Non-ValueAdded (NVA) procedures or steps that consume unnecessary time and resources, and/or release emissions and waste that can no longer be reused or recycled to be eliminated or replaced to create a Value Added (VA) process flow that avoids waste in a clean, green and environmental friendly manner. This paper presents the implementation of the L&G strategy through MSM in metal working production systems. In metalworking production systems, the variables of operational performance and resources consumption considered are process time, number of operators, consumables, raw material, and energy. These can be suitably used for reduction in water emissions, gas emissions, solid waste and scrap generated in metalworking production systems.
2023
Autores
Peças, P; John, L; Ribeiro, I; Baptista, AJ; Pinto, SM; Dias, R; Henriques, J; Estrela, M; Pilastri, A; Cunha, F;
Publicação
Sustainability (Switzerland)
Abstract
In recent years, the Twin-Transition reference model has gained notoriety as one of the key options for decarbonizing the economy while adopting more sustainable models leveraged by the Industry 4.0 paradigm. In this regard, one of the most relevant challenges is the integration of data-driven approaches with sustainability assessment approaches, since overcoming this challenge will foster more agile sustainable development. Without disregarding the effort of academics and practitioners in the development of sustainability assessment approaches, the authors consider the need for holistic frameworks that also encourage continuous improvement in sustainable development. The main objective of this research is to propose a holistic framework that supports companies to assess sustainability performance effectively and more easily, supported by digital capabilities and data-driven concepts, while integrating improvement procedures and methodologies. To achieve this objective, the research is based on the analysis of published approaches, with special emphasis on the data-driven concepts supporting sustainability assessment and Lean Thinking methods. From these results, we identified and extracted the metrics, scopes, boundaries, and kinds of output for decision-making. A new holistic framework is described, and we have included a guide with the steps necessary for its adoption in a given company, thus helping to enhance sustainability while using data availability and data-analytics tools. © 2023 by the authors.
2023
Autores
Pecas, P; John, L; Ribeiro, I; Baptista, AJ; Pinto, SM; Dias, R; Henriques, J; Estrela, M; Pilastri, A; Cunha, F;
Publicação
SUSTAINABILITY
Abstract
In recent years, the Twin-Transition reference model has gained notoriety as one of the key options for decarbonizing the economy while adopting more sustainable models leveraged by the Industry 4.0 paradigm. In this regard, one of the most relevant challenges is the integration of data-driven approaches with sustainability assessment approaches, since overcoming this challenge will foster more agile sustainable development. Without disregarding the effort of academics and practitioners in the development of sustainability assessment approaches, the authors consider the need for holistic frameworks that also encourage continuous improvement in sustainable development. The main objective of this research is to propose a holistic framework that supports companies to assess sustainability performance effectively and more easily, supported by digital capabilities and data-driven concepts, while integrating improvement procedures and methodologies. To achieve this objective, the research is based on the analysis of published approaches, with special emphasis on the data-driven concepts supporting sustainability assessment and Lean Thinking methods. From these results, we identified and extracted the metrics, scopes, boundaries, and kinds of output for decision-making. A new holistic framework is described, and we have included a guide with the steps necessary for its adoption in a given company, thus helping to enhance sustainability while using data availability and data-analytics tools.
2023
Autores
de Matos, B; Salles, R; Mendes, J; Gouveia, JR; Baptista, AJ; Moura, P;
Publicação
MATHEMATICS
Abstract
Humanity faces serious problems related to water supply, which will be aggravated by population growth. The water used in human activities must be treated to make it available again without posing risks to human health and the environment. In this context, Wastewater Treatment Plants (WWTPs) have gained importance. The treatment process in WWTPs is complex, consisting of several stages, which consume considerable amounts of resources, mainly electrical energy. Minimizing such energy consumption while satisfying quality and environmental requirements is essential, but it is a challenging task due to the complexity of the processes carried out in WWTPs. One form of evaluating the performance of WWTPs is through the well-known Key Performance Indicators (KPIs). The KPIs are numerical indicators of process performance, being a simple and common way to assess the efficiency and eco-efficiency of a process. By applying KPIs to WWTPs, techniques for monitoring, predicting, controlling, and optimizing the efficiency and eco-efficiency of WWTPs can be created or improved. However, the use of computational methodologies that use KPIs (KPIs-based methodologies) is still limited. This paper provides a literature review of the current state-of-the-art of KPI-based methodologies to monitor, control and optimize energy efficiency and eco-efficiency in WWTPs. In this paper, studies presented on 21 papers are identified, assessed and synthesized, 12 being related to monitoring and predicting problems, and 9 related to control and optimization problems. Future research directions relating to unresolved problems are also identified and discussed.
2022
Autores
Carneiro, T; Oliveira, J; Baptista, AJ; de Castro, PMST;
Publicação
Designs
Abstract
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