Lean Manufacturing Towards Industry 5.0

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 706

Special Issue Editors


E-Mail Website
Guest Editor
Department of Engineering Technology, University of Kentucky, Lexington, KY 40508, USA
Interests: lean manufacturing; quality management; Industry 4.0; Industry 5.0

E-Mail Website
Guest Editor
Department of Engineering Technology, University of Kentucky, Lexington, KY 40506, USA
Interests: structured problem solving; lean and digitalization (Industry 4.0); modeling and analysis of manufacturing systems; lean application in healthcare; lean production in high variety/low volume manufacturing; challenges to lean implementation; lean production development

E-Mail Website
Guest Editor
Department of Mechatronics Engineering, Bells University of Technology, Ota 112104, Ogun State, Nigeria
Interests: lean production; artificial intelligence; Industry 4.0

Special Issue Information

Dear Colleagues,

Lean Production has long been a foundation of efficient production, focusing on eliminating waste, optimizing processes, and delivering value to the customer. As we transition towards Industry 5.0, this lean approach is evolving to integrate advanced technologies with a human-centric focus. Industry 5.0 builds on the automation and connectivity of Industry 4.0, emphasizing collaboration between humans and machines to create more personalized and sustainable manufacturing systems. In this new era, lean principles continue to play a vital role, but they are now complemented by artificial intelligence, robotics, and data analytics, which enable even greater efficiency and customization. The shift towards Industry 5.0 encourages manufacturers to go beyond just reducing waste and improving efficiency; it also demands attention to worker well-being, creativity, and sustainability. Lean tools such as Kaizen and Just-in-Time (JIT) are being enhanced with real-time data and AI-driven insights, allowing for more adaptive and responsive production systems. This integration ensures that lean manufacturing remains relevant, driving innovation while maintaining its core principle of delivering maximum value with minimal waste. Industry 5.0 represents a harmonious blend of technology and human ingenuity, with lean manufacturing as the foundation for this next-generation industrial revolution.

Dr. Catherine Maware
Dr. David Parsley
Prof. Dr. Ilesanmi Afolabi Daniyan
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

  • lean manufacturing
  • Industry 4.0
  • Industry 5.0
  • human-centric manufacturing
  • human-cyber-physical systems
  • resilient manufacturing
  • Toyota Production System
  • value-driven manufacturing

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

25 pages, 1699 KiB  
Article
Development and Application of a Stochastic Model for Optimizing Production Cycles Aimed at Sustainable Production
by Sanja Stanisavljev, Dragan Ćoćkalo, Mila Kavalić, Verica Gluvakov, Mihalj Bakator, Luka Djordjević and Stefan Ugrinov
Systems 2025, 13(8), 628; https://doi.org/10.3390/systems13080628 - 24 Jul 2025
Abstract
This paper analyzed the importance of applying modern concepts and tools for monitoring production processes in order to improve effectiveness, efficiency, and sustainable manufacturing. The aim of the study was to develop and apply a stochastic model based on a modified real-time observation [...] Read more.
This paper analyzed the importance of applying modern concepts and tools for monitoring production processes in order to improve effectiveness, efficiency, and sustainable manufacturing. The aim of the study was to develop and apply a stochastic model based on a modified real-time observation method to optimize production cycles in the metalworking industry. The research was conducted over several years in real industrial conditions using instantaneous observations, and the collected data were statistically analyzed using control charts and flow coefficient functions. The results showed a significant reduction in production cycle times and improved efficiency, particularly when the batch size was optimized to 10 units. The analyzed working time elements and flow coefficients enabled a comprehensive analysis and influenced trends in subsequent years, thereby improving production management. A comparative analysis of the results reveals a downward trend in average PC time per unit over the years—56.2, 37.7, 31.5, and 44.8 min from phases I to IV—until the introduction of a new operation. The corresponding flow coefficient functions are y1 = 297.54/x + 2; y2 = 239/x − 7.36; y3 = 192/x + 0.65; and y4 = 438.2/x − 11.3. These findings suggest that the optimal batch size for the enterprise under consideration is 10 units. The findings confirmed that the integration of Lean principles and Industry 4.0 methods contributes to the reduction of non-productive time and better process control. The study provided a simple and effective model for cycle time optimization that can be implemented even in small and medium-sized enterprises. Full article
(This article belongs to the Special Issue Lean Manufacturing Towards Industry 5.0)
Show Figures

Figure 1

Back to TopTop