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An eco-approach to optimise efficiency and productivity of a hydraulic excavator

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journal contribution
posted on 2015-09-03, 08:44 authored by Felix Ng, Jennifer HardingJennifer Harding, Jacqui Glass
The depletion of fossil fuel and the ozone layer has been a global concern for decades. The International Organization for Standardization has published earth-moving machine sustainability standards for the industry to provide information to satisfy their customers' interests in their construction projects. Furthermore, steeply rising energy prices and the collapse of financial institutions in recent years have sparked demand for ways to improve individual energy efficiency. Original equipment manufacturers of earth-moving machines must address sustainability requirements, as well as remaining competitive and they aim to do this by improving machine efficiency, adopting advanced fleet management systems, providing operator training courses etc. Clearly high fuel efficiency is important to reduce depletion of fossil fuels and damage to the environment. However, the objectives of achieving the highest possible productivity (m3/h) and improving fuel efficiency (kg/l) are often considered separately. Many equations have been formulated to measure a machine's highest possible productivity level, yet there is a lack of consensus between academia and industry sources on the terms which should be considered within such equations. Perhaps more importantly, none have explicitly considered the relationship between fuel efficiency and productivity, and only scant consideration is given to the role of operators in achieving optimum productivity for fuel efficiency. Therefore, this paper presents an eco-approach to enable operators to achieve optimal productivity for fuel efficiency of a hydraulic excavator. Hydraulic excavators are primarily designed for excavating with a bucket. Their ease of use, versatility and high productivity have won them major segments of the construction equipment market, therefore the focus on hydraulic exactors in this paper is justifiable. The research presented in this paper has adopted an applied research methodology to collect measurable, empirical evidence through scientific experiments in order to test several hypotheses that focus on the reduction of GHG produced by construction machines. The research has examined two variables, engine speed and bucket cut depth, to determine their effects on productivity and fuel efficiency of a hydraulic excavator. The experimental results show that the combinations of various engine speed settings and bucket cut depths can increase productivity by 30% and cut greenhouse gas emissions by 24%, consequentially moving 62% more spoil every hour for every litre of fuel consumed. The results also suggest that identifying the correct bucket cut depth is the key to significant improvements in productivity and reduction in greenhouse gas emissions. The paper therefore concludes that adoption of an appropriate construction machine operation style can help reduce the greenhouse gas emissions associated with hydraulic excavators. Hence, educating operators to select the right engine speed and bucket cut depth is a cost effective approach to lowering the operational costs and carbon emissions through lower fuel consumption and greater machine longevity.


This work was sponsored by the Engineering and Physical Sciences Research Council is gratefully acknowledged (EPSRC Grant EP/G037272/1).



  • Mechanical, Electrical and Manufacturing Engineering

Published in

Journal of Cleaner Production


NG, F., HARDING, J.A. and GLASS, J., 2016. An eco-approach to optimise efficiency and productivity of a hydraulic excavator. Journal of Cleaner Production, 112(5), pp.3966-3976.


© 2015 The Authors. Published by Elsevier Ltd.


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This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

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This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/




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