English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

High complexity of production processes results in more frequent use of computer systems for their modeling and simulation. Process modeling helps to find optimal solution, verify some assumptions before implementation and eliminate errors. In practice, modeling of production processes concerns two areas: hard modeling (based on differential equations of mathematical physics) and soft (based on existing data). In the paper the possibility of synergistic connection of these two approaches was indicated: it means hard modeling support based on the tools used in soft modeling. It aims at significant reducing the time in order to obtain final results with the use of hard modeling. Some test were carried out in the Calibrate module of NovaFlow&Solid (NF&S) simulation system in the frame of thermal analysis (ATAS-cup). The authors tested output values forecasting in NF&S system (solidification time) on the basis of variable parameters of the thermal model (heat conduction, specific heat, density). Collected data was used as an input to prepare soft model with the use of MLP (Multi-Layer Perceptron) neural network regression model. The approach described above enable to reduce the time of production process modeling with use of hard modeling and should encourage production companies to use it

Synergy of modeling processes in the area of soft and hard modeling