acatech Industrie 4.0 Maturity Index – A Multidimensional Maturity Model

Zeller, Violett; Hocken, Christian; Stich, Volker

doi:10.1007/978-3-319-99707-0_14

Cited by 32 publications

(15 citation statements)

References 7 publications

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“…During the analysis it is possible to identify four major groups of challenges: interpersonal communication, competences and skills, systems integration, and technological strategy. These groups were derived and adapted from two main maturity models for industry 4.0 readiness: acatech [33] and impuls [34].…”

Section: Resultsmentioning

confidence: 99%

Adoption of digital technologies during the COVID-19 pandemic: Lessons learned from collaborative Academia-Industry R&D case studies

Simões

Ferreira

Castro

et al. 2021

2021 IEEE 19th International Conference on Industrial Informatics (INDIN)

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The need of lockdown, due to COVID-19, led many manufacturing companies to accelerate the adoption of digital technologies. Manufacturing companies were strongly affected by workforce shortages associated with the spread of COVID-19 and the lockdown, as well by connectivity losses among business partners. Therefore, these companies are reviewing their strategies to increase productivity, mainly embracing digital manufacturing technologies. Here the adoption of digital technologies aims to improve efficiency and flexibility in their processes, also improving connectivity among business partners. This study investigates how collaborative academia-industry R&D cases accelerated the adoption of digital technologies by manufacturing companies, given the current COVID-19 pandemic situation. Based on multiple case studies, this article reports the challenges and the strategies of three ongoing collaborative industry-academia R&D projects developed during the COVID pandemic situation. The results are presented in four different perspectives derived from industry 4.0 readiness maturity models: interpersonal communication, personal competencies and skills, systems integration, and technological strategy. It highlights the importance of manufacturing companies to have a welldesigned digitalization strategy, need of continuous training and development of their workforce, and the support of Research & Technology Organizations (RTO) to bring more maturity to the efforts required during a turbulent situation. The results of this paper can provide relevant decision support for manufacturing companies, and its stakeholders, in face of challenges of the actual pandemic and post-pandemic scenario.

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Section: Resultsmentioning

confidence: 99%

Adoption of digital technologies during the COVID-19 pandemic: Lessons learned from collaborative Academia-Industry R&D case studies

Simões

Ferreira

Castro

et al. 2021

2021 IEEE 19th International Conference on Industrial Informatics (INDIN)

View full text Add to dashboard Cite

show abstract

“…The storage and processing of this big amount of data about the production system allow building analytical diagnostic systems. Then based on machine learning predictive systems can be created, as well as complex decision support systems based on expert knowledge [28].…”

Section: Methodsmentioning

confidence: 99%

Development of an industrial cyber-physical platform for small series production using digital twins

Yablochnikov

Chukichev

Timofeeva

et al. 2021

Phil. Trans. R. Soc. A.

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The article describes an industrial cyber-physical platform for small series production using digital twins under development at ITMO University (Saint Petersburg, Russia). The platform is based on the following approaches: group technology, adaptive and selective assembling, and digital twin of production systems and processes. The article presents a mechanism for constructing a unified manufacturing process, and results of an integrated multiscale simulation of an injection moulding process. The issues of ensuring identification and monitoring of objects of the industrial cyber-physical platform are considered. Specific service applications required to implement the smart product concept are discussed. The combination of the considered technologies is used to create digital twins of production system objects. All humans that have different roles in the product value stream can interact with the industrial cyber-physical platform at the three levels, receiving support in performing their tasks. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

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“…Given that the application of advanced digital and automation technologies in intralogistics is limited (see, e.g., Napolitano (2012) or Michel (2016)), examples for Level 5 intralogistics activities are still scarce and our results are thus plausible. In contrast to this, Level 1 processes are still common in intralogistics and it might be questioned whether this mostly analogue and manual process can be considered as being a first step toward Intralogistics 4.0 (Zeller et al 2018).…”

Section: Intralogistics 40 Maturity Of the Casesmentioning

confidence: 99%

Job satisfaction: An explorative study on work characteristics changes of employees in Intralogistics 4.0

Winkelhaus

Grosse

Glock

2022

J of Business Logistics

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The increasing trend toward digitalization in logistics poses a significant managerial challenge, particularly by fundamentally changing the traditional, manual workplaces in intralogistics. Although intralogistics processes have, in some cases, already been automated or are supported by smart technologies, humans remain an inevitable part of future intralogistics but with changing work characteristics. This study aims to examine the influences of the transition toward Intralogistics 4.0 on work characteristics of intralogistics employees. First, a systematic literature review on work characteristics and job satisfaction in a broader Logistics 4.0 context was conducted. Thereafter, a qualitative, explorative methodology was employed to examine the perception of work characteristics that impact job outcomes such as job satisfaction, motivation, and performance at different Intralogistics 4.0 maturity levels. The results of semi‐structured interviews conducted across seven companies demonstrated the significant, heterogeneous changes of work characteristics related to the type of technology applied in Intralogistics 4.0. Our findings indicate that the development toward Intralogistics 4.0‐implemented workplaces does not have a simple or predefined impact on humans; instead, the individual design is relevant and can improve the workplaces with more opportunities for satisfying and motivating jobs.

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acatech Industrie 4.0 Maturity Index – A Multidimensional Maturity Model

Cited by 32 publications

References 7 publications

Adoption of digital technologies during the COVID-19 pandemic: Lessons learned from collaborative Academia-Industry R&D case studies

Adoption of digital technologies during the COVID-19 pandemic: Lessons learned from collaborative Academia-Industry R&D case studies

Development of an industrial cyber-physical platform for small series production using digital twins

Job satisfaction: An explorative study on work characteristics changes of employees in Intralogistics 4.0

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