Ticari Bilimler Fakültesi / Faculty of Commercial Science

Permanent URI for this collectionhttps://hdl.handle.net/11727/2074

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Start date: 2020Subject: search.filters.subject.Enterprise architecture

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    Machine learning-enabled healthcare information systems in view of Industrial Information Integration Engineering
    (2022) Uysal, Murat Pasa; 0000-0002-8349-9403
    Recent studies on Machine learning (ML) and its industrial applications report that ML-enabled systems may be at a high risk of failure or they can easily fall short of business objectives. Cutting-edge developments in this field have increased complexity and also brought new challenges for enterprise information integration. This situation can even get worse when considering the vital importance of ML-enabled healthcare information systems (HEIS). Therefore, the main argument of this paper is that we need to adopt the principles of Industrial Information Integration Engineering (IIIE) for the design, development, and deployment processes of ML-enabled systems. A mixed research paradigm is adopted, and therefore, this study is conducted by following the guidelines and principles of Action Research, Design Science Research, and IIIE. The contributions of this study are two-fold: (a) to draw researchers' and practitioners' attention to the integration problems of ML-enabled systems and discuss them in view of IIIE, and (b) to propose an enterprise integration architecture for ML-enabled HEIS of a uni-versity hospital, which is designed and developed by following the guidelines and principles of IIIE.
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    Smart manufacturing in intelligent digital mesh: Integration of enterprise architecture and software product line engineering
    (2021) Uysal, Murat Pasa; Mergen, A. Erhan
    Smart Manufacturing (SM) has substantial challenges, such as sharing data and integrating different systems or products into an intelligent, digital and interconnected manufacturing context. This situation naturally points to a contemporary paradigm, Intelligent Digital Mesh (IDM). Recent studies have presented the top ten state of the art technology trends called IDM, and they report forecasts about the technical developments for the future. However, the development of smart systems has been challenging, both for IDM and SM. Additionally, various sources of variability and complexities are inherent in these environments. One of them is the application of the development for SM. Except for the limited techniques; the review of literature cannot provide a comprehensive framework, which provides the integration of platform-, system- and enterprise-specific reusable solutions, while addressing the problems of mass customization and variability. Therefore, we conduct a two-phase mixed research, following the guidelines of the Design Science Research Method. The IDM, Enterprise Architecture (EA) and Software Product Line Engineering (SPLE) approaches are combined to produce a Smart Manufacturing Development Framework (SMDF). This study can be viewed as an attempt to enhance SM and information integration knowledge domains.