Services Solutions · Operations Research & AI Digital Twin

SPG GenOR-Twin

SPG GenOR-Twin is an Operations Research (OR) Digital Twin available as a SaaS operational interface and developer API. It builds a live virtual replica of physical workflows, translating unstructured reports, logs, and sensor alerts into mathematical planning models in real time.

Operations Research Digital Twin layout showing optimized workflow nodes and real-time scheduling graphs

OR / AI · DIGITAL TWIN

Optimization latency

< 3 ms

Model update sync

Real-time

Scheduling improvement

+97%

Capabilities

What this platform does

Each capability is a deployed module — not a feature on a roadmap. Engagements typically begin with a 4-week scoping exercise to confirm fit against your operational data and constraints.

01 / 05

Natural language operational constraint capture

Operational teams communicate in plain language notes, emails, and handover logs. GenOR-Twin parses them to automatically extract and structure mathematical optimization constraints.

02 / 05

Operations research optimization engine

Leverages exact solvers and meta-heuristics to dynamically solve Mixed-Integer Linear Programming (MILP), routing, and resource scheduling models based on live constraint updates.

03 / 05

Real-time digital twin synchronization

Injects physical updates — asset breakdowns, crew changes, or arrival delays — directly into the active solver within milliseconds, maintaining live operational sync.

04 / 05

Adaptive simulation & risk testing

Runs parallel scenarios to simulate operational disruptions, evaluating risk thresholds and proposing mitigation strategies before physical execution.

05 / 05

Cross-domain operational scalability

Validated across multiple heavy-duty operations including railway dispatch, harbor operations, manufacturing scheduling, and multi-hub logistics routing.