Increasing Supply Chain Visibility With Limited Data Availability: Data Assimilation In Discrete Event Simulation

Being able to timely access and share accurate information to all stakeholders that can influence a supply chain is referred to as <i>supply chain visibility</i>. Supply chain visibility is crucial for increasing the resilience of a...

Strategic Use of Data Assimilation for Dynamic Data-Driven Simulation

Dynamic data-driven simulation (DDDS) incorporates real-time measurement data to improve simulation models during model run-time. Data assimilation (DA) methods aim to best approximate model states with imperfect measurements, where particle Filters (PFs) are commonly used with discrete-event simulations. In this paper, we study three critical...

Data assimilation in the minerals industry: Real-time updating of spatial models using online production data

Declining ore grades, extraction at greater depths and longer hauling distances put pressure on maturing mines. Not enough new mines will be commissioned on time to compensate for the resulting shortages. Ore-body replacement rates are relatively low due to a reduced appetite for exploration. Development times are generally increasing and most...

Data Assimilation in Discrete Event Simulations: A Rollback Based Sequential Monte Carlo Approach

Data assimilation is an analysis technique which aims to incorporate measured observations into a dynamic system model in order to produce accurate estimates of the current state variables of the system. Although data assimilation is conventionally applied in continuous system models, it is also a desired ability for its discrete event...