Level of automation (LOA) in aerospace composite manufacturing: Present status and future directions towards industry 4.0

2022 ◽  
Vol 62 ◽  
pp. 44-61
Author(s):  
Deepesh Jayasekara ◽  
Nai Yeen Gavin Lai ◽  
Kok-Hoong Wong ◽  
Kulwant Pawar ◽  
Yingdan Zhu
2000 ◽  
Vol 7 (5) ◽  
pp. 423-428 ◽  
Author(s):  
Adnan I. Qureshi ◽  
Andrew J. Ringer ◽  
M. Fareed ◽  
K. Suri ◽  
Lee R. Guterman ◽  
...  

2018 ◽  
Vol 58 (1) ◽  
pp. 41-52 ◽  
Author(s):  
Péter Bucsky

Abstract The freight transport sector is a low profit and high competition business and therefore has less ability to invest in research and development in the field of autonomous vehicles (AV) than the private car industry. There are already different levels of automation technologies in the transport industry, but most of these are serving niche demands and answers have yet to be found about whether it would be worthwhile to industrialise these technologies. New innovations from different fields are constantly changing the freight traffic industry but these are less disruptive than on other markets. The aim of this article is to show the current state of development of freight traffic with regards to AVs and analyse which future directions of development might be viable. The level of automation is very different in the case of different transport modes and most probably the technology will favour road transport over other, less environmentally harmful traffic modes.


2014 ◽  
Vol 47 (2) ◽  
pp. 59
Author(s):  
R. Easwaran ◽  
A. Raja ◽  
G. Ravichandran ◽  
G. Buvanashekaran

ChemInform ◽  
2010 ◽  
Vol 27 (26) ◽  
pp. no-no
Author(s):  
D. M. WHITFIELD ◽  
S. P. DOUGLAS

1996 ◽  
Vol 3 (2) ◽  
pp. 83-97 ◽  
Author(s):  
Tadashi Matsuda ◽  
Toshiro Terachi ◽  
Osamu Yoshida

Author(s):  
Giacomo Büchi ◽  
Monica Cugno ◽  
Rebecca Castagnoli

This paper analyses the role of cost differentials in the fourth industrial revolution. It uses a literature review in order to identify origins, definitions, enabling technologies and changes in company productivity. Research results show how certain Industry 4.0 enabling technologies help obtain better economic results in mass production and others that support new production models in mass production: mass customization and mass personalization. This paper is of a theoretical nature and identifies certain reflections concerning Industry 4.0’s role in managerial literature by providing interesting lines to be developed in future directions of research.


Author(s):  
ELDON L. CHRISTENSEN ◽  
LEONARD W. GREY ◽  
JAMES D. NAVRATIL ◽  
WALLACE W. SCHULZ

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shailendra Kumar ◽  
Mohammad Asjad ◽  
Mohd. Suhaib

Purpose This paper aims to put forward a labelling system capable of reflecting the level of different Industry 4.0 (I4.0)features present in a manufacturing system and further propose a comparative index to collectively estimate and compare the system automation level. Design/methodology/approach Data for the empirical study were collected from interactions with the practising managers and experts. A relationship among the six I4.0 features is developed with fuzzy cognitive maps. Findings The paper proposed a simple and easy-to-understand labelling system for I4.0 systems, which indicates the automation level in each of six dimensions of any manufacturing system. The system is further strengthened by a proposed automation comparative index (ACI), which collectively reflects the automation level on a scale of “0” to “1”. Thus, the labelling system and parameter could help in comparing the level of automation in the manufacturing system and further decision-making. Research limitations/implications Only seven industrial sectors are illustrated in the paper, but the proposed concept of the classification scheme and ACI find their applicability on a large spectrum of industries; thus, the concept can be extended to other industrial sectors. Furthermore, a threshold value of ACI is a differentiator between a I4.0 and other automated systems. Both aspects have the scope of further work. Practical implications The way and pace by which the industrial world takes forward the concept of I4.0, soon it will need a labelling system and a parameter to assess the automation level of any automated system. The scheme assesses the automation level present in a manufacturing system. It will also estimate the level of the presence of each of all six attributes of an I4.0 system. Both labelling system and ACI will be the practical tools in the hands of the practising managers to help compare, identify the thrust areas and make decisions accordingly. Originality/value To the best of the authors’ knowledge, this is the first study of its kind that proposed the labelling system and automation comparison index for I4.0 systems.


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