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Project Management of Complex Systems (Manufacturing and Services)
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Project Management of Complex Systems (Manufacturing and Services)

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Complex Systems and Cybernetics".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 728

Special Issue Editors

Prof. Dr. Alencar Bravo

E-Mail Website
Guest Editor
Department of Management, Université du Québec à Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada
Interests: eco-design tools; techniques and methods; lifecycle management; total cost of ownership; lean; sustainability; uncertainty and risk management; support systems for projects
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Darli Rodrigues Vieira

E-Mail Website
Guest Editor
Department of Management, Université du Québec à Trois-Rivières, Trois-Rivières, QC G8Z 4M3, Canada
Interests: project management; defense projects; product lifecycle management; new product development; supply chain management; strategy and management of operations
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue on “Project Management of Complex Systems (Manufacturing and Services)” explores the multifaceted challenges of managing and integrating systems in environments where development, production, and service operations intersect. By nature, these contexts require a deep understanding of how systems evolve, adapt, and interface with diverse elements—ranging from defining and adjusting requirements and meeting tight contractual deadlines to achieving performance targets and quality standards. Success hinges not only on robust project management practices but also on innovative strategies that enable organizations to respond proactively to complexity and change.

A critical factor in achieving outstanding results lies in cultivating strong synergies among people, processes, and technologies, all framed within a systems perspective that spans everything from early design studies to full-scale implementation. Technologies such as artificial intelligence, blockchain, 5G, and collaborative robotics now offer unprecedented opportunities to streamline complex operations, automate essential tasks, and support decision making. When effectively harnessed, these innovations enhance transparency, traceability, and customization, highlighting the importance of intelligent project portfolios and resilient supply chains.

This Special Issue invites contributions that offer emerging insights, methods, and best practices for project management within intricate systems. We particularly welcome submissions that demonstrate how a systems-oriented perspective can strengthen collaboration, drive value creation throughout the supply chain, and foster organizational and technological innovation in both industry and services.

For this Special Issue, we invite articles that address, among other topics, the following:

  • Complex Systems Management
  • Systems Engineering in Project Management
  • Decision-Making in Complex Project Management
  • Systems Engineering and Artificial Intelligence
  • Complex Supply Chain Management Systems
  • Needs and Requirements in Project Management for Complex Systems
  • Product Lifecycle Management in Complex Systems
  • Complex Services
  • Additive Manufacturing in Complex Systems
  • Cybersecurity in Manufacturing and Services
  • AI and Generative AI in the Factory of the Future
  • Clean Technology Manufacturing

Prof. Dr. Alencar Bravo
Prof. Dr. Darli Rodrigues Vieira
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • complex systems
  • systems engineering
  • project management
  • manufacturing
  • services
  • product lifecycle management
  • decision-making

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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32 pages, 2370 KB  
Article
Enabling Technologies for Circular Economy Transition: Cases in the Manufacturing Industry
by Beatriz Makssoudian Ferraz, Alexander Moltschanov, Leonie Meldt and Marly Monteiro de Carvalho
Systems 2025, 13(10), 865; https://doi.org/10.3390/systems13100865 - 1 Oct 2025
Viewed by 260
Abstract
This study aims to investigate the role of Industry 4.0 (I4.0) technologies in facilitating the transition towards a circular economy (CE) in the manufacturing sector, exploring four key circular economy strategies—reuse, repair, refurbishment, and remanufacturing. This study combines a comprehensive literature review with [...] Read more.
This study aims to investigate the role of Industry 4.0 (I4.0) technologies in facilitating the transition towards a circular economy (CE) in the manufacturing sector, exploring four key circular economy strategies—reuse, repair, refurbishment, and remanufacturing. This study combines a comprehensive literature review with case studies of ten manufacturing organisations from various sectors, including electronics, information and communication technologies, and the household and furniture industries. The research focuses on three main areas: the adoption of circular strategies, the challenges associated with implementing Industry 4.0 technologies, and the role of these technologies in enabling the transition to a circular economy. Data were collected through ten interviews with managers responsible for sustainability, corporate social responsibility, or circular economy projects and initiatives, as well as through documentary analysis of archival materials. The study found that organisations typically adopt multiple circular strategies, with repair being the most prevalent strategy across all sectors and adopted in every case analysed. However, the adoption of I4.0 technologies faces challenges such as scalability issues, digital expertise shortages, and outdated infrastructure. Advanced adopters of I4.0 technologies benefit from robust delivery systems supported by collaborative networks, which enhance knowledge transfer and development among stakeholders. Full article
(This article belongs to the Special Issue Project Management of Complex Systems (Manufacturing and Services))
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Other

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25 pages, 4152 KB  
Systematic Review
Mapping the AI Landscape in Project Management Context: A Systematic Literature Review
by Masoom Khalil, Alencar Bravo, Darli Vieira and Marly Monteiro de Carvalho
Systems 2025, 13(10), 913; https://doi.org/10.3390/systems13100913 - 17 Oct 2025
Abstract
The purpose of this research is to systematically map and analyze the use of AI technologies in project management, identifying themes, research gaps, and practical implications. This study conducts a systematic literature review (SLR) that combines bibliometric analysis with qualitative content evaluation to [...] Read more.
The purpose of this research is to systematically map and analyze the use of AI technologies in project management, identifying themes, research gaps, and practical implications. This study conducts a systematic literature review (SLR) that combines bibliometric analysis with qualitative content evaluation to explore the present landscape of AI in project management. The search covered literature published until November 2024, ensuring inclusion of the most recent developments. Studies were included if they examined AI methods applied to project management contexts and were published in peer-reviewed English journals as articles, review articles, or early access publications; studies unrelated to project management or lacking methodological clarity were excluded. It follows a structured coding protocol informed by inductive and deductive reasoning, using NVivo (version 12) and Biblioshiny (version 4.3.0) software. From the entire set of 1064 records retrieved from Scopus and Web of Science, 27 publications met the final inclusion criteria for qualitative synthesis. Bibliometric clusters were derived from the entire set of 885 screened records, while thematic coding was applied to the 27 included studies. This review highlights the use of Artificial Neural Networks (ANN), Case-Based Reasoning (CBR), Digital Twins (DTs), and Large Language Models (LLMs) as central to recent progress. Bibliometric mapping identified several major thematic clusters. For this study, we chose those that show a clear link between artificial intelligence (AI) and project management (PM), such as expert systems, intelligent systems, and optimization algorithms. These clusters highlight the increasing influence of AI in improving project planning, decision-making, and resource management. Further studies investigate generative AI and the convergence of AI with blockchain and Internet of Things (IoT) systems, suggesting changes in project delivery approaches. Although adoption is increasing, key implementation issues persist. These include limited empirical evidence, inadequate attention to later project stages, and concerns about data quality, transparency, and workforce adaptation. This review improves understanding of AI’s role in project contexts and outlines areas for further research. For practitioners, the findings emphasize AI’s ability in cost prediction, scheduling, and risk assessment, while also emphasizing the importance of strong data governance and workforce training. This review is limited to English-language, peer-reviewed research indexed in Scopus and Web of Science, potentially excluding relevant grey literature or non-English contributions. This review was not registered and received no external funding. Full article
(This article belongs to the Special Issue Project Management of Complex Systems (Manufacturing and Services))
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