Article
Business
Izlem Tekin Bayrak, Ferhan Cebi
Summary: The era of Industry 4.0 opens up new opportunities for operational efficiency improvement, business model innovation, and enhanced customer experience. However, many manufacturing organizations encounter serious challenges at the beginning of their transformation journey. Existing studies mostly focus on maturity models and readiness assessments, lacking a holistic procedure model for a successful end-to-end transformation. This article presents a procedure model that enables manufacturing organizations to define objectives, analyze current maturity level, prioritize needs, and develop implementation roadmaps. The model has been tested and validated in a white goods manufacturing company.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Article
Computer Science, Interdisciplinary Applications
Ebru Gokalp, Veronica Martinez
Summary: The Digital Transformation Capability Maturity Model (DX-CMM) is designed to assist organizations by providing a comprehensive roadmap to determine their current DX capability level, conduct gap analysis, and provide improvement suggestions. Case study results in the chemical and machine manufacturing domains demonstrate that the DX-CMM is effective in identifying DX maturity levels and providing improvement roadmaps, as well as benchmarking organizations against each other using the same approach.
COMPUTERS IN INDUSTRY
(2021)
Article
Computer Science, Information Systems
Marcelo Fabricio Prim, Jefferson de Oliveira Gomes, Holger Kohl, Ronald Orth, Markus Will, Gabriel Bertholdo Vargas
Summary: Industry 4.0 is a socioeconomic phenomenon that brings significant transformations to industries, including products, processes, services, business models, organizational structures, and strategies. This study aims to identify how intangible factors influence each other across different Industry 4.0 maturity levels, and a conceptual framework was developed to demonstrate the dynamics of these factors. Engaged leaders were found to play a crucial role in developing structural capital factors.
Article
Engineering, Industrial
Christoph Liebrecht, Magnus Kandler, Matthias Lang, Sebastian Schaumann, Nicole Stricker, Thorsten Wuest, Gisela Lanza
Summary: The economically successful implementation of Industry 4.0 methods in industrial companies requires a structured introduction process, including the analysis and evaluation of available methods, selection of suitable ones, and development of specific implementation scenarios with prioritized methods.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Business
Ahmad Sajjad, Wasim Ahmad, Salman Hussain, Bilal Akbar Chuddher, Muhammad Sajid, Mirza Jahanjaib, Muhammad Khurram Ali, Muhammad Jawad
Summary: Developing countries face challenges in adopting Industry 4.0 in their manufacturing sectors due to a lack of compatibility in technological and maturity models. This empirical research presents a modified maturity model based on existing models from Germany and Singapore, called the LM4I4.0, which integrates lean philosophy with Industry 4.0. The model has been validated in the manufacturing industries of Pakistan, showing that the country's maturity level in Industry 4.0 is relatively low.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Hong-Long Chen
Summary: This study evaluates the impact of Industry 4.0 maturity on corporate financial performance, with a focus on the mediating effects of internal business process performance (IBPP), supply chain performance (SCP), and customer performance. The results show that Industry 4.0 maturity significantly affects IBPP, SCP, and customer performance, which in turn influence financial performance. Industry 4.0 magnifies potential returns mainly through IBPP, SCP, and customer performance.
Article
Engineering, Industrial
Daisy Valle Enrique, Giuliano Almeida Marodin, Fernando Bigares Charrua Santos, Alejandro G. Frank
Summary: This study investigates the relationship between Industry 4.0 technologies and production targets such as flexibility, quality, and productivity. The results show that different technology arrangements are adopted based on the specific production targets, and there are interconnections and trade-offs between these targets and the adopted technologies.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(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)
Article
Automation & Control Systems
Jiewu Leng, Shide Ye, Man Zhou, J. Leon Zhao, Qiang Liu, Wei Guo, Wei Cao, Leijie Fu
Summary: Blockchain technology is driving business and industrial innovation as a new generation secure information technology, but its applications in Industry 4.0 are facing challenges such as scalability, flexibility, and cybersecurity issues. This study discusses cybersecurity issues in manufacturing systems and proposes metrics for implementing blockchain applications, providing insights for future research directions in blockchain-secured smart manufacturing.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Engineering, Industrial
Sameh M. Saad, Ramin Bahadori, Hamidreza Jafarnejad
Summary: This study proposed a Smart SME Technology Readiness Assessment (SSTRA) methodology to assess SMEs Industry 4.0 technology readiness, with a focus on smart product design. The SSTRA allows decision-makers to identify and prioritize requirements, and enables SMEs to evaluate their capabilities in relevant technologies of Industry 4.0. The methodology provides decision-making based on data collection, analysis, visualization, and documentation, reducing the risk of further investment and implementation in Industry 4.0 technologies.
JOURNAL OF MANUFACTURING TECHNOLOGY MANAGEMENT
(2021)
Article
Social Issues
Liane Mahlmann Kipper, Sandra Iepsen, Ana Julia Dal Forno, Rejane Frozza, Leonardo Furstenau, Jessica Agnes, Danielli Cossul
Summary: This study identified the key competencies needed for Industry 4.0 through a systematic literature review, emphasizing the importance of integrated efforts by companies, governments, and universities, as well as the establishment of "learning factories" to provide practical experiences for professionals. The main competencies required include leadership, innovation, teamwork, as well as knowledge in information technology, software development, and data analysis, among others.
TECHNOLOGY IN SOCIETY
(2021)
Article
Computer Science, Hardware & Architecture
Fadime Ilisulu, Ayca Kolukisa Tarhan, Kubilay Kavak
Summary: This article introduces a Demand Response Process Assessment Model (DRPAM) for evaluating, implementing, and improving capabilities of customers' demand response processes. The model was developed referencing standards and maturity models, and validated through expert opinions and a case study assessment, proving its effectiveness.
COMPUTER STANDARDS & INTERFACES
(2022)
Article
Engineering, Industrial
Pinosh Kumar Hajoary, P. Balachandra, Jose Arturo Garza-Reyes
Summary: Manufacturing enterprises often struggle to assess and implement Industry 4.0 technologies and processes due to a lack of assessment framework and procedures. To address this, this research proposes a multi-dimensional framework and indicators for assessing Industry 4.0 maturity and preparedness. The study validates the framework through data analysis from a multinational steel manufacturing company and highlights the highest performance in the supply chain dimension and the lowest in the business model dimension.
PRODUCTION PLANNING & CONTROL
(2023)
Review
Engineering, Industrial
Jeff Morgan, Mark Halton, Yuansong Qiao, John G. Breslin
Summary: This paper provides a fundamental research review of Reconfigurable Manufacturing Systems (RMS) and explores the state-of-the-art in distributed and decentralized machine control and machine intelligence. Key areas reviewed include RMS fundamentals, machine control technologies, and machine intelligence paradigms. The paper establishes a vision for next-generation Industry 4.0 manufacturing machines with Smart and Reconfigurable (SR*) capabilities.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Review
Computer Science, Interdisciplinary Applications
Hector Canas, Josefa Mula, Manuel Diaz-Madronero, Francisco Campuzano-Bolarin
Summary: This article focuses on the advances, advantages, limitations, requirements, and methodologies in implementing the strategic Industry 4.0 (I4.0) initiative, particularly in the field of production planning. It proposes a taxonomy of I4.0 design terms and presents models, algorithms, and components used in an I4.0 setting.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Information Systems
Ebru Gokalp, Mert Onuralp Gokalp, Selin coban
Summary: This study investigates the importance of determinants affecting the adoption and usage of blockchain-based SCM systems in organizations. The findings indicate that environment-related determinants are more critical than technology-related or organization-related determinants.
INFORMATION SYSTEMS MANAGEMENT
(2022)
Article
Computer Science, Artificial Intelligence
Sercan Oruc, P. Erhan Eren, Altan Kocyigit
Summary: The study demonstrates the effectiveness of using a constraint programming model and a prototype mobile application for personal process management, showing potential in decision support systems. Quantitative and qualitative evaluations indicate positive feedback for the system in both the planning and execution phases, assisting users in making faster decisions in daily activities.
DECISION SUPPORT SYSTEMS
(2022)
Article
Computer Science, Information Systems
Mert Onuralp Gokalp, Ebru Gokalp, Kerem Kayabay, Altan Kocyigit, P. Erhan Eren
Summary: This paper aims to investigate the social and technical drivers of data science practices and develop a standard model to assist organizations in digital transformation. By integrating literature findings and practitioners' considerations, the Data Science Capability Maturity Model (DSCMM) was developed to assess and improve organizations' data science capabilities.
ONLINE INFORMATION REVIEW
(2022)
Article
Engineering, Industrial
Ebru Gokalp, Veronica Martinez
Summary: The use of on-premises technology to create a competitive advantage in the business environment has led to the new era of digital transformation. Despite the potential benefits, companies struggle in reforming existing processes in line with these technologies. Existing maturity models in the digital transformation domain have been found lacking, leading to the development of a holistic DX-CMM model to assist organizations in improvement efforts.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Computer Science, Software Engineering
Mert Onuralp Gokalp, Ebru Gokalp, Selin Gokalp, Altan Kocyigit
Summary: Data analytics plays a crucial role in gaining competitive advantage, generating business value, and driving revenue streams for organizations. However, the existing literature lacks a comprehensive roadmap to help organizations improve their data analytics maturity. This study proposes a data analytics maturity assessment framework (DAMAF) that evaluates the maturity of an organization's data analytics in a staged manner, providing a structured roadmap and suggestions for improvement.
JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS
(2023)
Article
Business
Kerem Kayabay, Mert Onuralp Gokalp, Ebru Gokalp, P. Erhan Eren, Altan Kocyigit
Summary: This study introduces the Data Science Roadmapping (DSR) to guide organizations in leveraging data for competitive advantage. Results show that DSR can facilitate data-driven development through comprehensive roadmap strategies. Social change is also a significant challenge in achieving data-driven requirements.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Computer Science, Hardware & Architecture
Mert Onuralp Gokalp, Ebru Gokalp, Kerem Kayabay, Selin Gokalp, Altan Kocyigit, P. Erhan Eren
Summary: Business success today is powered by data-centric software, with big data analytics (BDA) generating valuable insights and empowering strategic decision-making. This study addresses the research gap in the BDA domain by proposing a process capability assessment model with six levels, aiming to improve business value through identifying current capability levels and creating a roadmap for continuous improvement.
COMPUTER STANDARDS & INTERFACES
(2022)
Article
Computer Science, Theory & Methods
Ece Isik-Polat, Gorkem Polat, Altan Kocyigit
Summary: In federated learning, a global model is formed by aggregating model updates from participants, while ensuring privacy. However, the global model is vulnerable to attacks such as data poisoning and model poisoning. Existing defense algorithms often make strong assumptions that are not consistent with federated learning and lack comprehensive experimental analyses. We propose a defense algorithm called ARFED that does not make any assumptions and considers the outlier status of participant updates based on the distance to the global model. Extensive experiments demonstrate the robust defense capability of ARFED against different attacks.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Computer Science, Software Engineering
Ebru Gokalp, Bora Caliskanbas, Altan Kocyigit
Summary: The Software Product Line (SPL) approach is gaining attention for its benefits in reducing costs, improving quality, and shortening delivery time. However, organizations face challenges in implementing this approach and need a clear road map. To address this, we developed the SPL Capability Maturity Model (SPL-CMM) to assess SPL-specific processes and guide process improvement, based on the SPICE-ISO/IEC 330xx standard.
JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS
(2023)
Proceedings Paper
Engineering, Multidisciplinary
Kerem Nazliel, Kerem Kayabay, Mert Onuralp Gokalp, Ebru Gokalp, Erhan Eren
Summary: This study develops a comprehensive technology selection methodology for Data Science by combining quantitative multi-criteria decision-making methods with qualitative group decision-making approaches. The proposed methodology allows decision-makers to select the most suitable data science tools according to project requirements and provides information on technology categories, functional and non-functional requirements, and possible technology stacks.
2022 IEEE TECHNOLOGY AND ENGINEERING MANAGEMENT CONFERENCE (TEMSCON EUROPE)
(2022)
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)
