IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i2p492-d306600.html
   My bibliography  Save this article

Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions

Author

Listed:
  • Raffaele Cioffi

    (Department of Engineering, Parthenope University, Isola C4, Centro Direzionale, 80143 Napoli NA, Italy)

  • Marta Travaglioni

    (Department of Engineering, Parthenope University, Isola C4, Centro Direzionale, 80143 Napoli NA, Italy)

  • Giuseppina Piscitelli

    (Department of Engineering, Parthenope University, Isola C4, Centro Direzionale, 80143 Napoli NA, Italy)

  • Antonella Petrillo

    (Department of Engineering, Parthenope University, Isola C4, Centro Direzionale, 80143 Napoli NA, Italy)

  • Fabio De Felice

    (Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Via G. Di Biasio, 43, 03043 Cassino FR, Italy)

Abstract

Adaptation and innovation are extremely important to the manufacturing industry. This development should lead to sustainable manufacturing using new technologies. To promote sustainability, smart production requires global perspectives of smart production application technology. In this regard, thanks to intensive research efforts in the field of artificial intelligence (AI), a number of AI-based techniques, such as machine learning, have already been established in the industry to achieve sustainable manufacturing. Thus, the aim of the present research was to analyze, systematically, the scientific literature relating to the application of artificial intelligence and machine learning (ML) in industry. In fact, with the introduction of the Industry 4.0, artificial intelligence and machine learning are considered the driving force of smart factory revolution. The purpose of this review was to classify the literature, including publication year, authors, scientific sector, country, institution, and keywords. The analysis was done using the Web of Science and SCOPUS database. Furthermore, UCINET and NVivo 12 software were used to complete them. A literature review on ML and AI empirical studies published in the last century was carried out to highlight the evolution of the topic before and after Industry 4.0 introduction, from 1999 to now. Eighty-two articles were reviewed and classified. A first interesting result is the greater number of works published by the USA and the increasing interest after the birth of Industry 4.0.

Suggested Citation

  • Raffaele Cioffi & Marta Travaglioni & Giuseppina Piscitelli & Antonella Petrillo & Fabio De Felice, 2020. "Artificial Intelligence and Machine Learning Applications in Smart Production: Progress, Trends, and Directions," Sustainability, MDPI, vol. 12(2), pages 1-26, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:492-:d:306600
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/2/492/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/2/492/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jeffrey D. Sachs & Guido Schmidt-Traub & Mariana Mazzucato & Dirk Messner & Nebojsa Nakicenovic & Johan Rockström, 2019. "Six Transformations to achieve the Sustainable Development Goals," Nature Sustainability, Nature, vol. 2(9), pages 805-814, September.
    2. María Pérez-Ortiz & Silvia Jiménez-Fernández & Pedro A. Gutiérrez & Enrique Alexandre & César Hervás-Martínez & Sancho Salcedo-Sanz, 2016. "A Review of Classification Problems and Algorithms in Renewable Energy Applications," Energies, MDPI, vol. 9(8), pages 1-27, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Magdalena Osial & Agnieszka Pregowska, 2022. "The Application of Artificial Intelligence in Magnetic Hyperthermia Based Research," Future Internet, MDPI, vol. 14(12), pages 1-17, November.
    2. Maksymilian Mądziel, 2023. "Liquified Petroleum Gas-Fuelled Vehicle CO 2 Emission Modelling Based on Portable Emission Measurement System, On-Board Diagnostics Data, and Gradient-Boosting Machine Learning," Energies, MDPI, vol. 16(6), pages 1-15, March.
    3. Muhammad Rashid & Muhammad Attique Khan & Majed Alhaisoni & Shui-Hua Wang & Syed Rameez Naqvi & Amjad Rehman & Tanzila Saba, 2020. "A Sustainable Deep Learning Framework for Object Recognition Using Multi-Layers Deep Features Fusion and Selection," Sustainability, MDPI, vol. 12(12), pages 1-21, June.
    4. Ahmed, Shamima & Alshater, Muneer M. & Ammari, Anis El & Hammami, Helmi, 2022. "Artificial intelligence and machine learning in finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 61(C).
    5. Jingyu Li & Yangbo Chen & Yanzheng Zhu & Jun Liu, 2023. "Study of Flood Simulation in Small and Medium-Sized Basins Based on the Liuxihe Model," Sustainability, MDPI, vol. 15(14), pages 1-16, July.
    6. Feng, Yunting & Lai, Kee-hung & Zhu, Qinghua, 2022. "Green supply chain innovation: Emergence, adoption, and challenges," International Journal of Production Economics, Elsevier, vol. 248(C).
    7. Isaac Akomea-Frimpong & Amma Kyewaa Agyekum & Alexander Baah Amoakwa & Prosper Babon-Ayeng & Fatemeh Pariafsai, 2024. "Toward the attainment of climate-smart PPP infrastructure projects: a critical review and recommendations," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(8), pages 19195-19229, August.
    8. Salem Ahmed Alabdali & Salvatore Flavio Pileggi & Dilek Cetindamar, 2023. "Influential Factors, Enablers, and Barriers to Adopting Smart Technology in Rural Regions: A Literature Review," Sustainability, MDPI, vol. 15(10), pages 1-38, May.
    9. Iztok Palčič & Jasna Prester, 2020. "Impact of Advanced Manufacturing Technologies on Green Innovation," Sustainability, MDPI, vol. 12(8), pages 1-14, April.
    10. Amjad Almusaed & Ibrahim Yitmen & Asaad Almssad, 2023. "Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review," Energies, MDPI, vol. 16(6), pages 1-23, March.
    11. Alim Al Ayub Ahmed & Sugandha Agarwal & IMade Gede Ariestova Kurniawan & Samuel P. D. Anantadjaya & Chitra Krishnan, 2022. "Business boosting through sentiment analysis using Artificial Intelligence approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 699-709, March.
    12. Matteo Acquarone & Claudio Maino & Daniela Misul & Ezio Spessa & Antonio Mastropietro & Luca Sorrentino & Enrico Busto, 2023. "Influence of the Reward Function on the Selection of Reinforcement Learning Agents for Hybrid Electric Vehicles Real-Time Control," Energies, MDPI, vol. 16(6), pages 1-22, March.
    13. Rabab Triki & Mohamed Hédi Maâloul & Younès Bahou & Mohamed Kadria, 2023. "The Impact of Digitization to Ensure Competitiveness of the Ha’il Region to Achieve Sustainable Development Goals," Sustainability, MDPI, vol. 15(2), pages 1-13, January.
    14. Sunghun Kim & Youngjin Park & Seungbeom Yoo & Ocktaeck Lim & Bernike Febriana Samosir, 2023. "Development of Machine Learning Algorithms for Application in Major Performance Enhancement in the Selective Catalytic Reduction (SCR) System," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    15. Henry Ekwaro-Osire & Dennis Bode & Klaus-Dieter Thoben & Jan-Hendrik Ohlendorf, 2022. "Identification of Machine Learning Relevant Energy and Resource Manufacturing Efficiency Levers," Sustainability, MDPI, vol. 14(23), pages 1-19, November.
    16. Bowen Li & Fangxin Jiang & Hongjie Xia & Jiawei Pan, 2022. "Under the Background of AI Application, Research on the Impact of Science and Technology Innovation and Industrial Structure Upgrading on the Sustainable and High-Quality Development of Regional Econo," Sustainability, MDPI, vol. 14(18), pages 1-19, September.
    17. Kinkel, Steffen & Baumgartner, Marco & Cherubini, Enrica, 2022. "Prerequisites for the adoption of AI technologies in manufacturing – Evidence from a worldwide sample of manufacturing companies," Technovation, Elsevier, vol. 110(C).
    18. Li Wei & Mahmud Iwan Solihin & Sarah ‘Atifah Saruchi & Winda Astuti & Lim Wei Hong & Ang Chun Kit, 2024. "Surface Defects Detection of Cylindrical High-Precision Industrial Parts Based on Deep Learning Algorithms: A Review," SN Operations Research Forum, Springer, vol. 5(3), pages 1-71, September.
    19. Beatrice Garske & Antonia Bau & Felix Ekardt, 2021. "Digitalization and AI in European Agriculture: A Strategy for Achieving Climate and Biodiversity Targets?," Sustainability, MDPI, vol. 13(9), pages 1-21, April.
    20. Krzysztof Rusek & Agnieszka Kleszcz & Albert Cabellos-Aparicio, 2023. "Bayesian inference of spatial and temporal relations in AI patents for EU countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3313-3335, June.
    21. Manuel Woschank & Erwin Rauch & Helmut Zsifkovits, 2020. "A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics," Sustainability, MDPI, vol. 12(9), pages 1-23, May.
    22. Hao Wang & Chen Peng & Bolin Liao & Xinwei Cao & Shuai Li, 2023. "Wind Power Forecasting Based on WaveNet and Multitask Learning," Sustainability, MDPI, vol. 15(14), pages 1-22, July.
    23. Constantin Aurelian Ionescu & Melinda Timea Fülöp & Dan Ioan Topor & Sorinel Căpușneanu & Teodora Odett Breaz & Sorina Geanina Stănescu & Mihaela Denisa Coman, 2021. "The New Era of Business Digitization through the Implementation of 5G Technology in Romania," Sustainability, MDPI, vol. 13(23), pages 1-23, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chi Zhang & Zhongchang Sun & Qiang Xing & Jialong Sun & Tianyu Xia & Hao Yu, 2021. "Localizing Indicators of SDG11 for an Integrated Assessment of Urban Sustainability—A Case Study of Hainan Province," Sustainability, MDPI, vol. 13(19), pages 1-14, October.
    2. Sonika Redhu & Pragati Jain, 2024. "Unveiling the nexus between water scarcity and socioeconomic development in the water-scarce countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(8), pages 19557-19577, August.
    3. Prince Waqas Khan & Yung-Cheol Byun & Sang-Joon Lee & Dong-Ho Kang & Jin-Young Kang & Hae-Su Park, 2020. "Machine Learning-Based Approach to Predict Energy Consumption of Renewable and Nonrenewable Power Sources," Energies, MDPI, vol. 13(18), pages 1-16, September.
    4. Keeheon Lee, 2021. "A Systematic Review on Social Sustainability of Artificial Intelligence in Product Design," Sustainability, MDPI, vol. 13(5), pages 1-29, March.
    5. Ida Kubiszewski & Kenneth Mulder & Diane Jarvis & Robert Costanza, 2022. "Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 139-148, February.
    6. Oliver Reader, M. & Eppinga, Maarten B. & de Boer, Hugo J. & Petchey, Owen L. & Santos, Maria J., 2024. "Consistent ecosystem service bundles emerge across global mountain, island and delta systems," Ecosystem Services, Elsevier, vol. 66(C).
    7. Björnemalm, Rickard & Sandström, Christian & Åkesson, Nelly, 2023. "A Public Choice Perspective on Mission-Oriented Innovation Policies and the Behavior of Government Agencies," Ratio Working Papers 366, The Ratio Institute.
    8. Puertas, Rosa & Guaita-Martinez, José M. & Marti, Luisa, 2023. "Analysis of the impact of university policies on society's environmental perception," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    9. Amin Jan & Mário Nuno Mata & Pia A. Albinsson & José Moleiro Martins & Rusni Bt Hassan & Pedro Neves Mata, 2021. "Alignment of Islamic Banking Sustainability Indicators with Sustainable Development Goals: Policy Recommendations for Addressing the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(5), pages 1-38, March.
    10. Alvaro Furlani Bastos & Surya Santoso, 2021. "Optimization Techniques for Mining Power Quality Data and Processing Unbalanced Datasets in Machine Learning Applications," Energies, MDPI, vol. 14(2), pages 1-21, January.
    11. Koundouri, Phoebe & Theodossiou, Nicolaos & Stavridis, Charalampos & Devves, Stathis & Plataniotis, Angelos, 2022. "A methodology for linking the Energy-related Policies of the European Green Deal to the 17 SDGs using Machine Learning," MPRA Paper 122118, University Library of Munich, Germany.
    12. Lejla Terzić, 2024. "An investigation of the interlinkages between green growth dimensions, the energy trilemma, and sustainable development goals: Evidence from G7 and E7 economies," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 1, pages 24-53.
    13. Tobias Wulfert & Robert Woroch & Gero Strobel & Thorsten Schoormann & Leonardo Banh, 2024. "E-commerce ecosystems as catalysts for sustainability: A multi-case analysis," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-21, December.
    14. Iban, Muzaffer Can & Aksu, Oktay, 2020. "A model for big spatial rural data infrastructure in Turkey: Sensor-driven and integrative approach," Land Use Policy, Elsevier, vol. 91(C).
    15. Paola Perez-Aleman & Tommaso Ferretti, 2023. "Creating innovation capabilities for improving global health: Inventing technology for neglected tropical diseases in Brazil," Journal of International Business Policy, Palgrave Macmillan, vol. 6(1), pages 84-114, March.
    16. Mehmet Çağlar & Cem Gürler, 2022. "Sustainable Development Goals: A cluster analysis of worldwide countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 8593-8624, June.
    17. Zhang, Dongyang & Kong, Qunxi, 2022. "Renewable energy policy, green investment, and sustainability of energy firms," Renewable Energy, Elsevier, vol. 192(C), pages 118-133.
    18. Jan Anton van Zanten & Rob van Tulder, 2020. "Beyond COVID-19: Applying “SDG logics” for resilient transformations," Journal of International Business Policy, Palgrave Macmillan, vol. 3(4), pages 451-464, December.
    19. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
    20. Deepak Gautam & Nomesh Bolia, 2024. "Developing an incentive‐based model for efficient product recovery and reverse logistics," Business Strategy and the Environment, Wiley Blackwell, vol. 33(8), pages 7972-7989, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:492-:d:306600. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.