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Industry 4.0 and Sustainability Implications: A Scenario-Based Analysis of the Impacts and Challenges
Open accessAbstract
The new evolution of the production and industrial process called Industry 4.0, and its related technologies such as the Internet of Things, big data analytics, and cyber–physical systems, among others, still have an unknown potential impact on sustainability and the environment. In this paper, we conduct a literature-based analysis to discuss the sustainability impact and challenges of Industry 4.0 from four different scenarios: deployment, operation and technologies, integration and compliance with the sustainable development goals, and long-run scenarios. From these scenarios, our analysis resulted in positive or negative impacts related to the basic production inputs and outputs flows: raw material, energy and information consumption and product and waste disposal. As the main results, we identified both positive and negative expected impacts, with some predominance of positives that can be considered positive secondary effects derived from Industry 4.0 activities. However, only through integrating Industry 4.0 with the sustainable development goals in an eco-innovation platform, can it really ensure environmental performance. It is expected that this work can contribute to helping stakeholders, practitioners and governments to advance solutions to deal with the outcomes emerging through the massive adoption of those technologies, as well as supporting the expected positive impacts through policies and financial initiatives.
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“The ultimate distribution of the gas can influence not only the design and procurement of the most appropriate gasification and gas upgrading systems, but it will also influence the demands and challenges of gas analysis in the measurement facility [65].”
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Metadata
- Authors
- Bonilla, S. H., Silva, H. R. O., Terra da Silva, M., Franco Gonçalves, R., & Sacomano, J. B.
- Affiliations
- Universidade Paulista (BR)
- Post Graduate Program in Production Engineering, Paulista University, UNIP, São Paulo 04026-002, Brazil
- Corresponding author
- Bonilla, Silvia H.
- Venue
- Sustainability
- Publisher
- MDPI AG
- Published
- 2018-10-17
- Volume
- 10
- Issue
- 10
- Pages
- 3740
- ISSN
- 2071-1050 (ISSN-L)
- OpenAlex
- W2897985668
- Cited by
- 645
- References
- 71
- Citations by year
- 2026: 47 · 2025: 57 · 2024: 86 · 2023: 110 · 2022: 95 · 2021: 106 · 2020: 100 · 2019: 42 · 2018: 2
- FWCI
- 51.84
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Sustainability (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (1675677)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Strategy and Management › Sustainable Supply Chain Management
- Keywords
- Industry 4.0, sustainability impacts, Sustainable Development Goals, Internet of Things, big data analytics, cyber-physical systems, environmental performance, energy consumption, waste disposal, raw material consumption, information consumption, scenario analysis, technology adoption
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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