Editorial to the Special Issue Information Integration for Innovative Design and Smart Manufacturing

2017 ◽  
Vol 02 (04) ◽  
pp. 1702003 ◽  
Author(s):  
Margherita Peruzzini ◽  
Josip Stjepandić
Keyword(s):  
Decision Making ◽  
Information Integration ◽  
Enterprise Management ◽  
Smart Manufacturing ◽  
Intelligent Data Analysis ◽  
Reconfigurable Manufacturing ◽  
Special Issue ◽  
Innovative Design ◽  
Manufacturing Automation ◽  
Key Features

Information integration is one of the key features to foster innovative design approaches and to enable smart manufacturing in modern companies. Future manufacturing will be more automated, more digitalized, but also more flexible, distributed, networked and collaborative. As a consequence, information integration approaches are necessary to support companies to be innovative and profitable. The issue collects valuable examples of how collaborative approaches and interdisciplinary actions can benefit companies, from new idea co-creation to smart enterprise management, from intelligent data analysis to flexible decision-making, from smart management of business relationships to reconfigurable manufacturing automation.

scholarly journals Healthcare Data for Achieving a More Personalized Treatment of Chronic Kidney Disease

Biomedicines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 488
Author(s):  
Francisco Herrera-Gómez ◽  
F. Javier Álvarez
Keyword(s):  
Chronic Kidney Disease ◽  
Decision Making ◽  
Kidney Disease ◽  
Prognostic Markers ◽  
Observational Evidence ◽  
Personalized Treatment ◽  
Special Issue ◽  
Healthcare Data ◽  
Clinical Endpoints ◽  
Risk Patients

The current concept of healthcare incites a more personalized treatment of diseases. To this aim, biomarkers are needed to improve decision-making facing chronic kidney disease (CKD) patients. Prognostic markers provided by real-world (observational) evidence are proposed in this Special Issue entitled “Biomarkers in Chronic Kidney Disease”, with the intention to identify high-risk patients. These markers do not target measurable parameters in patients but clinical endpoints that may be in turn transformed to benefits under the effect of future interventions.

scholarly journals Special Issue of the Manufacturing Engineering Society 2020 (SIMES-2020)

2021 ◽  
Vol 11 (13) ◽  
pp. 5975
Author(s):  
Ana María Camacho ◽  
Eva María Rubio
Keyword(s):  
Applied Sciences ◽  
Modeling And Simulation ◽  
Industry 4.0 ◽  
Product Lifecycle Management ◽  
Special Issue ◽  
Product Lifecycle ◽  
Manufacturing Automation ◽  
Engineering Society ◽  
Manufacturing Engineering ◽  
Lifecycle Management

The Special Issue of the Manufacturing Engineering Society 2020 (SIMES-2020) has been launched as a joint issue of the journals “Materials” and “Applied Sciences”. The 14 contributions published in this Special Issue of Applied Sciences present cutting-edge advances in the field of Manufacturing Engineering focusing on advances and innovations in manufacturing processes; additive manufacturing and 3D printing; manufacturing of new materials; Product Lifecycle Management (PLM) technologies; robotics, mechatronics and manufacturing automation; Industry 4.0; design, modeling and simulation in manufacturing engineering; manufacturing engineering and society; and production planning. Among them, the topic “Manufacturing engineering and society” collected the highest number of contributions (representing 22%), followed by the topics “Product Lifecycle Management (PLM) technologies”, “Industry 4.0”, and “Design, modeling and simulation in manufacturing engineering” (each at 14%). The rest of the topics represent the remaining 35% of the contributions.

scholarly journals Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review

2021 ◽  
Vol 13 (10) ◽  
pp. 5495
Author(s):  
Mihai Andronie ◽  
George Lăzăroiu ◽  
Roxana Ștefănescu ◽  
Cristian Uță ◽  
Irina Dijmărescu
Keyword(s):  
Decision Making ◽  
Internet Of Things ◽  
Literature Review ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Data Driven ◽  
Smart Manufacturing ◽  
Production Networks ◽  
Production Logistics ◽  
Time Production

With growing evidence of the operational performance of cyber-physical manufacturing systems, there is a pivotal need for comprehending sustainable, smart, and sensing technologies underpinning data-driven decision-making processes. In this research, previous findings were cumulated showing that cyber-physical production networks operate automatically and smoothly with artificial intelligence-based decision-making algorithms in a sustainable manner and contribute to the literature by indicating that sustainable Internet of Things-based manufacturing systems function in an automated, robust, and flexible manner. Throughout October 2020 and April 2021, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “Internet of Things-based real-time production logistics”, “sustainable smart manufacturing”, “cyber-physical production system”, “industrial big data”, “sustainable organizational performance”, “cyber-physical smart manufacturing system”, and “sustainable Internet of Things-based manufacturing system”. As research published between 2018 and 2021 was inspected, and only 426 articles satisfied the eligibility criteria. By taking out controversial or ambiguous findings (insufficient/irrelevant data), outcomes unsubstantiated by replication, too general material, or studies with nearly identical titles, we selected 174 mainly empirical sources. Further developments should entail how cyber-physical production networks and Internet of Things-based real-time production logistics, by use of cognitive decision-making algorithms, enable the advancement of data-driven sustainable smart manufacturing.

scholarly journals Nonconscious Cognitive Suffering: Considering Suffering Risks of Embodied Artificial Intelligence

Philosophies ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 24
Author(s):  
Steven Umbrello ◽  
Stefan Lorenz Sorgner
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Embodied Cognition ◽  
Information Integration ◽  
Physical State ◽  
Conscious State ◽  
Human Cognition ◽  
Machine Consciousness

Strong arguments have been formulated that the computational limits of disembodied artificial intelligence (AI) will, sooner or later, be a problem that needs to be addressed. Similarly, convincing cases for how embodied forms of AI can exceed these limits makes for worthwhile research avenues. This paper discusses how embodied cognition brings with it other forms of information integration and decision-making consequences that typically involve discussions of machine cognition and similarly, machine consciousness. N. Katherine Hayles’s novel conception of nonconscious cognition in her analysis of the human cognition-consciousness connection is discussed in relation to how nonconscious cognition can be envisioned and exacerbated in embodied AI. Similarly, this paper offers a way of understanding the concept of suffering in a way that is different than the conventional sense of attributing it to either a purely physical state or a conscious state, instead of grounding at least a type of suffering in this form of cognition.

Expanding Foresight Evaluation Capacity

2019 ◽  
Vol 11 (4) ◽  
pp. 287-291
Author(s):  
Annette L. Gardner ◽  
Peter Bishop
Keyword(s):  
Decision Making ◽  
Professional Practice ◽  
Health Sector ◽  
Systematic Evaluation ◽  
Special Issue ◽  
Scenario Development ◽  
Evaluation Capacity ◽  
The Subject ◽  
Evaluation Approaches

The subject of evaluating foresight work has been around for almost as long as the professional practice itself has, but the field has done little to move closer to a systematic evaluation of its work. This special issue marks the second collection of articles on that project after a special issue of Futures in 2012 (Van Der Duin and Van Der Martin 2012). This issue takes a three-part approach: Part 1: evaluation of foresight in general and evaluation approaches and methods that can support designing an appropriate evaluation; Part 2: evaluation of foresight work in organizations and its impact on long-term thinking and decision-making; and Part 3: evaluation of specific foresight activities—an undergraduate learner foresight experience and a health sector scenario development exercise. The foreword ends with a reflection on the continuing issue of foresight and evaluation.

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