Supply Chain Concepts & Challenges in Autonomous Systems

In the context of modern engineering and technology industries, a supply chain refers to the network of organisations, resources, and processes involved in the design, procurement, manufacturing, and delivery of a product or system ^[1]. For autonomous systems, the supply chain includes everything from electronic components (sensors, chips, batteries) and mechanical parts (motors, frames) to software dependencies and data provisioning. Since the autonomous systems are multi-disciplinary, a typical supply chain is global. The components and services are sourced globally, making the supply chain geographically distributed and highly interdependent. Effective management ensures that every subsystem arrives on time, meets specifications, and can be integrated seamlessly ^[2]. The main processes within an autonomous systems supply chain include:

• Procurement: Identifying and acquiring necessary parts and raw materials.
• Production Planning: Scheduling and coordinating the assembly of subsystems.
• Quality Assurance (QA): Verifying compliance with technical and safety standards.
• Logistics: Transportation, warehousing, and inventory management.
• Aftermarket Services: Maintenance, software updates, and replacement part logistics.

In highly complex domains such as aerospace and automotive, these processes must align with standards such as AS9100, ISO 9001, and IATF 16949 for quality assurance and traceability.

Autonomous systems depend heavily on specialised components such as LiDARs, high-density batteries, and embedded processors. Many of these have limited global suppliers, creating vulnerability to shortages or geopolitical disruptions ^[3].