A simple energy usage toolkit from manufacturing simulation data

• Published in: Journal of cleaner production Vol. 122; pp. 266 - 276
• Main Authors: Wilson, Joel, Arokiam, Alan, Belaidi, Hafid, Ladbrook, John
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 20.05.2016
• Subjects: Computer simulation; Decision making; Discrete-event simulation; Energy conservation; Energy efficiency; Energy modelling; Energy use; Interactive; Management; Mathematical models; Sustainable manufacturing; Sustainable manufacturing; Energy efficiency; Energy modelling; Discrete-event simulation
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2015.11.071

A fundamental problem in the management of energy usage is the inability to clearly predict any possible energy saving opportunities. The cost of both under or overestimating potential returns on investment can be prohibitive to a decision maker. In recent years the simulation of energy usage using existing manufacturing simulation tools has increased in popularity among researchers, but it is decision makers who need to see the benefits of this discipline. This paper proposes an interactive manufacturing energy management toolkit which makes use of existing productivity simulation models for the prediction of energy usage. An interactive Microsoft® Excel® based toolkit is developed to control Lanner's WITNESS® discrete-event simulation software using Microsoft® Visual Basic® for Applications. The toolkit has the ability to predict potential areas where energy saving opportunities can be made within a complex manufacturing line, and is accessible from management presentations and proposals. The interactivity of the toolkit provides an environment which facilitates efficient hypothesis testing. The paper includes an industrial case study where the approach was used to quantify theoretical savings from certain energy usage reduction scenarios within a complex automotive engine manufacturing line. •An interactive manufacturing energy management tool is proposed.•Can predict potential complex manufacturing energy saving opportunities.•Accessible from management presentations and proposals.•Tool Interactivity provides an environment which facilitates hypothesis testing.•An industrial case study shows savings from energy usage reduction scenarios.