다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Machine learning and reasoning for predictive maintenance in Industry 4.0: Current status and challenges

Due to increased competitive pressure, modern organizations tend to rely on knowledge and its exploitation to sustain a long-term advantage. This calls for a precise understanding of knowledge management (KM) processes and, specifically, how knowledge is created, shared/transferred, acquired, stored/retrieved, and applied throughout an organizational system. However, since the beginning of the new millennium, such KM processes have been deeply affected and molded by the advent of the fourth industrial revolution, also called Industry 4.0, which involves the interconnectedness of machines and their ability to learn and share data autonomously. For this reason, the present article investigates the intellectual structure and trends of KM in Industry 4.0. Bibliometric analysis and a systematic literature review are conducted on a total of 90 relevant articles. The results reveal six clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge of Industry 4.0 and its consequences.

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Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Aims and objectives  This study presents a cost–utility analysis that compared medium- vs high-fidelity human patient simulation manikins in nursing education The analysis sought to determine whether the extra costs associated with high-fidelity manikins can justify the differences, if any, in the outcomes of clinical reasoning, knowledge acquisition and student satisfaction

Background  Investment in simulated learning environments has increased at an unprecedented pace One of the driving forces is the potential for simulation experiences to improve students’ learning and engagement A cost-effectiveness analysis is needed to inform decisions related to investment in and use of simulation equipment

Method  Costs associated with the use of medium- and high-fidelity manikins were calculated to determine the total cost for each A cost-utility analysis using multiattribute utility function was then conducted to combine costs and three outcomes of clinical reasoning, knowledge acquisition and student satisfaction from a quasi-experimental study to arrive at an overall cost utility

Results  The cost analysis indicated that to obtain equivalent clinical reasoning, knowledge acquisition and student satisfaction scores, it required $AU1·21 (US$ 1·14; €0·85) using medium-fidelity as compared with $AU6·28 (US$6·17; €4·40) for high-fidelity human patient simulation manikins per student

Conclusion  Based on the results of the cost-utility analysis, medium-fidelity manikins are more cost effective requiring one-fifth of the cost of high-fidelity manikins to obtain the same effect on clinical reasoning, knowledge acquisition and student satisfaction

Relevance to clinical practice  It is important that decision-makers have an economic analysis that considers both the costs and outcomes of simulation to identify the approach that has the lowest cost for any particular outcome measure or the best outcomes for a particular cost

A cost–utility analysis of medium vs. high‐fidelity human patient simulation manikins in nursing education

An Anthology of Theories and Models of Design

An ontological basis for computer aided innovation

Use of formal ontologies as a foundation for inventive design studies

Towards a formal definition of contradiction in inventive design

Following the trend of Industry 4.0, automation in different manufacturing processes has triggered the use of intelligent condition monitoring systems, which are crucial for improving productivity ...

Cecilia Zanni-Merk

Papers

An ontological basis for computer aided innovation

Use of formal ontologies as a foundation for inventive design studies

Towards a formal definition of contradiction in inventive design

Smart Condition Monitoring for Industry 4.0 Manufacturing Processes: An Ontology-Based Approach

Context Modeling for Industry 4.0: an Ontology-Based Proposal