Design-OS: A Specification-Driven Framework for Engineering System Design with a Control-Systems Design Case

TL;DR

Design-OS is a structured, specification-driven framework that enhances engineering system design by integrating human and AI collaboration across multiple stages, demonstrated on control systems with open-source and commercial platforms.

Contribution

It introduces a novel, multi-stage workflow that formalizes specifications as shared contracts, enabling traceability and AI integration in physical system design.

Findings

Successfully applied to rotary inverted pendulum platforms

Maintains traceability from concept to implementation

Supports reproducibility with shared artifacts

Abstract

Engineering system design -- whether mechatronic, control, or embedded -- often proceeds in an ad hoc manner, with requirements left implicit and traceability from intent to parameters largely absent. Existing specification-driven and systematic design methods mostly target software, and AI-assisted tools tend to enter the workflow at solution generation rather than at problem framing. Human--AI collaboration in the design of physical systems remains underexplored. This paper presents Design-OS, a lightweight, specification-driven workflow for engineering system design organized in five stages: concept definition, literature survey, conceptual design, requirements definition, and design definition. Specifications serve as the shared contract between human designers and AI agents; each stage produces structured artifacts that maintain traceability and support agent-augmented execution. We position Design-OS relative to requirements-driven design, systematic design frameworks, and AI-assisted design pipelines, and demonstrate it on a control systems design case using two rotary inverted pendulum platforms -- an open-source SimpleFOC reaction wheel and a commercial Quanser Furuta pendulum -- showing how the same specification-driven workflow accommodates fundamentally different implementations. A blank template and the full design-case artifacts are shared in a public repository to support reproducibility and reuse. The workflow makes the design process visible and auditable, and extends specification-driven orchestration of AI from software to physical engineering system design.