Sustainability through the Digitalization of Industrial Machines: Complementary Factors of Fuel Consumption and Productivity for Forklifts with Sensors

Natallia Pashkevich, Darek Haftor, Mikael Karlsson and Soumitra Chowdhury
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Natallia Pashkevich: School of Social Sciences, Södertörn University, 141 89 Huddinge, Sweden
Darek Haftor: Department of Informatics and Media, Uppsala University, 751 20 Uppsala, Sweden
Mikael Karlsson: Research Manager, Bestwood AB, 172 75 Sundbyberg, Sweden
Soumitra Chowdhury: Department of Informatics, Linnaeus University, 351 95 Växjö, Sweden

Sustainability, 2019, vol. 11, issue 23, 1-21

Abstract: Increasing the fuel efficiency of industrial machines through digitalization can enable the transport and logistics sector to overcome challenges such as low productivity growth and increasing CO 2 emissions. Modern digitalized machines with embedded sensors that collect and transmit operational data have opened up new avenues for the identification of more efficient machine use. While existing studies of industrial machines have mostly focused on one or a few conditioning factors at a time, this study took a complementary approach, using a large set of known factors that simultaneously conditioned both the fuel consumption and productivity of medium-range forklifts ( n = 285) that operated in a natural industrial setting for one full year. The results confirm the importance of a set of factors, including aspects related to the vehicles’ travels, drivers, operations, workload spectra, and contextual factors, such as industry and country. As a novel contribution, this study shows that the key conditioning factors interact with each other in a non-linear and non-additive manner. This means that addressing one factor at a time might not provide optimal fuel consumption, and instead all factors need to be addressed simultaneously as a system.

Keywords: digitalization; complementarities; sustainability; fuel consumption; heavy-duty equipment; productivity; sensor data (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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