Multi-resolution simulation models of a manufacturing system, such as a virtual factory, coupled with simulation-based analytics offer exciting opportunities to manufacturers to exploit the increasing availability of data from their corresponding real factory at different hierarchical levels. A virtual factory simulation model can be maintained as a live representation of the real factory and used to highly accelerate learning from data using simulation-based analytics applications.
While large corporations are already embarking on simulation-based analytics initiatives, small and medium enterprises (SMEs) may find it challenging to set up a virtual factory simulation model and analytics applications due to barriers of expertise and investments in hardware and software. This paper proposes a shared infrastructure for a virtual factory simulation-based analytics that can be employed by SMEs.
There is a multitude of efforts for developing and deploying standalone applications based on the four technologies, namely AI, analytics, mathematical optimization, and simulation. This paper proposes an infrastructure for an application that brings together simulation and analytics technologies for supporting manufacturing operations management and machine level decisions. Simulation applications can generate credible outputs for a range of what-if scenarios. Such use of simulation models to generate data, which is then analyzed by data-driven analytics applications, has been referred to as model simulation-based analytics.
Simulation-based analytics framework for a virtual factory