Machine Knowledge Software: Key Factors and Best Practices for Market Adoption and Integration of Systems Simulation

This presentation was made at the 2019 NAFEMS World Congress in Quebec Canada

Resource Abstract

Industries are pushed to adopt new technologies in order to address such challenges as efficiency and precision increase, cost and weight reduction, compactness, environmental print, etc. to name a few. A new generation of components and systems is playing an important role in accelerating this transformation. Even though this new technology is promising in terms of both performance and flexibility, its expected market adoption, unfortunately sometimes, gets rejected at the initial machine concept phase.

System simulation is a good alternative to overcome this problem if the underlying simulation models are understood by and accessible to a large majority of users, and if they are easily modifiable according to lab tests, field data, but also from other software. The ultimate goal is to allow users, during the initial steps and proof of concept, to gain knowledge about the actual use of the expected products designed with all the benefits.

We want to avoid having simulation reserved to a very small minority of users with models that take forever to be developed. This is the case with the majority of simulation software on the market.

Therefore, an ideal concept would be based on the development and availability of hybrid simulation component models whose characteristics and performances are thoroughly respected. These components can be selected with all their options and dimensioned from a complete off-the-shelf database. They can then be easily assembled in an animated and interactive simulation environment that allows for manual and/or automated "What-If" type of manipulation.

This presentation explains, by showing convincing case studies of alternative technologies that have emerged in recent years, how the power of simulation tools - (digitalization ...) leveraging knowledge sharing, results’ communication (knowledge sharing capability) and use-based modification of simulation models, made it easy to integrate these technologies into marketed systems.

The concept presented allows for a greater number of actors involved to become quickly familiar with the features of multi-technology machines, even in the subsequent steps of the lifecycle including design, start-up, training, maintenance, etc. In short, these "digital twins", thoroughly reproducing their real counterpart, widely open the door to their reuse for the creation of training platforms and the development of methodologies helping to service these systems.

Document Details

AuthorRemillard. V
Date 18th June 2019
OrganisationFamic Technologies Inc.


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