<div class="section abstract"><div class="htmlview paragraph">Digital transformation is at the forefront of manufacturing considerations, but
often excludes discrete event simulation and cost modelling capabilities,
meaning digital twin capabilities are in their infancy. As cost and time are
critical metrics for manufacturing companies it is vital the associated tools
become a connected digital capability. The aim is to digitize cost modelling
functionality and its associated data requirements in order to couple cost
analysis with digital factory simulation. The vast amount of data existing in
today’s industry alongside the standardization of manufacturing processes has
paved the way for a ‘data first’ cost and discrete event simulation environment
that is required to facilitate the automated model building capabilities
required to seamlessly integrate the digital twin within existing manufacturing
environments.</div><div class="htmlview paragraph">An ISA-95 based architecture is introduced where phases within a cost modelling
and simulation workflow are treated as a series of interconnected modules:
process mapping (including production layout definition); data collection and
retrieval (resource costs, equipment costs, labour costs, learning rates,
process/activity times etc.); network and critical path analysis; cost
evaluation; cost optimisation (bottleneck identification, production
configuration); simulation model build; cost reporting (dashboard visualisation,
KPIs, trade-offs). Different phases are linked to one another to enable
automated cost and capacity analysis. Leveraging data in this manner enables the
updating of standard operating procedures and learning rates in order to better
understand manufacturing cost implications, such as actual cost versus
forecasted, and to incorporate cost implications into scheduling and planning
decisions.</div><div class="htmlview paragraph">Two different case studies are presented to highlight different applications of
the proposed architecture. The first shows it can be used within a feasibility
study to benchmark novel robotic joining techniques against traditional riveting
of stiffened aero structures.</div><div class="htmlview paragraph">In the second case study discrete event digital factory simulations are used to
supply important production metrics (process times, wait times, resource
utilisation) to the cost model to provide ‘real-time’ cost modelling. This
enables both time and cost to be used for more informed decision making within
an ever demanding manufacturing landscape. In addition, this approach will add
value to simulation processes by enabling simulation engineers to focus on value
adding activities instead of time consuming model builds, data gathering and
model iterations.</div></div>
