Smart Industry – Theories and Practices for Sustainability
A special issue of Sustainability (ISSN 2071-1050).
Deadline for manuscript submissions: closed (30 July 2023) | Viewed by 375
Special Issue Editors
Interests: design and analysis of experiments; operations and quality management
Special Issues, Collections and Topics in MDPI journals
Interests: industrial instrumentation; smart sensing; Industry 4.0; environmental monitoring
Special Issues, Collections and Topics in MDPI journals
Interests: automation; optimization; simulation; decision making; multiobjective optimization; post-Pareto analysis and response surface methodology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Most manufacturing and service industries are aware of the digital transition need for leveraging their business sustainability and competitiveness. However, many of them are still starting to plan this transition, while others are in an early stage in that digital transformation. This is not a fast and easy process due to technical and non-technical issues. Additionally, digital technologies and Industrial Internet of Things (IIoT) already have a relevant role in the actual business intelligence age.
Industry is experiencing unprecedented conditions and challenges related to technology and data availability. Digital, networked, and intelligent technologies provide huge amounts of raw data that allow to create new or modify existing business processes, culture, and customer experiences to meet changing business and market requirements. However, massive datasets require the usage of Big Data analytics tools to extract the right information from them. To select and implement those tools for gathering actionable and manageable insights from the data is a major challenge. Successful case studies of machine learning and artificial intelligence techniques that enhance decision support and significantly improve businesses efficiency and sustainability from an economic, environmental, social, and governance point of view must be reported, but unsuccessful examples will exist and must be presented as well, because they also provide useful insights and learnings.
In this context, researchers and practitioners are invited to submit original research articles, reviews, and case studies within the following topics and related fields.
Topics: digital transformation; Industry 4.0; intelligent technologies; artificial intelligence; machine learning; big data; simulation technologies; virtual reality; process configuration and control; digital twin; supply chain 5.0.
We look forward to receiving your contributions.
Prof. Dr. Nuno Ricardo Pais Costa
Dr. José Miguel Costa Dias Pereira
Dr. João Miguel Lourenço
Guest Editors
Manuscript Submission Information
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Keywords
- digital transition
- artificial intelligence
- automation
- intelligent technologies
- simulation
- big data
- operations efficiency
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