Review
Automation & Control Systems
Zuhara Chavez, Jannicke Baalsrud Hauge, Monica Bellgran
Summary: This paper examines the digitalization level of implemented solutions in SMEs when handling deviations, finding a focus on practical applications rather than comprehensive frameworks, potentially increasing deployment difficulty for SMEs.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Review
Computer Science, Software Engineering
Huseyin Unlu, Onur Demirors, Vahid Garousi
Summary: Industry 4.0 transforms traditional manufacturing from isolated optimized cells to fully integrated data and product flows across borders. Assessing organizational capability is a well-known approach during the early stages of transitioning to Industry 4.0. However, no widely accepted maturity/readiness model for Industry 4.0 exists, and the objectivity of assessment methods is controversial.
JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS
(2023)
Review
Green & Sustainable Science & Technology
Bruna Maria Geronimo, Giane Goncalves Lenzi
Summary: Currently, testing and calibration laboratories are undergoing organizational restructuring to meet technical and regulatory requirements. Maturity models (MMs) can be used to assist these laboratories in implementing and maintaining management systems. The use of fuzzy logic in the construction of MMs helps remove subjective elements from maturity assessment.
Review
Construction & Building Technology
J. K. D. D. T. Jayanetti, B. A. K. S. Perera, K. G. A. S. Waidyasekara, Mohan Siriwardena
Summary: This study systematically reviews the literature on existing lean-construction-related maturity models through critical review. The study identifies the most common attributes, strengths, and weaknesses among these models. The findings can be used to develop more robust models and enhance the knowledge base on theoretical underpinnings. The study also assists organizations in effectively assessing LC maturity and calls for further research and development in this area.
Review
Construction & Building Technology
Sonali Alankarage, Nicholas Chileshe, Aparna Samaraweera, Raufdeen Rameezdeen, David J. Edwards
Summary: In the past decade, there has been a significant increase in the number of maturity models offered in Building Information Modelling (BIM). However, there are problems with model choice criteria for organizations and understanding of BIM maturity model (BIMMM) application areas. This study conducted a systematic literature review (SLR) using 32 papers published between 2010 and 2021, and found that the development and application of BIMMMs are mainly based on existing maturity models, with the National BIM Standard's Interactive Capability Maturity Model being the most dominant foundation. The lack of applications and validation of mainstream models, as well as doubts about the validity of the models, highlight the need for further research in BIMMMs for their development and application in practice.
ARCHITECTURAL ENGINEERING AND DESIGN MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Marcia Cristina Machado, Tereza Cristina Melo de Brito Carvalho
Summary: This study investigates the relationship between maturity models in information technology companies and sustainability indicators, linking them to decision-making factors for investors and customers. By analyzing COBIT, GRI, and SDG indicators, a set of 50 sustainability indicators covering four dimensions was proposed and validated through analyzing sustainability reports of IT companies. It was found that some IT companies have incorporated SDGs into their strategic objectives.
Review
Chemistry, Analytical
Cristian Rocha-Jacome, Ramon Gonzalez Carvajal, Fernando Munoz Chavero, Esteban Guevara-Cabezas, Eduardo Hidalgo Fort
Summary: This study provides a comprehensive analysis of Industry 4.0, including detailed literature research and diagram analysis. The results offer two proposed diagram analyses of Industry 4.0, which can support digital transformation studies in academia and companies, and provide a simple alternative analysis of the functions and scope of integrating technologies.
Article
Business
Kerem Elibal, Eren Ozceylan
Summary: This paper conducts a comparison of four Industry 4.0 maturity models using TQM principles, and applies fuzzy logic principles for analysis and decision making. The results show that the model by Schumacher et al. (2016) has the highest score in terms of alignment with TQM principles.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Review
Green & Sustainable Science & Technology
Agnes Toth-Peter, Rui Torres de Oliveira, Shane Mathews, Leonie Barner, Sandra Figueira
Summary: The current planetary crisis and the urgency of the situation require more sustainable production and consumption patterns. Businesses, especially multinationals, play a crucial role in transitioning to a circular economy, which offers a promising approach to achieving the UN Sustainable Development Goals. Industry 4.0 technologies have the potential to support this transition through data-driven and smart business processes. However, merging these technologies with a circular economy is a complex process that fundamentally changes the business value chain. This paper provides a systematic overview to better understand the transition process to circular business models and the enabling role of industry 4.0.
JOURNAL OF CLEANER PRODUCTION
(2023)
Review
Computer Science, Information Systems
Siaw-Teng Liaw, Myron Anthony Godinho
Summary: This study provides a literature review on capability maturity models (MMs) for the implementation and evaluation of digital health (DH) ecosystems. It identifies diverse domain-specific MMs and their development, implementation, and evaluation methods. The study also introduces a new category of community-facing MMs. The conclusion suggests using a metamodel like DHPMAT-MM to unify domain-specific MMs and guide the overall implementation and evaluation of DH ecosystems.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
(2023)
Review
Engineering, Industrial
Fotios K. Konstantinidis, Nikolaos Myrillas, Konstantinos A. Tsintotas, Spyridon G. Mouroutsos, Antonios Gasteratos
Summary: This study evaluates the application of machine vision technology in intelligent factories through a systematic literature review strategy and proposes an assessment framework. The findings indicate that machine vision is widely used in various technological areas of Industry 4.0, such as autonomous robots and augmented reality. By analyzing vision-based applications in the automotive manufacturing process, the study clusters the components and processing techniques of machine vision systems and presents the I5.0 technology maturity assessment framework, guiding the integration of machine vision into intelligent factories.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Review
Computer Science, Artificial Intelligence
Raghad Baker Sadiq, Nurhizam Safie, Abdul Hadi Abd Rahman, Shidrokh Goudarzi
Summary: The review highlights that most AI maturity model developments focus on specific domains and employ a bottom-up design approach with descriptive characteristics. Currently, maturity grid and continuous representation with five levels are trending in maturity model development. A significant proportion of studies concentrate on assessing the technology aspect, even in specific domains.
PEERJ COMPUTER SCIENCE
(2021)
Review
Engineering, Industrial
Antonio Carmona-Lavado, Elena M. Gimenez-Fernandez, Vesna Vlaisavljevic, Carmen Cabello-Medina
Summary: This article presents a systematic literature review on cross-industry innovation (CII), a specific form of open innovation (OI) that is increasingly important in the context of digitalization and technological convergence. Previous research on CII is dispersed and adopts different perspectives. The study analyzed 45 articles published between 1997 and 2021, addressing research questions related to the conceptualization, types, features, process, determinants, consequences, and methodological trends of CII. The findings contribute to a comprehensive understanding of CII and offer valuable insights, including a new definition and classification of CII, integration of diverse CII processes, and a network map showing knowledge crossfertilization between industries.
Review
Economics
Nathalia Suchek, Mario Franco
Summary: The paper presents a systematic literature review on the inter-organisational cooperation involving SMEs for sustainability, particularly in relation to the emergence of the circular economy. The review highlights four main categories, namely government-promoted sustainability cooperation, effects of inter-organisational cooperation for sustainability, the process of cooperation oriented towards sustainability, and the discussions on cooperation for the circular economy. The review provides theoretical implications for future research and offers practical implications for entrepreneurs, managers, and policy-makers.
JOURNAL OF THE KNOWLEDGE ECONOMY
(2023)
Review
Education & Educational Research
Lasha Labadze, Maya Grigolia, Lela Machaidze
Summary: This paper explores the benefits, opportunities, challenges, potential limitations, concerns, and prospects of using AI chatbots in education. Research findings highlight the advantages for students in terms of homework and study assistance, personalized learning experience, and skill development. For educators, the main benefits are time-saving assistance and improved pedagogy. However, educators need to address significant challenges and critical factors related to AI applications, such as reliability, accuracy, and ethical considerations.
INTERNATIONAL JOURNAL OF EDUCATIONAL TECHNOLOGY IN HIGHER EDUCATION
(2023)
Article
Otorhinolaryngology
A. Brueckner, J. Klewer, C. Zoelsmann
Proceedings Paper
Computer Science, Information Systems
Julia Friedrich, Vanita Roemer, Kristin Gilbert, Christian Zinke-Wehlmann, Anne Steputat-Raetze, Ulrike Pietrzyk
Summary: Collaborative networks play a crucial role in production and product service systems, improving efficiency and transparency in the value creation process and enhancing working conditions for employees. With the rise of digitalization, providers of personal services are increasingly utilizing collaborative networks, raising the question of how to design these networks to support individual interactions in the context of social services.
SMART AND SUSTAINABLE COLLABORATIVE NETWORKS 4.0 (PRO-VE 2021)
(2021)
Proceedings Paper
Computer Science, Artificial Intelligence
Christian Zinke-Wehlmann, Julia Friedrich
COLLABORATIVE NETWORKS AND DIGITAL TRANSFORMATION
(2019)
Proceedings Paper
Computer Science, Information Systems
Christian Frommert, Anna Haefner, Julia Friedrich, Christian Zinke
COLLABORATIVE NETWORKS OF COGNITIVE SYSTEMS
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
Christian Zinke, Kyrill Meyer, Julia Friedrich, Leopold Reif
ADVANCES IN HUMAN FACTORS IN TRAINING, EDUCATION, AND LEARNING SCIENCES, AHFE 2017
(2018)
Proceedings Paper
Computer Science, Theory & Methods
Frederik Kramer, Naoum Jamous, Michael Becker, Markus Wirth, Stephan Klingner, Julia Friedrich, Martin Schneider
PROCEEDINGS OF THE 50TH ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES
(2017)
Article
Business
Julia Friedrich, Michael Becker, Frederik Kramer, Markus Wirth, Martin Schneider
JOURNAL OF BUSINESS RESEARCH
(2020)
Article
Engineering, Industrial
Xiaoliang Yan, Reed Williams, Elena Arvanitis, Shreyes Melkote
Summary: This paper extends prior work by developing a semantic segmentation approach for machinable volume decomposition using pre-trained generative process capability models, providing manufacturability feedback and labels of candidate machining operations for query 3D parts.
JOURNAL OF MANUFACTURING SYSTEMS
(2024)
Article
Engineering, Industrial
Jing Huang, Zhifen Zhang, Rui Qin, Yanlong Yu, Guangrui Wen, Wei Cheng, Xuefeng Chen
Summary: In this study, a deep learning framework that combines interpretability and feature fusion is proposed for real-time monitoring of pipeline leaks. The proposed method extracts abstract feature details of leak acoustic emission signals through multi-level dynamic receptive fields and optimizes the learning process of the network using a feature fusion module. Experimental results show that the proposed method can effectively extract distinguishing features of leak acoustic emission signals, achieving higher recognition accuracy compared to typical deep learning methods. Additionally, feature map visualization demonstrates the physical interpretability of the proposed method in abstract feature extraction.
JOURNAL OF MANUFACTURING SYSTEMS
(2024)