Optimization
Model constraints, objectives and trade-offs to improve planning, resource allocation, throughput and operational decisions.
Industrial Intelligence
Advanced algorithms for difficult industrial decisions.
Some operational problems cannot be solved well with standard software. OBVERA designs computational systems for complex industrial environments, combining mathematical modelling, optimization, Machine Learning and advanced algorithms with real production and engineering data.
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Machine Learning
Identify patterns, similarities and predictive signals in industrial, production and engineering data.
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Advanced Algorithms
Design purpose-built computational methods for problems where generic tools are too slow, rigid or imprecise.
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Computational Geometry
Analyze shapes, dimensions and geometric relationships for engineering, manufacturing, retrieval and similarity applications.
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Production Decision Support
Combine historical production data, geometric similarity and operational constraints to recommend suitable production setups, machine allocation and process parameters.
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Decision-Support Systems
Turn models and algorithms into usable software that supports real decisions in day-to-day operations.
Method
From operational problem to working system.
01
Understand the operation.
We map the decision, constraints, available data, edge cases and business objective.
02
Formalize the problem.
We translate operational reality into a mathematical or computational representation that can be tested.
03
Build and validate.
We develop and compare alternative methods against real data and real operational cases.
04
Productize.
We turn the selected approach into a robust system that can be used in day-to-day operations.
Q.E.D.
Research depth. Operational purpose.
Our research capability exists to solve real problems. Technical rigor matters because the systems we build must work outside a laboratory - with imperfect data, operational constraints and decisions that have real consequences.