Representing financial data streams in digital simulations to support data flow design for a future Digital Twin

A. Murphy*, C. Taylor, C. Acheson, J. Butterfield, Y. Jin, P. Higgins, R. Collins, C. Higgins

*Corresponding author for this work

Research output: Contribution to journalArticle

2 Citations (Scopus)
10 Downloads (Pure)

Abstract

Discrete Event Simulations may be used to forecast detailed production system behaviour under future conditions and support better informed decision making. However, data beyond production metrics, e.g. financial information, is also necessary for most significant decisions. Herein a modelling approach is proposed and demonstrated based on simulating both production and financial transactions. The contribution of this paper is to represent the base production events as well as additional events which trigger financial transactions. The method is demonstrated for an idealised production business, employing Discrete Event Simulation and examining the impact of system labour arrangements on the business cash flow with a variable demand based on a normal probability distribution function (with distinct means and variances for each product). Based on the financial transactions a representation of a detail commercial scenario may be modelled alongside the production events. The presented studies identify the potential sensitivity of analysis to the volume and timing of transactions on accumulated accounting metrics such as profit. Additionally the paper illustrates how such a modelling approach can be used to characterise the system and assess specific control strategies when both production and finance data streams are available.

Original languageEnglish
Article number101853
JournalRobotics and Computer-Integrated Manufacturing
Volume61
Early online date05 Sep 2019
DOIs
Publication statusPublished - 01 Feb 2020

Keywords

  • Discrete Event Simulation
  • Factory Digital Twin
  • Financial metrics
  • Industrial Internet of Things
  • Labour resource planning
  • Production demand
  • Real time forecasting

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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