Integrated Ontologies in Support of Factory Systems Design

Zhang, J.; Agyapong-Kodua, Kwabena

doi:10.1016/j.ifacol.2015.06.398

Cited by 4 publications

(1 citation statement)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The need to link time and cost is recognized by Santana 24 who presented a mathematical model for capacity management based on different costing models in order to enhance operation and financial efficiency through capacity optimization. Zhang 25 discuses integrated ontologies for linking different components of the factory system (product, process, resource and cost) and identifies future work requiring connection with a cost control module to make design decisions in next generation factory systems. Tierney 26 describes a scalable cost modelling architecture for determining the costeffectiveness of aircraft joining technologies.…”

Section: Cost Modellingmentioning

confidence: 99%

Steps towards a Connected Digital Factory Cost Model

Tierney¹,

Higgins²,

Higgins³

et al. 2023

SAE Technical Paper Series

View full text Add to dashboard Cite

<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>

show abstract

Section: Cost Modellingmentioning

confidence: 99%