A Maturity Model for Manufacturing 4.0 in Emerging Countries

Caiado, Rodrigo Goyannes Gusmão; Scavarda, Luiz Felipe; Nascimento, Denise Cristina de Oliveira; Ivson, Paulo; Cunha, Vitor Heitor Cardoso

doi:10.1007/978-3-030-23816-2_38

Cited by 5 publications

(4 citation statements)

References 20 publications

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“…Numerous studies have examined the practicality of these tools in various industries [139,140] and different interand intra-organizational processes [110,111]. MMs have proven to be useful for both structured companies and small to medium-sized enterprises [112,138,[141][142][143], as well as in industrialized and emerging developing countries [8,107,144]. In this study, we aimed to address four research questions (RQs) concerning significant research contributions (RQ1), the evolution of topics over time (RQ2), key criteria for definition, design, and application (RQ3), and potential future developments (RQ4).…”

Section: Discussion and Future Enhancementsmentioning

confidence: 99%

“…Different approaches can be followed for the development of a MM, including theory-driven, practitioner-based, or mixed-design approaches. Theory-driven approaches commonly rely on literature research, whereas practitioner-based approaches make use of empirical development tools such as interviews [87,125,126], focus groups [8,16], and Delphi studies [18,36,127]. Analytical approaches, such as AHP [10,128,129], fuzzy theory [100,109,130], and principal component analysis [131], are less frequent but still noteworthy.…”

Section: Application Criteria Of Mms For Scmlmentioning

confidence: 99%

“…The former offer general frameworks for supply chain assessment, such as activity-based costing, balanced scorecard, and supply chain operation reference model. The latter apply maturity concepts in specific activities involved in the supply chain, such as the logistics [7], manufacturing [8], and sales and operations planning [9].…”

Section: Introductionmentioning

confidence: 99%

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Trends and Recommendations for Enhancing Maturity Models in Supply Chain Management and Logistics

Ferraro,

Leoni,

Cantini

et al. 2023

Applied Sciences

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Maturity models (MMs) are strategic tools used to assess and improve the current state of processes, objects, or people, with the goal of achieving continuous performance enhancement. While MMs are applied in various fields, their scope, design, and application criteria within Supply Chain Management and Logistics (SCML) lack comprehensive studies. This article aims to address this gap through a systematic literature review. The review analyzes 137 relevant articles using both bibliometric and content analysis techniques. The bibliometric analysis identifies major contributions, popular journals, and the classification and evolution of key keywords. The content analysis focuses on critical criteria related to the scope, design, and application of MMs. The findings reveal a growing emphasis on models assessing Industry 4.0 readiness and sustainability principles. However, several gaps are identified, including limited attention to optimizing and integrating logistic processes, underutilized and unvalidated MMs, and the absence of comprehensive improvement guidelines. Based on these trends and research gaps, this study proposes five recommendations for future developments that benefit both academics and practitioners. These recommendations aim to address the identified limitations and provide guidance for comprehensive and effective improvement strategies.

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Section: Discussion and Future Enhancementsmentioning

confidence: 99%

Section: Application Criteria Of Mms For Scmlmentioning

confidence: 99%

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Trends and Recommendations for Enhancing Maturity Models in Supply Chain Management and Logistics

Ferraro,

Leoni,

Cantini

et al. 2023

Applied Sciences

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“…The exponential development of technology in recent years is highlighted by the concept of Industry 4.0 and respective initiatives in various contexts of the Smart City, Engineering and Construction (SCEC) sectors, such as Building 4.0 [1], Real Estate 4.0 [2], Construction 4.0 [3][4][5][6], Mining 4.0 [7,8], Education 4.0 [9][10][11], and Manufacturing 4.0 [12,13]. The Industry 4.0 concept relies on connecting physical environments with digital ecosystems.…”

Section: Introductionmentioning

confidence: 99%

Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment

2021

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Construction projects and cities account for over 50% of carbon emissions and energy consumption. Industry 4.0 and digital transformation may increase productivity and reduce energy consumption. A digital twin (DT) is a key enabler in implementing Industry 4.0 in the areas of construction and smart cities. It is an emerging technology that connects different objects by utilising the advanced Internet of Things (IoT). As a technology, it is in high demand in various industries, and its literature is growing exponentially. Previous digital modeling practices, the use of data acquisition tools, human–computer–machine interfaces, programmable cities, and infrastructure, as well as Building Information Modeling (BIM), have provided digital data for construction, monitoring, or controlling physical objects. However, a DT is supposed to offer much more than digital representation. Characteristics such as bi-directional data exchange and real-time self-management (e.g., self-awareness or self-optimisation) distinguish a DT from other information modeling systems. The need to develop and implement DT is rising because it could be a core technology in many industrial sectors post-COVID-19. This paper aims to clarify the DT concept and differentiate it from other advanced 3D modeling technologies, digital shadows, and information systems. It also intends to review the state of play in DT development and offer research directions for future investigation. It recommends the development of DT applications that offer rapid and accurate data analysis platforms for real-time decisions, self-operation, and remote supervision requirements post-COVID-19. The discussion in this paper mainly focuses on the Smart City, Engineering and Construction (SCEC) sectors.

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