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Towards Lean Production in Industry 4.0

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Products and Services".

Deadline for manuscript submissions: closed (1 October 2023) | Viewed by 18678

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Special Issue Editors

Dr. Rui M. Lima

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Algoritmi Research Center, Department of Production and Systems, School of Engineering, University of Minho, Guimarães, Portugal
Interests: industrial engineering and management; production management; lean and agile project management; lean healthcare; lean thinking; engineering education; project-based learning (PBL); active learning; university-business cooperation (UBC)

Dr. Guilherme Tortorella

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Department of Mechanical Engineering, University of Melbourne, Melbourne 3010, Australia
Interests: industrial engineering and management; lean production management; Industry 4.0; organizational learning

Prof. Dr. Jiju Antony

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Industrial and Systems Engineering, Khalifa University, Abu Dhabi 127788, United Arab Emirates
Interests: operational excellence; continuous improvement; quality management and quality engineering

Prof. Dr. Daniel Luiz De Mattos Nascimento

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Guest Editor

Department of Business Management, University of Jaén, Linares, Spain
Interests: industrial engineering and management; lean production management; Industry 4.0; organizational learning
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Special Issue Information

Dear Colleagues,

The faster evolving processes and systems that allow data gathering and digitalization of processes in industries and services have been creating the right environment for connectivity between systems, machines, components, parts, items, and people. The connectivity may happen inside and outside a company, connecting companies with other companies and between companies and customers, creating the opportunity for co-design and co-production in faster-interconnected dynamic markets. All these possibilities of digitally accessing data, in real time if necessary, develop the conditions for faster improved decision-making processes and the development of agile learning organizations (Tortorella et al., 2020; Ghobakhloo, 2020; Santos et al., 2021; Schuh et al., 2020).

In fact, I4.0 is not only about technology (Jesus and Lima, 2020; Sony and Naik, 2020) and one may even argue that the effective implementation of the expected results of the fourth industrial revolution is achieved when employers and technology are interconnected in such ways that the best of this interconnection is achieved. To proceed on this path, it is of the utmost importance to foster the way people adapt and develop their competences to work in agile teams capable of incorporating the expected innovations and act as active innovators and influencer agents. Thus, the technological dimensions of I4.0 need to be strongly linked with the cultural and organizational aspects of I4.0 for better and real change into a new interconnected industrial environment (Mohelska and Sokolova, 2018).

Lean Production has been focusing on serving the right value to the customer at the right time, dealing with reductions in inefficiencies of companies (Holweg, 2007). This path has been walked by designing, organizing, planning, and controlling production systems to reduce production waste, involving teams in the process of change and continuous improvement (Krafcik, 1988; Shah and Ward, 2007). In summary, Lean Production can be a way to improve organizational readiness and make the most of the transition to Industry 4.0 (Vinodh et al., 2021).

What are the needs, opportunities, and solutions of Lean Production in Industry 4.0 and its relation to new sustainable services and industries’ organizational and management approaches, methods, and culture?
How can an organization know it is ready to embrace and how Lean approaches can support a successful interconnected transition to Industry 4.0?

In summary, this Special Issue is focused on not only the way Lean may evolve in this new environment of sustainable Industry 4.0 but also on how this new hyper-connected world may transform the Lean approaches and methods. This transformation must be clearly linked with one of the three pillars of sustainability—social, environmental, or economic—either in the overall background, assumptions, objectives, methods, or results of the proposed studies. Finally, each proposal must explicitly spell out how it can impact organizations and academic scholars working in the field.

References

Ghobakhloo, M. (2020). Industry 4.0, digitization, and opportunities for sustainability. Journal of Cleaner Production, 252, 119869.

Holweg, M. (2007). The genealogy of lean production. Journal of Operations Management, 25(2), 420-437.

Krafcik, J. F. (1988). Triumph of the lean production system. Sloan Management Review, 30(1), 41-52.

Jesus, C., & Lima, R. M. (2020). Literature Search of Key Factors for the Development of Generic and Specific Maturity Models for Industry 4.0. Applied Sciences (MDPI), 10(17), p. 5825. https://doi.org/10.3390/app10175825.

Mohelska, H., & Sokolova, M. (2018). Management approaches for Industry 4.0–the organizational culture perspective. Technological and Economic Development of Economy, 24(6), 2225-2240.

Santos, L.M.A.L., da Costa, M.B., Kothe, J.V., Benitez, G.B., Schaefer, J.L., Baierle, I.C. and Nara, E.O.B. (2021). Industry 4.0 collaborative networks for industrial performance. Journal of Manufacturing Technology Management, 32(2), 245-265.

Shah, R., & Ward, P. T. (2007). Defining and developing measures of lean production. Journal of Operations Management, 25(4), 785-805.

Schuh, G., Anderl, R., Dumitrescu, R., Krüger, A., & Hompel, M. T. (2020). Industrie 4.0 Maturity Index: Managing the Digital Transformation of Companies - update 2020 - acatech study. acatech - National Academy of Science and Engineering. https://en.acatech.de/publication/industrie-4-0-maturity-index-update-2020/

Sony, M., & Naik, S. (2020). Industry 4.0 integration with socio-technical systems theory: A systematic review and proposed theoretical model. Technology in Society, 61, 101248.

Tortorella, G. L., Vergara, A. M. C., Garza-Reyes, J. A., & Sawhney, R. (2020). Organizational learning paths based upon industry 4.0 adoption: An empirical study with Brazilian manufacturers. International Journal of Production Economics, 219, 284-294.

Vinodh, S., Antony, J., Agrawal, R., & Douglas, J. A. (2021). Integration of continuous improvement strategies with Industry 4.0: A systematic review and agenda for further research. TQM Journal, 33(2), 441–472. https://doi.org/10.1108/TQM-07-2020-0157

Dr. Rui M. Lima
Prof. Dr. Guilherme Tortorella
Prof. Dr. Jiju Antony
Prof. Dr. Daniel Luiz De Mattos Nascimento
Guest Editors

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Keywords

lean production
Industry 4.0
sustainability
agile management
continuous improvement

Published Papers (7 papers)

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Research

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24 pages, 2503 KiB

Open AccessArticle

A Maturity Model to Become a Smart Organization Based on Lean and Industry 4.0 Synergy

by Bertha Leticia Treviño-Elizondo, Heriberto García-Reyes and Rodrigo E. Peimbert-García

Sustainability 2023, 15(17), 13151; https://doi.org/10.3390/su151713151 - 1 Sep 2023

Cited by 2 | Viewed by 1524

Abstract

This paper proposes a maturity model (MM) to become a smart organization considering Lean as a key enabler to drive I4.0 adoption. A systematic literature review on I4.0 and Lean concepts plus I4.0 adoption models was conducted through the PRISMA method based on articles from Scopus and Web of Science databases, and records from official websites (e.g., consulting firms) published between 2011 and 2022. Identifying the Lean and I4.0 relationship and comparing the models’ relevant characteristics allowed the development of the MM proposal. Although previous research refers to Lean and I4.0 collaboration, the opportunity to design a reference model for adopting both approaches was identified since their interaction enhances value creation. The comprehensive model supports structuring the types of Lean principles/methods/tools and I4.0 technologies and their action to link them and define which of them need to be implemented according to the maturity level chronologically. Additionally, the proposed MM provides an adoption roadmap that starts eliminating non-added activities in the initial stages for process improvement to integrate I4.0 enabling technologies later. The model makes it possible for practitioners to generate implementation and development processes oriented toward I4.0 adoption based on maturity levels in which Lean has the starting point at the first ones. Hence, it defines the enabling technologies to be incorporated and linked throughout the value chain, enhancing a Lean culture. This model will help organizations to become “smart” by allowing them to transition toward the best technology investment and continuously add value to their processes, people, and products. Moreover, the results will motivate researchers to study further the application of models for I4.0 adoption in which Lean is integrated to fill the gap with the I4.0 embrace caused by quickly changing industrial environments and the uncertainty and unknowledge of guidelines associated with incorporating new technologies. Full article

(This article belongs to the Special Issue Towards Lean Production in Industry 4.0)

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20 pages, 2748 KiB

Open AccessArticle

Improving the Performance of a SME in the Cutlery Sector Using Lean Thinking and Digital Transformation

by José Dinis-Carvalho, Rui M. Sousa, Inês Moniz, Helena Macedo and Rui M. Lima

Sustainability 2023, 15(10), 8302; https://doi.org/10.3390/su15108302 - 19 May 2023

Cited by 2 | Viewed by 1515

Abstract

The main purpose of this paper is to show that if three specific contextual factors are present in a company, it is possible to achieve great performance improvements with a lean and industry 4.0 implementation. In terms of research methods, a case study was carried out of a project to implement digitalization and Lean practices in a cutlery company, which in fact encompassed a project of master’s degree in engineering and industrial management. Thus, the research question is: “It is possible to achieve major improvements in a lean and industry 4.0 implementation if three specific contextual factors are present in the company, namely (i) commitment of top management, (ii) knowledge on digitalization and lean, and (iii) very low Value-Added Ratio?”. Regarding the company project, action-research was adopted, and the project team began by mapping and diagnosing the production processes of the two product families (knives and spoons/forks). High levels of work in process, long throughput times, poor flow planning and control, and high stocks of finished products, quickly stood out in both families. Improvement proposals were developed and implemented, namely: (i) creation of a production scheduling and control system, (ii) improvement of the warehouse stock management system, and (iii) adoption of new routines, management tools, visual management, and kaizen meetings. The results achieved were excellent (e.g., throughput time reduced by 27.6% and productivity increased by 36.5%) and aligned with Sustainable Development Goals SDG 9 and 12. The findings of this study corroborate that exceptional results in the company performance can be achieved through a lean and industry 4.0 intervention, if the three referred contextual factors occur. Full article

(This article belongs to the Special Issue Towards Lean Production in Industry 4.0)

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21 pages, 1432 KiB

Open AccessArticle

A Socio-Technical Framework for Lean Project Management Implementation towards Sustainable Value in the Digital Transformation Context

by Bianca Felizardo Lima, Julio Vieira Neto, Renan Silva Santos and Rodrigo Goyannes Gusmão Caiado

Sustainability 2023, 15(3), 1756; https://doi.org/10.3390/su15031756 - 17 Jan 2023

Cited by 8 | Viewed by 3471

Abstract

Motivated by the project uncertainties of complex realities brought by the fourth industrial revolution, Industry 4.0 (I4.0), researchers must look at Lean project management (LPM) soft skills as a new mindset to have a holistic view of customer needs and to improve value to the organization. In the digital transformation era, it is essential that Lean practitioners develop socio-technical thinking while also prioritizing interpersonal soft skills that directly affect their ability to solve problems in order for the company to grow sustainably. This paper aims to identify the critical soft skills (CSSs) to implement LPM in the I4.0 era and to investigate, from the perspective of organizations, the latent factors for LPM implementation that generate sustainable value. For this purpose, a mixed-method approach was used, combining literature review and a survey with 166 Brazilian professionals. This empirical study intends to set the CSSs from a practice perspective and explore the benefits they generate throughout the organization. Data analysis was conducted with descriptive statistics and factorial analysis. Research findings revealed convergences regarding the practitioners’ perception regarding the ten CSSs identified in the literature, and portray two latent factors, human and process factors, which can assist decision-makers in implementing LPM by offering a better perspective of the key factors that add sustainable value for companies in the digital transformation context. This study contributes to the debate on rethinking traditional skills, accentuates the need for adjustments, and proposes a socio-technical framework that can be used in a project manager’s routine to enable better Lean project execution, help with decision making, and increase the understanding and meeting of customer needs. Full article

(This article belongs to the Special Issue Towards Lean Production in Industry 4.0)

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12 pages, 1880 KiB

Open AccessCommunication

Performance Measurement Systems in Continuous Improvement Environments: Obstacles to Their Effectiveness

by Flávio Cunha, José Dinis-Carvalho and Rui M. Sousa

Sustainability 2023, 15(1), 867; https://doi.org/10.3390/su15010867 - 3 Jan 2023

Cited by 3 | Viewed by 3199

Abstract

The implementation of an effective performance measurement system (PMS) is essential in organizations seeking continuous improvement and sustainability, especially in the context of Industry 4.0. However, a number of barriers/obstacles hampers this effectiveness. For example, the inclusion of performance indicators without practical use, or presenting absurd results, are frequent in the industry, leading people to distrust and devalue such systems. The main research question in this study is: What are the main obstacles to effective performance measurement systems in organizations? These obstacles will be identified and categorized, and some conditions required to eliminate/mitigate them will be explored. A systematic literature review is carried out, according to the PRISMA methodology, to identify the most frequent factors referred to as obstacles to PMS effectiveness, due to their negative influence on the implementation, use or maintenance of these systems. This review resulted in the identification of 175 obstacles that were then classified into 19 types of obstacles divided into 6 categories, whose definition was inspired by the 6M approach usually associated with Ishikawa diagrams. Then, the relationships between the obstacles are explored and investigated in order to identify interdependencies that may further influence the effectiveness of the PMS. Solutions and methodologies that can help mitigate/eliminate their impact on PMS effectiveness are also identified. Full article

(This article belongs to the Special Issue Towards Lean Production in Industry 4.0)

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34 pages, 2785 KiB

Open AccessArticle

Using Industry 4.0’s Big Data and IoT to Perform Feature-Based and Past Data-Based Energy Consumption Predictions

by Jonathan Gumz, Diego Castro Fettermann, Enzo Morosini Frazzon and Mirko Kück

Sustainability 2022, 14(20), 13642; https://doi.org/10.3390/su142013642 - 21 Oct 2022

Cited by 5 | Viewed by 1572

Abstract

Industry 4.0 and its technologies allow advancements in communications, production and management efficiency across several segments. In smart grids, essential parts of smart cities, smart meters act as IoT devices that can gather data and help the management of the sustainable energy matrix, a challenge that is faced worldwide. This work aims to use smart meter data and household features data to seek the most appropriate methods of energy consumption prediction. Using the Cross-Industry Standard Process for Data Mining (CRISP-DM) method, Python Platform, and several prediction methods, prediction experiments were performed with household feature data and past consumption data of over 470 smart meters that gathered data for three years. Support vector machines, random forest regression, and neural networks were the best prediction methods among the ones tested in the sample. The results help utilities (companies that maintain the infrastructure for public services) to offer better contracts to new households and to manage their smart grid infrastructure based on the forecasted demand. Full article

(This article belongs to the Special Issue Towards Lean Production in Industry 4.0)

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15 pages, 660 KiB

Open AccessArticle

Green Defense Industries in the European Union: The Case of the Battle Dress Uniform for Circular Economy

by João Reis, David Pascoal Rosado, Yuval Cohen, César Pousa and Adriane Cavalieri

Sustainability 2022, 14(20), 13018; https://doi.org/10.3390/su142013018 - 12 Oct 2022

Cited by 2 | Viewed by 2348

Abstract

As climate change is at the top of the world’s agenda, the armed forces and other defense actors must give a signal that they are environmentally responsible. In this regard, the defense industry should be one of the first actors to devise new strategies and actions aimed at reducing the environmental footprint. This article focuses on the measures being taken by the defense industry and the armed forces, and on how technology, the circular economy (CE) and Lean principles can contribute to a better environment. A qualitative multimethod research model was used, covering more than one research method, such as a systematic literature review and a case study research. Although the literature highlights that the defense sector in Europe is far from being a green actor, a transition to the CE was identified. In that regard, the European Union (EU) defense industry has been a key player in CE R strategies, such as: repurpose, remanufacture, repair, reuse, reduce and rethink. The contribution of new technologies has empowered military equipment to acquire enhanced characteristics, such as material resistance, while EU technology centers have been instrumental in a green transition. Additionally, more comprehensive research is needed in order to allow generalization of the results. Full article

(This article belongs to the Special Issue Towards Lean Production in Industry 4.0)

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Review

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25 pages, 1408 KiB

Open AccessReview

Lean, Six Sigma, and Simulation: Evidence from Healthcare Interventions

by Diego Tlapa, Ignacio Franco-Alucano, Jorge Limon-Romero, Yolanda Baez-Lopez and Guilherme Tortorella

Sustainability 2022, 14(24), 16849; https://doi.org/10.3390/su142416849 - 15 Dec 2022

Cited by 3 | Viewed by 4236

Abstract

In the Industry 4.0 era, healthcare services have experienced more dual interventions that integrate lean and six sigma with simulation modeling. This systematic review, which focuses on evidence-based practice and complies with the PRISMA guidelines, aims to evaluate the effects of these dual interventions on healthcare services and provide insights into which paradigms and tools produce the best results. Our review identified 4018 studies, of which 39 studies met the inclusion criteria and were selected. The predominantly positive results reported in 73 outcomes were mostly related to patient flow: length of stay, waiting time, and turnaround time. In contrast, there is little reported evidence of the impact on patient health and satisfaction, staff wellbeing, resource use, and savings. Discrete event simulation stands out in 74% of the interventions as the main simulation paradigm. Meanwhile, 66% of the interventions utilized lean, followed by lean-six sigma with 28%. Our findings confirm that dual interventions focus mainly on utilization and access to healthcare services, particularly on either patient flow problems or problems concerning the allocation of resources; however, most interventions lack evidence of implementation. Therefore, this study promotes further research and encourages practical applications including the use of Industry 4.0 technologies. Full article

(This article belongs to the Special Issue Towards Lean Production in Industry 4.0)

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