Machine-integrated dynamic functions typically rely only on the machine controller data of the specific machine.
Hopper uses not only high-frequency machine data from all connected machines (not only one), but also contextual information such as raw material properties of each batch and environmental conditions, etc.
Hopper enables transfer learning, since it is compatible with various types and vendors of injection molding machines and can combine and compare data across entire machine fleet.

Machine integrated functions for injection molding machines: Switch-over point + Holding pressure phase

Hopper: Optimized profiles for plastification, injection, post-preassure phases, hence not only shifting the Switch-over point. A Recommendation can be up to 70 parameters (more than machine integrated functions which are targeting weight or volume constancy shot by shot). Hopper considers minimum process change, avoiding “jumping around in the allowed process window”.

Machine-integrated dynamic functions are targeting constant shot weight/volume under variation of viscosity or density (both is hard to handle).

Hopper as on-top software tool: Combined Cycle-time + Scrap-likelihood (good-part-ratio per hour as target of optimization) of various scrap reasons, like dimensional deviations, surface defects, flow lines and mechanical properties.

Machine integrated functions: act within running cycle correction

Hopper: act after completion of running cycle meaning next cycle or later

Machine integrated functions: during running production avoiding in-process scrap caused by variation of shot weight.

Hopper:
-Faster mold change-over due to proposals for “Shot 1” already fine-tuned for current raw material batch + climate avoiding manual fine-tuning
-In-process scrap-avoidance based on flucutations of process or variation of boundary conditions (climate / dryer / material batch)
-Compliance to check if parts are produced within validated parameter windows