scholarly journals An Adapted Model of Cognitive Digital Twins for Building Lifecycle Management

2021 ◽  
Vol 11 (9) ◽  
pp. 4276
Author(s):  
Ibrahim Yitmen ◽  
Sepehr Alizadehsalehi ◽  
İlknur Akıner ◽  
Muhammed Ernur Akıner
Keyword(s):  
Decision Making ◽  
Process Optimization ◽  
Cognitive Abilities ◽  
Digital Twins ◽  
Automation And Control ◽  
And Control ◽  
Dynamic Process Optimization ◽  
Lifecycle Management ◽  
Self Learning ◽  
Aec Industry

In the digital transformation era in the Architecture, Engineering, and Construction (AEC) industry, Cognitive Digital Twins (CDT) are introduced as part of the next level of process automation and control towards Construction 4.0. CDT incorporates cognitive abilities to detect complex and unpredictable actions and reason about dynamic process optimization strategies to support decision-making in building lifecycle management (BLM). Nevertheless, there is a lack of understanding of the real impact of CDT integration, Machine Learning (ML), Cyber-Physical Systems (CPS), Big Data, Artificial Intelligence (AI), and Internet of Things (IoT), all connected to self-learning hybrid models with proactive cognitive capabilities for different phases of the building asset lifecycle. This study investigates the applicability, interoperability, and integrability of an adapted model of CDT for BLM to identify and close this gap. Surveys of industry experts were performed focusing on life cycle-centric applicability, interoperability, and the CDT model’s integration in practice besides decision support capabilities and AEC industry insights. The evaluation of the adapted model of CDT model support approaching the development of CDT for process optimization and decision-making purposes, as well as integrability enablers confirms progression towards Construction 4.0.

Individual Differences in Decision Making Depend on Cognitive Abilities, Monitoring and Control

2016 ◽  
Vol 30 (2) ◽  
pp. 209-223 ◽  
Author(s):  
Simon A. Jackson ◽  
Sabina Kleitman ◽  
Lazar Stankov ◽  
Pauline Howie
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Abilities ◽  
Monitoring And Control ◽  
And Control

Uncertainty Quantification for Additive Manufacturing Process Improvement: Recent Advances

2021 ◽  
Author(s):  
Sankaran Mahadevan ◽  
Paromita Nath ◽  
Zhen Hu
Keyword(s):  
Decision Making ◽  
Additive Manufacturing ◽  
Uncertainty Quantification ◽  
Process Optimization ◽  
Data Driven ◽  
Future Research ◽  
Multi Scale ◽  
Uncertainty Sources ◽  
Optimization And Control ◽  
And Control

Abstract This paper reviews the state of the art in applying uncertainty quantification (UQ) methods to additive manufacturing (AM). Physics-based as well as data-driven models are increasingly being developed and refined in order to support process optimization and control objectives in AM, in particular to maximize the quality and minimize the variability of the AM product. However, before using these models for decision-making, a fundamental question that needs to be answered is to what degree the models can be trusted, and consider the various uncertainty sources that affect their prediction. Uncertainty quantification (UQ) in AM is not trivial because of the complex multi-physics, multi-scale phenomena in the AM process. This article reviews the literature on UQ methodologies focusing on model uncertainty, discusses the corresponding activities of calibration, verification and validation, and examines their applications reported in the AM literature. The extension of current UQ methodologies to additive manufacturing needs to address multi-physics, multi-scale interactions, increasing presence of data-driven models, high cost of manufacturing, and complexity of measurements. The activities that need to be undertaken in order to implement verification, calibration, and validation for AM are discussed. Literature on using the results of UQ activities towards AM process optimization and control (thus supporting maximization of quality and minimization of variability) is also reviewed. Future research needs both in terms of UQ and decision-making in AM are outlined.

scholarly journals An Enabling Open-Source Technology for Development and Prototyping of Production Systems by Applying Digital Twinning

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 21
Author(s):  
Robert Kazała ◽  
Sławomir Luściński ◽  
Paweł Strączyński ◽  
Albena Taneva
Keyword(s):  
Open Source ◽  
Production Systems ◽  
Communication Technologies ◽  
Digital Twin ◽  
Twin System ◽  
Digital Twins ◽  
First Choice ◽  
Automation And Control ◽  
And Control

This article presents the most valuable and applicable open-source tools and communication technologies that may be employed to create models of production processes by applying the concept of Digital Twins. In recent years, many open-source technologies, including tools and protocols, have been developed to create virtual models of production systems. The authors present the evolution and role of the Digital Twin concept as one of the key technologies for implementing the Industry 4.0 paradigm in automation and control. Based on the presented structured review of valuable open-source software dedicated to various phases and tasks that should be realised while creating the whole Digital Twin system, it was demonstrated that the available solutions cover all aspects. However, the dispersion, specialisation, and lack of integration cause this software to usually not be the first choice to implement DT. Therefore, to successfully create full-fledged models of Digital Twins by proceeding with proposed open-source solutions, it is necessary to make additional efforts due to integration requirements.

Linking decision-making research and cancer prevention and control: Important themes.

2005 ◽  
Vol 24 (4, Suppl) ◽  
pp. S106-S110 ◽  
Author(s):  
Kevin D. McCaul ◽  
Ellen Peters ◽  
Wendy Nelson ◽  
Michael Stefanek
Keyword(s):  
Decision Making ◽  
Cancer Prevention ◽  
Prevention And Control ◽  
Cancer Prevention And Control ◽  
And Control

Scham und Autonomie

2012 ◽  
Vol 2012 (1) ◽  
pp. 163-192
Author(s):  
Sonja Rinofner-Kreidl
Keyword(s):  
Decision Making ◽  
Social Dynamics ◽  
Self Esteem ◽  
Self Determination ◽  
Intentional Content ◽  
Conceptual Clarification ◽  
The Social ◽  
Conventional Behavior ◽  
And Control

Autonomy is associated with intellectual self-preservation and self-determination. Shame, on the contrary, bears a loss of approval, self-esteem and control. Being afflicted with shame, we suffer from social dependencies that by no means have been freely chosen. Moreover, undergoing various experiences of shame, our power of reflection turns out to be severly limited owing to emotional embarrassment. In both ways, shame seems to be bound to heteronomy. This situation strongly calls for conceptual clarification. For this purpose, we introduce a threestage model of self-determination which comprises i) autonomy as capability of decision-making relating to given sets of choices, ii) self-commitment in terms of setting and harmonizing goals, and iii) self-realization in compliance with some range of persistently approved goals. Accordingly, the presuppositions and distinctive marks of shame-experiences are made explicit. Within this framework, we explore the intricate relation between autonomy and shame by focusing on two questions: on what conditions could conventional behavior be considered as self-determined? How should one characterize the varying roles of actors that are involved in typical cases of shame-experiences? In this connection, we advance the thesis that the social dynamics of shame turns into ambiguous positions relating to motivation, intentional content,and actors’ roles.

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