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Article
Engineering, Industrial
Tongtong Zhou et al.
Summary: Digital servitisation is an important strategy for enhancing industrial companies' competitiveness. However, selecting the appropriate IIoT platform for deploying industrial service is challenging due to a lack of understanding of the required capabilities. To address this issue, a multi-criteria decision making framework is proposed, which combines cloud hierarchical BWM and cloud TOPSIS methods. This framework helps companies accurately determine the criteria weights and ranking of potential platforms, allowing managers to make informed decisions and leverage the IIoT platform for digital servitisation.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Bin Zhou et al.
Summary: This paper proposes a method of analyzing time series data based on an industrial knowledge graph, which effectively improves the knowledge processing efficiency of the manufacturing system by integrating temporal features and semantic information. By using deep learning models and graph embedding techniques, semantic information related to product quality prediction can be extracted from time series data and linked to the knowledge graph, describing the dynamic semantic information of the manufacturing environment.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Geng Zhang et al.
Summary: With the rapid development of information technologies, shared manufacturing is facing a growing need for monitoring and maintenance. Existing research primarily focuses on a resource-centric strategy for management, overlooking the experience data from users/customers. To fill this gap, a hybrid sensing-based approach is proposed for monitoring and maintenance of shared manufacturing resources.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Lin Li et al.
Summary: This study introduces the concept of the backroom effect and investigates the impact of the deterioration rate difference between perishable products in the backroom and on retail shelves on joint shelf-space and inventory decisions. By developing a decision-making model that determines both inventory replenishment policy and shelf space allocation, the study finds that a strategy considering the backroom effect can increase profit.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Xiang T. R. Kong et al.
Summary: This paper introduces an order batching approach based on an automated system to minimize the processing time and system response time of auction orders. The proposed method achieves better efficiency in order processing according to computational experiments.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Xinlai Liu et al.
Summary: This paper proposes a unified five-layer blockchain-enabled secure digital twin platform architecture for small and middle enterprises (SMEs) in the manufacturing industry to overcome the limitations of traditional manufacturing patterns. The experimental results show that the proposed platform, named imseStudio, effectively digitizes manufacturing resources and promotes the transformation towards service manufacturing.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Review
Engineering, Industrial
Chao Liu et al.
Summary: This paper presents a systematic literature review on the digitalisation and servitisation of machine tools in the context of Industry 4.0. The review provides a comprehensive understanding of recent advancements in this field, including key technologies, methods, standards, architectures, and applications. Additionally, a novel conceptual framework called Cyber-Physical Machine Tool (CPMT) is proposed as a systematic approach to achieving digitalisation and servitisation of next-generation machine tools. The paper also discusses major research issues, challenges, and future research directions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Majid Azadi et al.
Summary: Evaluating the performance of providers of Industry 4.0 technologies is a ongoing challenge, and existing methods have some shortcomings. In this study, we propose a comprehensive analytical method based on data envelopment analysis to assess the sustainability of cloud service providers for Industry 4.0.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Ming Li et al.
Summary: Social manufacturing is a new networked manufacturing paradigm that organizes socialized manufacturing resources to meet personalized demands, requiring collaboration among social, cyber, and physical spaces. However, managing the distributed and heterogeneous resources is challenging. This study proposes a blockchain-enabled digital twin collaboration platform as a solution, and conducts a verification experiment.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Zhuming Bi et al.
Summary: This paper investigates the impact of enterprise architecture on system capabilities in dealing with changes and uncertainties in globalized business environments, and proposes a new enterprise architecture to enhance system flexibility, resilience, and adaptability.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Jingwei Guo et al.
Summary: Smart manufacturing is a popular concept that focuses on smarter decision-making and increasing production efficiency. This article proposes the use of Dataspace as a feasible and effective method to manage data in smart manufacturing. The contribution of this research is the design of an industrial Dataspace platform that accommodates the characteristics of smart manufacturing, such as harnessing distributed data, understanding industrial data through ontology or knowledge, and enabling related decisions. An analytical case in Surface Mounting Technology manufacturing is provided to demonstrate the customization and decision support offered by industrial Dataspace.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Andrea de Giorgio et al.
Summary: This study examines whether automatically authored videos of industrial operators can help other operators learn procedural tasks. The results show that expert aid can reduce assembly time for untrained operators, while automatically authored videos have the opposite effect on assembly time. Therefore, hybrid training methods are still necessary.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Lei Ren et al.
Summary: The Industrial Internet of Things (IIoT) plays a critical role in the development of digital servitization in smart manufacturing. However, there is a knowledge gap between different manufacturing fields, hindering the integration and utilization of industrial big data. To address this challenge, a Framework of Manufacturing Knowledge Graph (FMKG) is proposed, along with an attention-based graph embedding model (ABGE), to extract and complement relationships in the knowledge graph for efficient integration and leverage of industrial knowledge.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Litong Zhang et al.
Summary: This paper proposes a modelling and online training method for digital twin workshop to address the difficulties in modelling, simulation, and verification. It describes a multi-level digital twin aggregate modelling method and a digital twin organization system. A spatio-temporal data model is constructed based on the data demand for digital twin aggregates. The paper also presents a training method using truncated normal distribution and a verification method based on real-virtual error for digital twin models. The effectiveness of real-time status monitoring, online model training, and production simulation is verified through a case study.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Erik Flores-Garcia et al.
Summary: This study proposes a data model for multichannel communication that facilitates IIoT-enabled DS for smart production logistics. It presents three findings from a case study, showing the improvements in delivery, makespan, and energy efficiency in material handling.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Baozhuang Niu et al.
Summary: This paper investigates the value of IoT-enabled PDT quotation in a brand's logistics outsourcing decisions and found that the imbalanced payoffs between PDT cost-saving and sales volume expansion may make investing in the IoT-enabled logistics system not beneficial in highly competitive markets.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Wiebke Reim et al.
Summary: Digital platforms in the manufacturing industry face various challenges in collaboration, but these challenges can be addressed through strategies such as transparency, incentive models, servitization, and control.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Business
Bard Tronvoll et al.
INDUSTRIAL MARKETING MANAGEMENT
(2020)
Review
Computer Science, Artificial Intelligence
Pai Zheng et al.
ADVANCED ENGINEERING INFORMATICS
(2019)
Article
Engineering, Industrial
Marco Ardolino et al.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2018)
Article
Automation & Control Systems
Emiliano Sisinni et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2018)
Article
Green & Sustainable Science & Technology
Pai Zheng et al.
JOURNAL OF CLEANER PRODUCTION
(2018)
Article
Engineering, Industrial
Alfred Theorin et al.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2017)
