Journal of Manufacturing Technology Management

Demeter, Krisztina; Szász, Levente; Rácz, Béla-Gergely; Györfy, Lehel-Zoltán

2024 Journal of Manufacturing Technology Management

doi: 10.1108/jmtm-07-2023-0299

The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.Design/methodology/approachUsing a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.FindingsOur findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.Originality/valueRelying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.

Rachinger, Michael; Müller, Julian M.

2024 Journal of Manufacturing Technology Management

doi: 10.1108/jmtm-07-2023-0279

Business Model Innovation is increasingly created by an ecosystem of related companies. This paper aims to investigate the transition of a manufacturing ecosystem toward electric vehicles from a business model perspective.Design/methodology/approachThe authors investigate an automotive manufacturing ecosystem that is in transition toward electric and electrified vehicles, conducting semi-structured interviews with 46 informants from 27 ecosystem members.FindingsThe results reveal that the actions of several ecosystem members are driven by regulations relating to emissions. Novel requirements regarding components and complementary offers necessitate the entry of actors from other industries and the formation of new ecosystem members. While the newly emerged ecosystem has roots in an established ecosystem, it relies on new value offers. Further, the findings highlight the importance of ecosystem governance, while the necessary degree of change in the members' business models depends on their roles and positions in the ecosystem. Therefore, upstream suppliers of components must perform business model adaptation, whereas downstream providers must perform more complex business model innovation.Originality/valueThe paper is among the first to investigate an entire manufacturing ecosystem and analyze its transition toward electric vehicles and the implications for business model innovation.

Momeni, Beheshte; Rapaccini, Mario; Martinsuo, Miia

2024 Journal of Manufacturing Technology Management

doi: 10.1108/jmtm-07-2023-0275

Manufacturers face various challenges and risks during their digital servitization (DS), due to the complexity caused by introducing breakthrough technologies, increasingly complex product-service solutions and new stakeholders in the business network. The process necessitates the implementation of various changes that usually happen over a long period of time. Using complexity management as a theoretical lens, this paper delves into manufacturers’ DS journeys and explores how manufacturers manage the associated complexities.Design/methodology/approachThis paper investigates the DS journey of two manufacturers in a longitudinal case study from 2014 to 2021.FindingsThree main complexity management actions during the DS journey were identified: shaping the digital service system, shaping the organization and shaping the network. Tied to different types of complexities, these actions demonstrate how manufacturers navigate their journey. The findings also reveal different complexity management approaches used at the different stages of this journey.Originality/valueThis paper offers a comprehensive framework for understanding complexity management in the DS journey, including the types of complexities, complexity management actions and complexity management approaches and their rationale. This paper shows that different requirements are created during emerge, consolidate and evolve stages of the DS journey. Manufacturers need a dynamic approach that considers changes in complexities and actions over time.

Martinez, Felipe; Jirsák, Petr

2024 Journal of Manufacturing Technology Management

doi: 10.1108/jmtm-05-2023-0165

Exploring the Lean and Green relationship goes back to the beginnings of Lean manufacturing. Most cases established that companies implementing Lean have Green results. However, there are Lean practices with a higher impact on Green, but others with less impact. Therefore, this paper presents research that explores the relationship between Lean and Green in manufacturing companies and aims to determine whether Lean practices have a higher association with Green aspects.Design/methodology/approachA survey was conducted amongst manufacturing firms to determine their Lean Index (LI). The internally related elements of the Lean construct determined each firm’s LI, whilst Cronbach alpha determined internal LI consistency. The survey also identified firms developing six Green aspects: International Organisation for Standardisation (ISO) 14001, ISO 50001, general Green aspects and the specific aspects of materials, energy and water. An individual sample t-test shows different LI levels of association for each Green aspect. Binomial logistic regression shows the LI element association for each Green aspect.FindingsLI is higher at firms reporting the inclusion of Green aspects. More than half of LI components have a statistically relevant association with the six Green aspects. In general, Ishikawa diagrams had the highest association with Green aspects whilst the lowest was seen in workers as improvement initiators. By grouping the LI elements into their categories, the Lean practices related to controlling processes have a higher association, whilst the involvement of employees has the lowest.Research limitations/implicationsFurther research found in this paper identifies the possibilities for investigating the specificities of each Lean tool to develop Green aspects in companies.Practical implicationsPractitioners learn that Lean and Green are not separate issues in business. This article provides evidence that Lean practices in place at companies are already associated with Green aspects, so integration may already be happening.Originality/valueThis paper provides specifics on the relationship between each Lean practice and developing Green aspects. Thus, this paper specifies the Lean practices that contribute most to Green efficiency to support the joint development of both themes.

Ghobakhloo, Morteza; Fathi, Masood; Iranmanesh, Mohammad; Vilkas, Mantas; Grybauskas, Andrius; Amran, Azlan

2024 Journal of Manufacturing Technology Management

doi: 10.1108/jmtm-12-2023-0530

This study offers practical insights into how generative artificial intelligence (AI) can enhance responsible manufacturing within the context of Industry 5.0. It explores how manufacturers can strategically maximize the potential benefits of generative AI through a synergistic approach.Design/methodology/approachThe study developed a strategic roadmap by employing a mixed qualitative-quantitative research method involving case studies, interviews and interpretive structural modeling (ISM). This roadmap visualizes and elucidates the mechanisms through which generative AI can contribute to advancing the sustainability goals of Industry 5.0.FindingsGenerative AI has demonstrated the capability to promote various sustainability objectives within Industry 5.0 through ten distinct functions. These multifaceted functions address multiple facets of manufacturing, ranging from providing data-driven production insights to enhancing the resilience of manufacturing operations.Practical implicationsWhile each identified generative AI function independently contributes to responsible manufacturing under Industry 5.0, leveraging them individually is a viable strategy. However, they synergistically enhance each other when systematically employed in a specific order. Manufacturers are advised to strategically leverage these functions, drawing on their complementarities to maximize their benefits.Originality/valueThis study pioneers by providing early practical insights into how generative AI enhances the sustainability performance of manufacturers within the Industry 5.0 framework. The proposed strategic roadmap suggests prioritization orders, guiding manufacturers in decision-making processes regarding where and for what purpose to integrate generative AI.

Fani, Virginia; Bucci, Ilaria; Rossi, Monica; Bandinelli, Romeo

2024 Journal of Manufacturing Technology Management

doi: 10.1108/jmtm-11-2023-0509

Examining synergies between Lean, Industry 4.0, and Industry 5.0 principles, the aim is to showcase how Lean's focus on people enhances Industry 5.0 implementations, leading to the development of the Lean 5.0 paradigm. In addition, insights from artisanal industries, like the fashion one, are specifically collected.Design/methodology/approachFirst, a literature review was conducted to define a comprehensive framework to understand how Lean fits into the Human-Centric (HC) paradigm of Industry 5.0. Second, a case study was employed to give empirical insights and identify practical initiatives that brands can pursue, involving two best-in-class leather goods brands located in Italy.FindingsA conceptual framework to pave the way for new paradigm Lean 5.0 was defined and validated through a case study. To path the way for a case study in the fashion industry, the Lean HC paradigm is detailed into domains and related categories to group practices. The empirical insights demonstrate that Lean HC actions can be effectively supported by Industry 4.0 technologies in traditional sectors like the fashion industry, shifting towards Industry 5.0.Practical implicationsThe proposed framework and related practices can be used by companies to facilitate their transition towards Industry 5.0, leveraging on Lean Manufacturing.Originality/valueThe innovative contribution of the present work mainly refers to the proposed conceptual framework, encompassing Lean, HC and Industry 4.0 and introducing Lean 5.0 paradigm. The case study enriches the empirical contributions in the fashion industry.