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Lean Manufacturing in Industry 4.0
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Lean Manufacturing in Industry 4.0

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

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 14980

Special Issue Editors

Dr. Rossella Pozzi

E-Mail Website
Guest Editor
School of Industrial Engineering, LIUC Università Cattaneo, 21053 Castellanza, Italy
Interests: lean manufacturing; industry 4.0; mathematical models for production systems
Dr. Violetta Giada Cannas

E-Mail Website
Guest Editor
School of Industrial Engineering, LIUC Università Cattaneo, 21053 Castellanza, Italy
Interests: lean manufacturing; industry 4.0; engineer-to-order supply chain management

Special Issue Information

Dear Colleagues,

Since the advent of the fourth industrial revolution, there has been rising interest in the relationship between Industry 4.0 and lean manufacturing. The two paradigms share the objectives of productivity and flexibility, and the literature claims that they mutually support each other. Their combination is called ‘lean automation’. The literature reports significant opportunities in the case of the joint implementation of the two paradigms, also in terms of environmental and social impact. The understanding of the integration of the new technologies of Industry 4.0 with lean manufacturing systems is still in its early days, and only a few studies are dedicated to this topic so far. On the other hand, the comprehension of lean automation’s practices, principles, and effects on companies' operations would support managers in its implementation and in achieving operational excellence, contributing to production systems’ improvement.

This Special Issue particularly looks forward to articles addressing, among other topics, the implementation of lean principles in smart factories, the synergy between lean practices and cyber-physical systems, the role of data science in waste reduction, and the challenges of workforce upskilling in the face of rapidly evolving technologies. Contributions to this Special Issue should highlight the latest advancements in lean manufacturing strategies, as well as the ongoing challenges of integrating these approaches within Industry 4.0. By examining successful implementations and addressing potential pitfalls, this Special Issue aims to provide valuable insights for practitioners and researchers seeking to optimize production processes in the era of smart manufacturing. We are interested in studies using any of the full range of qualitative and quantitative investigative methodologies.

Dr. Rossella Pozzi
Dr. Violetta Giada Cannas
Guest Editors

Manuscript Submission Information

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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

  • manufacturing systems
  • lean manufacturing
  • operational excellence
  • industry 4.0
  • lean automation
  • lean 4.0
  • digitization
  • operational performance
  • data science
  • smart manufacturing

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Published Papers (6 papers)

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Research

25 pages, 2103 KiB  
Article
An Investigation into Lean Implementation Preparedness in the Engineering Projects Sector
by Uzayr Karimulla, Kapil Gupta and Daramy Vandi Von Kallon
Systems 2024, 12(9), 335; https://doi.org/10.3390/systems12090335 - 31 Aug 2024
Viewed by 940
Abstract
Lean methodologies, a system widely used in the manufacturing industry, have demonstrated numerous benefits and added significant value to the industry. In the same way that other industries have benefitted from the application of Lean techniques, the engineering projects sector can also realise [...] Read more.
Lean methodologies, a system widely used in the manufacturing industry, have demonstrated numerous benefits and added significant value to the industry. In the same way that other industries have benefitted from the application of Lean techniques, the engineering projects sector can also realise significant improvements by integrating Lean principles into its processes and operations. The study aims to gain a comprehensive insight into the application of the Lean concept, with a focus on the South African engineering projects sector. The findings of a thorough literature review, focussing on Lean techniques, technology, and the projects sector, examined key variables that have an impact on the effective implementation of Lean methodologies within this industry. The variables studied are skills and expertise, active work methods, and leadership style. The study also explores the impact of digital technologies on Lean implementation, exploring how these technologies enhance the integration of Lean practices. The study includes descriptive statistical analysis, exploratory factor analysis, and a confirmatory factor analysis of the data. A significant relationship is found between variables influencing Lean implementation and the effectiveness of Lean practices within the South African engineering projects sector. Full article
(This article belongs to the Special Issue Lean Manufacturing in Industry 4.0)
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14 pages, 1103 KiB  
Article
Data Science Supporting Lean Production: Evidence from Manufacturing Companies
by Rossella Pozzi, Violetta Giada Cannas and Tommaso Rossi
Systems 2024, 12(3), 100; https://doi.org/10.3390/systems12030100 - 15 Mar 2024
Cited by 2 | Viewed by 2903
Abstract
Research in lean production has recently focused on linking lean production to Industry 4.0 by discussing the positive relationship between them. In the context of Industry 4.0, data science plays a fundamental role, and operations management research is dedicating particular attention to this [...] Read more.
Research in lean production has recently focused on linking lean production to Industry 4.0 by discussing the positive relationship between them. In the context of Industry 4.0, data science plays a fundamental role, and operations management research is dedicating particular attention to this field. However, the literature on the empirical implementation of data science to lean production is still under-investigated and details are lacking in most of the reported contributions. In this study, multiple case studies were conducted involving the Italian manufacturing sector to collect evidence of the application of data science to support lean production and to understand it. The results provide empirical proof of the link and examples of a variety of data science techniques and tools that can be combined to support lean production practices. The findings offer insights into the applications of the traditional lean plan–do–check–act cycle, supporting feedback on performance metrics, total productive maintenance, total quality management, statistical process control, root cause analysis for problem-solving, visual management, and Kaizen. Full article
(This article belongs to the Special Issue Lean Manufacturing in Industry 4.0)
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18 pages, 1650 KiB  
Article
Facing Challenges of Implementing Total Productive Management and Lean Tools in Manufacturing Enterprises
by Tomislav Slavina and Nedeljko Štefanić
Systems 2024, 12(2), 52; https://doi.org/10.3390/systems12020052 - 3 Feb 2024
Viewed by 3201
Abstract
Manufacturing companies are always looking for ways to outperform their competitors. They are constantly trying to improve their efficiency and reduce costs. One method that improves efficiency and maximises the availability of production equipment is total productive maintenance (TPM), which is a lean [...] Read more.
Manufacturing companies are always looking for ways to outperform their competitors. They are constantly trying to improve their efficiency and reduce costs. One method that improves efficiency and maximises the availability of production equipment is total productive maintenance (TPM), which is a lean optimisation philosophy tool that focuses on the optimisation of maintenance. Although TPM is known for improving maintenance, there are many obstacles to its successful implementation. Failure to properly implement TPM can result in additional costs and lost time, and it can have a negative impact on employees. For these reasons, a survey was prepared and conducted among several companies, each involved in a different field of work and having a different number of employees. The main findings of this research are the key factors that can negatively impact the implementation of TPM and lean tools in general, as well as suggestions for improvements that can ensure their successful implementation and sustainability. An analysis was conducted based on the size of each company as well as the job roles within them. The study covers issues that may arise during the implementation of TPM and other lean tools at all levels of the hierarchy in an enterprise and provides guidance on how to manage situations that may prevent the successful application of TPM. Full article
(This article belongs to the Special Issue Lean Manufacturing in Industry 4.0)
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26 pages, 5476 KiB  
Article
Optimization of an Air Conditioning Pipes Production Line for the Automotive Industry—A Case Study
by Ana Laroca, Maria Teresa Pereira, Francisco J. G. Silva and Marisa J. G. P. Oliveira
Systems 2024, 12(2), 42; https://doi.org/10.3390/systems12020042 - 27 Jan 2024
Cited by 1 | Viewed by 2230
Abstract
The following work aims to show how a combination of continuous improvement (CI) and Lean tools can reduce waste and process variability along an air-conditioned pipe production line (PL), calculate its capacity, and improve its efficiency to achieve the expected productivity. A variability [...] Read more.
The following work aims to show how a combination of continuous improvement (CI) and Lean tools can reduce waste and process variability along an air-conditioned pipe production line (PL), calculate its capacity, and improve its efficiency to achieve the expected productivity. A variability study focused on the PL’s balancing was conducted to identify and reduce possible bottlenecks, as well as to evaluate the line’s real capacity. Several layout improvements were made to upgrade the line’s operational conditions and reduce unnecessary movements from the workers. The Constant Work-In-Progress (CONWIP) methodology was also applied to ease the component’s production management in the preparation stage. Additional modifications were implemented to support production and to contribute to the increases in efficiency, quality, and safety on the line. The results revealed an increase in the line’s capacity, associated with an efficiency rise from 28.81% to 47.21% from February to June 2023. The overall equipment effectiveness (OEE) in the same period increased by 18%. This demonstrates that, by interactively applying a mix of tools and methodologies, it is possible to achieve better performance of production lines. This knowledge can help scholars and practitioners to apply the same set of tools to solve usual problems in cell and production lines with performance below expectations. Full article
(This article belongs to the Special Issue Lean Manufacturing in Industry 4.0)
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24 pages, 5466 KiB  
Article
Design Model for the Digital Shadow of a Value Stream
by Nicholas Frick, Jan Terwolbeck, Benjamin Seibel and Joachim Metternich
Systems 2024, 12(1), 20; https://doi.org/10.3390/systems12010020 - 9 Jan 2024
Cited by 3 | Viewed by 2093
Abstract
The value stream method, a key tool in industry to analyze and visualize value streams in production, aims to holistically optimize process steps, reduce waste, and achieve continuous material flow. However, this method primarily relies on data from a single on-site inspection, which [...] Read more.
The value stream method, a key tool in industry to analyze and visualize value streams in production, aims to holistically optimize process steps, reduce waste, and achieve continuous material flow. However, this method primarily relies on data from a single on-site inspection, which is subjective and represents just a snapshot of the process. This limitation can lead to uncertainty and potentially incorrect decisions, especially in industries producing customer-specific products. The increasing digitization in production offers a solution to this limitation by supporting the method through data provision. The concept of the digital shadow emerges as a key tool that systematically captures, processes, and integrates necessary data into a model to enhance traditional value stream mapping. This addresses the method’s shortcomings, especially in heterogeneous IT landscapes and complex value streams. To effectively implement the digital shadow this study identifies concepts of digital shadows and their key components and evaluates them for their relevance in industrial environments using an expert study. Based on the results, a design model is defined. This model entails guidelines to support companies with the practical implementation of the digital shadow of a value stream. Lastly, the model is evaluated on a realistic value stream in a learning factory. Full article
(This article belongs to the Special Issue Lean Manufacturing in Industry 4.0)
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22 pages, 2421 KiB  
Article
Evaluation of Lean Manufacturing Tools and Digital Technologies Effectiveness for Increasing Labour Productivity in Construction
by Kirill Y. Kulakov, Alexandr K. Orlov and Vadim S. Kankhva
Systems 2023, 11(12), 570; https://doi.org/10.3390/systems11120570 - 7 Dec 2023
Cited by 3 | Viewed by 2614
Abstract
Multiple studies are devoted to problems of construction labour productivity and methods of increasing it. These studies contain systematized factors and the main measures that can be applied to influence them. However, the issues of reducingdowntime in design and construction by integrating Lean [...] Read more.
Multiple studies are devoted to problems of construction labour productivity and methods of increasing it. These studies contain systematized factors and the main measures that can be applied to influence them. However, the issues of reducingdowntime in design and construction by integrating Lean manufacturing tools and innovative digital technologies to increase construction labour productivity have not yet been actively studied. This paper examines the quantitative assessment of the impact of tools for Lean construction and the digitalization of business processes on labour productivity when implementing investment projects in development and changes in the effectiveness of projects. The conducted study contains an extensive review of the literature, identifies time losses as an important labour productivity factor, proposes a practical approach to the implementation of Lean 4.0 technology in the activities of a development company, and provides practical calculations of labour productivity for the existing project. Expert and calculated evidence of the positive impact of Lean 4.0 on labour productivity and performance parameters of construction projects are presented here. The effects of the introduction of tools and principles of Lean-digital technologies for construction project participants, as well as recommendations for the implementation of the proposed approach in construction practice, are discussed. Full article
(This article belongs to the Special Issue Lean Manufacturing in Industry 4.0)
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