Literature DB >> 35957390

A Primer on the Factories of the Future.

Noble Anumbe1,2, Clint Saidy1,2, Ramy Harik1,2.   

Abstract

In a dynamic and rapidly changing world, customers' often conflicting demands have continued to evolve, outstripping the ability of the traditional factory to address modern-day production challenges. To fix these challenges, several manufacturing paradigms have been proposed. Some of these have monikers such as the smart factory, intelligent factory, digital factory, and cloud-based factory. Due to a lack of consensus on general nomenclature, the term Factory of the Future (or Future Factory) has been used in this paper as a collective euphemism for these paradigms. The Factory of the Future constitutes a creative convergence of multiple technologies, techniques, and capabilities that represent a significant change in current production capabilities, models, and practices. Using the semi-narrative research methodology in concert with the snowballing approach, the authors reviewed the open literature to understand the organizing principles behind the most common smart manufacturing paradigms with a view to developing a creative reference that articulates their shared characteristics and features under a collective lingua franca, viz., Factory of the Future. Serving as a review article and a reference monograph, the paper details the meanings, characteristics, technological framework, and applications of the modern factory and its various connotations. Amongst other objectives, it characterizes the next-generation factory and provides an overview of reference architectures/models that guide their structured development and deployment. Three advanced communication technologies capable of advancing the goals of the Factory of the Future and rapidly scaling advancements in the field are discussed. It was established that next-generation factories would be data rich environments. The realization of their ultimate value would depend on the ability of stakeholders to develop the appropriate infrastructure to extract, store, and process data to support decision making and process optimization.

Entities:  

Keywords:  Industry 4.0; Internet of Things; advanced manufacturing; artificial intelligence; cyber manufacturing; cyber physical systems; data driven manufacturing; intelligent manufacturing; smart factory

Mesh:

Year:  2022        PMID: 35957390      PMCID: PMC9370931          DOI: 10.3390/s22155834

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.847


  19 in total

Review 1.  Developing killer apps for industrial augmented reality.

Authors:  Nassir A Navab
Journal:  IEEE Comput Graph Appl       Date:  2004 May-Jun       Impact factor: 2.088

Review 2.  How to grow a mind: statistics, structure, and abstraction.

Authors:  Joshua B Tenenbaum; Charles Kemp; Thomas L Griffiths; Noah D Goodman
Journal:  Science       Date:  2011-03-11       Impact factor: 47.728

Review 3.  Deep learning.

Authors:  Yann LeCun; Yoshua Bengio; Geoffrey Hinton
Journal:  Nature       Date:  2015-05-28       Impact factor: 49.962

4.  Visual computing as a key enabling technology for Industrie 4.0 and Industrial Internet.

Authors:  Jorge Posada; Carlos Toro; Iñigo Barandiaran; David Oyarzun; Didier Stricker; Raffaele de Amicis; Eduardo B Pinto; Peter Eisert; Jurgen Döllner; Ivan Vallarino
Journal:  IEEE Comput Graph Appl       Date:  2015 Mar-Apr       Impact factor: 2.088

5.  Smart manufacturing must embrace big data.

Authors:  Andrew Kusiak
Journal:  Nature       Date:  2017-04-05       Impact factor: 49.962

6.  Healthcare Data Gateways: Found Healthcare Intelligence on Blockchain with Novel Privacy Risk Control.

Authors:  Xiao Yue; Huiju Wang; Dawei Jin; Mingqiang Li; Wei Jiang
Journal:  J Med Syst       Date:  2016-08-26       Impact factor: 4.460

7.  A Survey of the Advancing Use and Development of Machine Learning in Smart Manufacturing.

Authors:  Michael Sharp; Ronay Ak; Thomas Hedberg
Journal:  J Manuf Syst       Date:  2018       Impact factor: 8.633

8.  SYMBALS: A Systematic Review Methodology Blending Active Learning and Snowballing.

Authors:  Max van Haastrecht; Injy Sarhan; Bilge Yigit Ozkan; Matthieu Brinkhuis; Marco Spruit
Journal:  Front Res Metr Anal       Date:  2021-05-28

9.  A Fog Computing and Cloudlet Based Augmented Reality System for the Industry 4.0 Shipyard.

Authors:  Tiago M Fernández-Caramés; Paula Fraga-Lamas; Manuel Suárez-Albela; Miguel Vilar-Montesinos
Journal:  Sensors (Basel)       Date:  2018-06-02       Impact factor: 3.576

10.  Automated Design and Integration of Asset Administration Shells in Components of Industry 4.0.

Authors:  Jakub Arm; Tomas Benesl; Petr Marcon; Zdenek Bradac; Tizian Schröder; Alexander Belyaev; Thomas Werner; Vlastimil Braun; Pavel Kamensky; Frantisek Zezulka; Christian Diedrich; Premysl Dohnal
Journal:  Sensors (Basel)       Date:  2021-03-12       Impact factor: 3.576

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