The Augmented Supply Chain

Massimo Merlino; Ilze Sproge

doi:10.1016/j.proeng.2017.01.053

The Augmented Supply Chain

Massimo Merlino^*
, Ilze Sproge

^*Šī darba korespondējošais autors

Management Engineering Faculty University of the Republic of San Marino
Transport and Telecommunication Institute (TSI)

Zinātniskās darbības rezultāts: Devums žurnālam › Konferences zinātniskais raksts › koleģiāli recenzēts

81 Atsauces (Scopus)

Kopsavilkums

Supply Chain processes must augment and change with massive injection of new technologies, robotics, artificial intelligence, big data approach, and contemporarily become more sustainable, considering the growing environmental challenges. This paper explores the main technological changes and the most advanced cases in sustainable Supply Chain. From Materials Handling to Production and Distribution, big data and robotics will change conditions and push further efficiency and customer service levels. After a general overview of the present and future trends in these areas, some practical case and experiences will be quoted.

Oriģinālvaloda	Angļu
Lapas (no-līdz)	308-318
Lapu skaits	11
Žurnāls	Procedia Engineering
Sējums	178
DOIs	https://doi.org/10.1016/j.proeng.2017.01.053
Publikācijas statuss	Publicēts - 2017
Ārēji publicēts	Jā
Pasākums	16th International Scientific Conference Reliability and Statistics in Transportation and Communication, RelStat 2016 - Riga, Latvija Ilgums: 19 okt. 2016 → 22 okt. 2016

ANO IAM

Šis izpildes rezultāts palīdz sasniegt šādus ANO ilgtspējīgas attīstības mērķus (IAM)

9. IAM — Rūpniecība, Inovācija un Infrastruktūra
12. IAM — Atbildīgs Patēriņš un Ražošana

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title = "The Augmented Supply Chain",

abstract = "Supply Chain processes must augment and change with massive injection of new technologies, robotics, artificial intelligence, big data approach, and contemporarily become more sustainable, considering the growing environmental challenges. This paper explores the main technological changes and the most advanced cases in sustainable Supply Chain. From Materials Handling to Production and Distribution, big data and robotics will change conditions and push further efficiency and customer service levels. After a general overview of the present and future trends in these areas, some practical case and experiences will be quoted.",

keywords = "artificial intelligence, big data, robotics, supply chain",

author = "Massimo Merlino and Ilze Sproge",

note = "Publisher Copyright: {\textcopyright} 2017 The Authors.; 16th International Scientific Conference Reliability and Statistics in Transportation and Communication, RelStat 2016 ; Conference date: 19-10-2016 Through 22-10-2016",

year = "2017",

doi = "10.1016/j.proeng.2017.01.053",

language = "English",

volume = "178",

pages = "308--318",

journal = "Procedia Engineering",

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AU - Merlino, Massimo

AU - Sproge, Ilze

PY - 2017

Y1 - 2017

N2 - Supply Chain processes must augment and change with massive injection of new technologies, robotics, artificial intelligence, big data approach, and contemporarily become more sustainable, considering the growing environmental challenges. This paper explores the main technological changes and the most advanced cases in sustainable Supply Chain. From Materials Handling to Production and Distribution, big data and robotics will change conditions and push further efficiency and customer service levels. After a general overview of the present and future trends in these areas, some practical case and experiences will be quoted.

AB - Supply Chain processes must augment and change with massive injection of new technologies, robotics, artificial intelligence, big data approach, and contemporarily become more sustainable, considering the growing environmental challenges. This paper explores the main technological changes and the most advanced cases in sustainable Supply Chain. From Materials Handling to Production and Distribution, big data and robotics will change conditions and push further efficiency and customer service levels. After a general overview of the present and future trends in these areas, some practical case and experiences will be quoted.

KW - artificial intelligence

KW - big data

KW - robotics

KW - supply chain

UR - https://www.scopus.com/pages/publications/85025612290

U2 - 10.1016/j.proeng.2017.01.053

DO - 10.1016/j.proeng.2017.01.053

M3 - Conference article

AN - SCOPUS:85025612290

SN - 1877-7058

VL - 178

SP - 308

EP - 318

JO - Procedia Engineering

JF - Procedia Engineering

T2 - 16th International Scientific Conference Reliability and Statistics in Transportation and Communication, RelStat 2016

Y2 - 19 October 2016 through 22 October 2016

ER -

The Augmented Supply Chain

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ANO IAM

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