EconPapers    
Economics at your fingertips  
 

Logistics 4.0 Energy Modelling

Megashnee Munsamy, Arnesh Telukdarie and Pavitra Dhamija
Additional contact information
Megashnee Munsamy: Mangosuthu University of Technology, Umlazi, South Africa
Arnesh Telukdarie: Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa
Pavitra Dhamija: Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa

International Journal of Business Analytics (IJBAN), 2020, vol. 7, issue 1, 98-121

Abstract: Logistics activities are significant energy consumers and known contributors to GHG emissions, hence optimisation of logistics energy demand is of critical importance. The onset of the fourth Industrial revolution delivers significant technological opportunities for logistics optimisation with additional benefits in logistics energy optimisation. This research propositions a business process centric logistics model based on Industry 4.0. A Logistics 4.0 architecture is developed comprising Industry 4.0 technologies and associated enablers. The Industry 4.0 architecture components are validated by conducting a Systematic Literature Review on Industry 4.0 and logistics. Applying the validated Logistics 4.0 architecture to a cyber physical logistics energy model, based on the digitalisation of business processes, a comprehensive simulation is developed identified as the Logistic 4.0 Energy Model. The model simulates the technological impact of Industry 4.0 on a logistics network. The model generates energy and CO2 emission values for “as-is” and “to-be” Industry 4.0 scenarios.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 018/IJBAN.2020010106 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jban00:v:7:y:2020:i:1:p:98-121

Access Statistics for this article

International Journal of Business Analytics (IJBAN) is currently edited by John Wang

More articles in International Journal of Business Analytics (IJBAN) from IGI Global
Bibliographic data for series maintained by Journal Editor ().

 
Page updated 2025-03-19
Handle: RePEc:igg:jban00:v:7:y:2020:i:1:p:98-121