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Emerging Methods and Tools for Production Systems’ Design and Management in the Mass Customization Era, 2nd Edition

A special issue of Applied Sciences (ISSN 2076-3417).

Deadline for manuscript submissions: 20 October 2025 | Viewed by 2964

Special Issue Editors

Special Issue Information

Dear Colleagues,

In the last decade, traditional industrial and market features were replaced by emerging factors, such as variable market demand, the need for flexibility, shorter product life cycles, and mass customization and personalization. This drastically modified the production environment, pressing industrial companies to embrace and implement new types of production paradigms. In this context, advanced production systems rose, e.g., changeable and reconfigurable manufacturing systems, and agile and virtual manufacturing systems, as effective solutions to cope with these issues.

The aim of this Special Issue is to attract contributions proposing state-of-the-art research, methods, tools, and industrial experiences about advanced manufacturing systems’ design and management in the mass customization era. Potential topics include, but are not limited to:

  • Manufacturing systems’ design, planning, operation, and control;
  • Changeability, flexibility, and reconfigurability;
  • Sustainability, de-manufacturing and re-manufacturing;
  • Rapid product/process prototyping, development and ramp-up;
  • Virtual, digital, and smart factories;
  • Innovating for smart production;
  • Product/process co-evolution;
  • Development of services, and product service systems;
  • Human–machine interaction and smart automation;
  • Learning factories and smart labs;
  • Smart products, services, and product-service systems;
  • Digital business models for mass customization;
  • Sustainability, circular economy, and mass customization;
  • Success factors and industrial best practices;
  • Managing variety, product/service platforms, and families;
  • Data-driven approaches for mass customization.

Dr. Marco Bortolini
Dr. Francesco Gabriele Galizia
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. Applied Sciences is an international peer-reviewed open access semimonthly 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

  • advanced production
  • manufacturing systems
  • mass customization
  • personalization
  • changeable manufacturing
  • reconfigurability
  • virtual manufacturing

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Related Special Issue

Published Papers (3 papers)

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25 pages, 4712 KiB  
Article
Assessment of Parameters Affecting the Efficiency of Production Processes Including Barriers and Perspectives of Automation in a Real Manufacturing Environment
by Wojciech Lewicki, Adam Koniuszy, Mariusz Niekurzak and Konrad Stefanowicz
Appl. Sci. 2025, 15(6), 3092; https://doi.org/10.3390/app15063092 - 12 Mar 2025
Cited by 1 | Viewed by 1117
Abstract
Modern product manufacturing is not only becoming more advanced but also requires increasingly precise and technologically advanced solutions, especially in the production process. One example is the automotive industry, where customization is becoming a key requirement. This work aimed to analyze the factors [...] Read more.
Modern product manufacturing is not only becoming more advanced but also requires increasingly precise and technologically advanced solutions, especially in the production process. One example is the automotive industry, where customization is becoming a key requirement. This work aimed to analyze the factors determining the efficiency of production processes, using the example of a selected company from the automotive industry—the production of spare parts—and to assess the impact of the applied optimization tools and techniques on improving operational results. This work combines theoretical and practical aspects, presenting a detailed analysis of data and actions taken in a real production environment. As part of the research, a thorough research program was presented, including the analysis of production data before and after conducting optimization workshops. Before the workshop, key problems were identified, such as the time-consuming rearranging of machines. The analysis using the parametric Student’s t test for two subsidiaries showed the rightness of the optimization activities. During the workshop, several changes were implemented, including the use of a new Destacker, modification of conversation procedures and training operators. The data collected after the workshop indicated a significant reduction in the times of reliance, which confirmed the effectiveness of the activities used. The analysis used tools such as the Pareto diagram and the ABC method, which allowed the identification of priority areas to improve. This work proves that the use of appropriate management tools and employee involvement in the optimization process can significantly improve the efficiency of production processes. Key success factors included the elimination of losses resulting from inefficient procedures, improvement of work organization and implementation of technological solutions. The results of this analysis form the basis for further research on improving production processes in the automotive industry. Full article
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32 pages, 820 KiB  
Article
Leveraging Blockchain and Consignment Contracts to Optimize Food Supply Chains Under Uncertainty
by Isha Sharma, Gurpreet Kaur, Bikash Koli Dey and Arunava Majumder
Appl. Sci. 2024, 14(24), 11735; https://doi.org/10.3390/app142411735 - 16 Dec 2024
Cited by 2 | Viewed by 1291
Abstract
The occurrence of the fourth industrial revolution (Industry 4.0) has led many industries to the path of adopting new technologies. Such technologies include blockchain, artificial intelligence (AI), and the Internet of Things (IoT). Blockchain creates the opportunity to access data and information in [...] Read more.
The occurrence of the fourth industrial revolution (Industry 4.0) has led many industries to the path of adopting new technologies. Such technologies include blockchain, artificial intelligence (AI), and the Internet of Things (IoT). Blockchain creates the opportunity to access data and information in a decentralized manner, resulting in increased customer satisfaction. This study develops a smart newsvendor model of the food industry with consignment contracts and blockchain technology. Under a consignment policy, the central division (manufacturer) can utilize the retailer’s warehouse for storage. The producer may also have the opportunity to share the holding cost with retailers without losing the ownership of products. The main contribution of this study is to analyze the profitability of the retailing and supply chain when the blockchain technology is implemented by the food industry. Moreover, a thorough investigation of profit and loss is conducted under a consignment contract when uncertain demand is encountered. This study mainly concerns perishable food items, and increasing volatility in market demand. Two cases of probabilistic uncertainty are considered, including uniform and normal distribution. The key investigations of this study are presented in terms of (a) the effect of adopting blockchain on market demand for the food industry, (b) analysis of company profitability for perishable food items and demand uncertainty, and (c) the effect of the consignment contract under blockchain technology in the food industry. Finally, this research develops an optimization tool to numerically analyze the effect of several factors of the blockchain technology on demand. Moreover, the optimal values of the design variables and the resulting maximum profitability provide valuable insights that support industry in formulating effective policies and making informed strategic decisions. Full article
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Other

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29 pages, 1055 KiB  
Systematic Review
Unlocking the Potential of Mass Customization Through Industry 4.0: Mapping Research Streams and Future Directions
by Ludovica Diletta Naldi, Francesco Gabriele Galizia, Marco Bortolini, Matteo Gabellini and Emilio Ferrari
Appl. Sci. 2025, 15(13), 7160; https://doi.org/10.3390/app15137160 - 25 Jun 2025
Viewed by 123
Abstract
Mass customization (MC) has become a pivotal manufacturing strategy for addressing the growing demand for personalized products without compromising cost efficiency and scalability. The emergence of Industry 4.0 (I4.0) has further expanded the potential of MC by enabling intelligent, flexible, and interconnected production [...] Read more.
Mass customization (MC) has become a pivotal manufacturing strategy for addressing the growing demand for personalized products without compromising cost efficiency and scalability. The emergence of Industry 4.0 (I4.0) has further expanded the potential of MC by enabling intelligent, flexible, and interconnected production systems. This paper presents a systematic literature review covering the period from 2011 to 2024, aimed at examining how I4.0 technologies influenced the conceptual evolution, technological enablers, and supply chain implications of MC. A total of 3441 publications were retrieved from Scopus and analyzed using a combination of bibliometric mapping and qualitative synthesis. The review identifies three primary research streams: (1) MC conceptual frameworks and performance metrics, (2) enabling technologies and methods across the product lifecycle, and (3) supply chain strategies tailored to MC environments. Key enablers such as product modularity, customer co-design platforms, additive manufacturing, and reconfigurable production systems are discussed, along with barriers related to complexity, integration challenges, and sustainability trade-offs. The study highlights a gradual convergence toward mass personalization, supported by real-time data, artificial intelligence, and predictive analytics. The findings offer a structured understanding of MC in the I4.0 context and point toward future research opportunities involving digital twin integration, cross-disciplinary implementation models, and sustainability-driven customization frameworks. Full article
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