Abstract
<b>Purpose</b>
This paper reports on the experimentation of an integrated manufacturing and building model to improve energy efficiency. Traditionally, manufacturing and building-facilities engineers work independently, with their own performance objectives, methods and software support. However, with progresses in resource reduction, advances have become more challenging. Further opportunities for energy efficiency require an expansion of scope across the functional boundaries of facility, utility and manufacturing assets.
<b>Design/methodology/approach</b>
The design of methods that provide guidance on factory modelling is inductive. The literature review outlines techniques for the simulation of energy efficiency in manufacturing, utility and facility assets. It demonstrates that detailed guidance for modelling across these domains is sparse. Therefore, five experiments are undertaken in an integrated manufacturing, utility and facility simulation software IES < VE > . These evaluate the impact of time-step granularity on the modelling of a paint shop process.
<b>Findings</b>
Experimentation demonstrates that time-step granularity can have a significant impact on simulation model results quality. Linear deterioration in results can be assumed from time intervals of 10 minutes and beyond. Therefore, an appropriate logging interval, and time-step granularity should be chosen during the data composition process. Time-step granularity is vital factor in the modelling process, impacting the quality of simulation results produced.
<b>Practical implications</b>
This work supports progress towards sustainable factories by understanding the impact of time-step granularity on data composition, modelling, and on the quality of simulation results. Better understanding of this granularity factor will guide engineers to use an appropriate level of data and understand the impact of the choices they are making.
<b>Originality/value</b>
This paper reports on the use of simulation modelling tool that links manufacturing, utilities and facilities domains, enabling their joint analysis to reduce factory resource consumption. Currently, there are few available tools to link these areas together; hence, there is little or no understanding of how such combined factory analysis should be conducted to assess and reduce factory resource consumption.