Manufacturing

Manufacturing

Lead: fortiss

Value-proposition:

The Manufacturing use-case, led by fortiss, focuses on the use of CODECO to manage fleets of Automated Guided Vehicles in a decentralised way by considering context-awareness, and network softwarization.

The use-case is being deployed in the fortiss IIoT Lab, and has as value-proposition to increase AGV autonomy via decentralised control, which is feasible with the assistance of CODECO.

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Actors
:
AGVs
(far Edge nodes) – mobile robots with different sensors (e.g., cameras, environmental sensors)
User
: user DEV, developer willing to deploy the CODECO AGV App; user Operator, human operators, and respective terminals, remotely assisting AGVs.
AGV fleet Controller
node.


Roles:
Deployment of micro-services in an AGV fleet:
a user (DEV, developer) wants to deploy a new CODECO offered application in UC5 across an AGV fleet and wants also to manage its application workload with K8s/CODECO.
The user (DEV) shall be able to observe the existing cluster via a CODECO dashboard (9), and be able to make initial adjustments, if required (9).


AGV Fleet control – Resilient infrastructure:
This user journey relates with the runtime management of the CODECO AGV Apps. The aim is to assist AGVs in autonomous navigation on indoor, blocked spaces. Key challenges concern energy optimization and support of intermittent connectivity. ICT stakeholders relevant for this use-case are mobile communications, Edge-Cloud providers.
A summary of the business impact is as follows:
The P5 value proposition (VP) canvas is provided in . The application of CODECO to the context of AGV fleet decentralized control has as customer segments the CODECO target groups DEV (developers), ICT (large industry and SMEs) and AR (Academia and Research). The targeted vertical domains are Manufacturing and Logistics, which correspond to domains where there is an increasing growth in the need of automation and cognitive processes to improve the overall operations in critical environments. With the integration of Industrial IoT and ML, these sectors are experiencing a major change towards decentralisation, as observable in the concept of Manufacturing as a Service (MaaS).

The proposed solution in this use-case consists of CODECO and of a set of AGV fleet Apps to assist the deployment of the use-case, and to play with CODECO components. The key innovation aspects in UC5 relate with the use of context-awareness and behaviour estimation to provide a higher degree of flexibility to the overall system, thus allowing control of AGVs to be handled in a decentralized way, expected to bring benefits in large-scale environments.
In terms of performance, the application of CODECO in UC5 is expected to improve scalability, resilience, and availability in comparison to K8s, adding also novel support in mobile environments.