Challenge
Choosing methods before goals?
Analysis methods are often fixed before the phenomenon and the decision are clear.
Technology
Physics simulation and real data,
for field-grade validation.
Listing methods is not the goal. We select and implement techniques around what can be built and what can be validated.
KIPtech
KIPtech starts from the goal.
We combine particle methods, robot simulation and AI surrogates to match the target phenomenon.
Methods chosen by requirement
We combine particle methods, continuum analysis, rigid-body and robot simulation, AI surrogates and real-data correction according to the phenomenon and validation goal. Methods are means, not ends.
Real-to-Sim modeling
We convert real equipment and objects into simulation from CAD, photos, videos, dimensions and logs. Without CAD, we start from simplified models and refine against measured data.
Robot / machine simulation
We validate reachable range, interference and motion conditions for robot arms, jigs, conveyors and dedicated machines — checking motion sequences and cycle times before machine tests.
Sim-to-Real validation
Simulation results are returned to machine conditions, robot motions and equipment design. Success and failure conditions found in simulation become material for deployment decisions.
Particle methods and physics simulation
We reproduce fluids, snow, sand, powders, viscous materials and deformation in computation.
SPH / DEM / FEM / MPM
We select and combine numerical methods according to the target phenomenon — fluids, granular media, continua, fracture and large deformation.
Multi-material interaction R&D
We are conducting research and development on computational methods for multi-material interaction. The detailed formulation is currently confidential.
AI surrogate acceleration
Approximate models trained on costly simulation results accelerate condition search and repeated validation.
Hybrid correction
Physics models, constraints and measurements reduce physically invalid AI outputs.
Real-data validation
Accuracy depends on conditions and data. We define the applicable range through PoCs and joint validation.