How MaaSAI Works

This page follows a single manufacturing job through the MaaSAI platform, so that readers without a technical background can see what each of the 23 MaaSAI solutions is for and how they fit together. The companies, quantities and deadlines used here are fictional and only illustrate the flow.

The walkthrough has ten stages, in this order: publish, discover and rank, negotiate, contract, collaborate, exchange data, operate and monitor, plan, simulate, and assess end of life.

Note

This walkthrough is an illustrative example of how the solutions are designed to work together, based on deliverables D5.1, D6.1, D8.1, D10.1 and D12.1. It is not a description of a specific deployment or of the status of a release. The individual solution pages give the details of each solution.

The Cast

Role	Example (fictional)	What they want
MaaS Provider	Acme Manufacturing	Sell its spare machining capacity as on-demand services.
MaaS Consumer	Nova Products	Get a batch of parts made on demand, without owning the machines.
Operators (provider side)	Acme’s shop-floor team	Keep the equipment healthy and the job on track.
Software agents	MaaS Consumer Agent (MCA) and MaaS Provider Agent (MPA)	Negotiate on behalf of Nova and Acme. Each company’s orchestrator agent deploys them for each request (D6.1).

1. Publish: Acme Offers Its Spare Capacity

Acme has a CNC line that sits idle two days a week and wants to offer that capacity as a service. Its user registers in the Cloud MaaS Marketplace (CMM), the organisation is validated as a provider, and the resources are published through a form built from the catalogue structure (D6.1). The Data Integrator (DI) brings data on Acme’s machines and their availability from its ERP/MES into its EDGE Data Storage (DS). The MaaS Dynamic Catalogue (MDC) maps the description onto the shared MaaS ontology, and the service becomes discoverable in the marketplace.

Solutions involved: Cloud MaaS Marketplace (CMM), MaaS Dynamic Catalogue (MDC), Data Integrator (DI), EDGE Data Storage (DS)

2. Discover and Rank: Nova Looks for a Provider

Nova needs 5,000 precision parts in three weeks. In the CMM it creates an order request describing the product, quantity, quality and lead time. The CMM retrieves the matching providers from the MDC and passes them, together with Nova’s criteria and weights, to the Recommendation System (RS), which ranks them (D6.1). Nova selects up to three providers, Acme among them, to negotiate with.

Solutions involved: Cloud MaaS Marketplace (CMM), MaaS Dynamic Catalogue (MDC), Recommendation System (RS)

3. Negotiate: Agents Agree the Terms

The CMM starts the negotiation: Nova’s orchestrator agent deploys one MaaS Consumer Agent (MCA) per selected provider, and Acme answers through a MaaS Provider Agent (MPA), which assesses each request against Acme’s capacity and constraints. The agents exchange offers on price, quantity and delivery date over the Point-to-Point Secure Messaging (PSM) broker, each negotiation on its own private topic (D6.1). Users can follow the negotiation, or run it in manual mode and enter counter-offers themselves; the user gives the final acceptance of the resulting deal: 5,000 parts at an agreed price, delivered in 18 days.

Solutions involved: Cloud MaaS Marketplace (CMM), MaaS Consumer Agent (MCA), MaaS Provider Agent (MPA), Point-to-Point Secure Messaging (PSM)

4. Contract: The Agreement Is Recorded

The CMM sends the agreed terms to the Smart Contracts Toolkit (SCT) through the SCT’s business event webhook, and the SCT records the agreement on the MaaS Blockchain (MSB) (D12.1). From then on, agreement approval, production updates, quality checkpoints and order completion are recorded as tamper-evident state transitions.

Solutions involved: Cloud MaaS Marketplace (CMM), Smart Contracts Toolkit (SCT), MaaS Blockchain (MSB)

5. Collaborate: The Two Teams Work Together

Once the contract is formalised, a MaaS Collaboration Hub (MCH) workspace is set up for the order; D5.1 states that the hub becomes active only after a match has been formalised through a smart contract. Acme and Nova can see the agreement and each other, create and track tasks, exchange messages and documents, and hold online meetings in one place instead of by phone and e-mail (D6.1).

Solutions involved: MaaS Collaboration Hub (MCH), Cloud MaaS Marketplace (CMM)

6. Exchange Data: Sharing Across Company Boundaries

To run the job, Acme and Nova need to share specifications, drawings and operational data. On each side, the DI brings ERP/MES data into that company’s own DS, an operational store based on the ISA-95 data model (D8.1). Data that must cross the company boundary is designed to be published from the DS through the PSM (D8.1, Figure 1), which authenticates each party (mutual TLS client certificates and Keycloak tokens) and encrypts the exchange (D8.1). Agreement events are anchored on the MSB through the SCT, and a digital passport for the asset can be designed and deployed with the Digital Industrial Passport Designer (DIP).

Solutions involved: Data Integrator (DI), EDGE Data Storage (DS), Point-to-Point Secure Messaging (PSM), Smart Contracts Toolkit (SCT), MaaS Blockchain (MSB), Digital Industrial Passport Designer (DIP)

7. Operate and Monitor: Production Runs

Production starts. Where Acme has a digital twin of the cell, the DTD keeps its state synchronised with the real equipment (D10.1), Data Analytics (DA) runs analytics workflows on the production data, and the Control Panels (CP) give the operator dashboards and alerts. Through Remote Monitoring and Control (RMC), Nova, as the consumer, can monitor and control the production it has contracted from a distance (D10.1). Meanwhile, the Predictive Maintenance Toolkit (PMT) flags a spindle that will need attention before it fails mid-batch.

Solutions involved: Digital Twins Designer (DTD) (optional), Data Analytics (DA), Control Panels (CP), Remote Monitoring and Control (RMC), Predictive Maintenance Toolkit (PMT)

8. Plan: Both Sides Adjust Their Schedules

The maintenance stop means the schedule has to change. Acme’s MaaS Provider Planner (MPP) re-optimises the shop schedule with deep reinforcement learning (D12.1) to fit the maintenance slot without missing the agreed delivery date, and Nova’s MaaS Consumer Planner (MCP) re-plans its own production accordingly. Where a job requires a production line to be prepared, the MaaS Workspace Configurator (MWC) recommends a line configuration for the incoming job (D10.1).

Solutions involved: MaaS Provider Planner (MPP), MaaS Consumer Planner (MCP), MaaS Workspace Configurator (MWC)

9. Simulate: Nova Tests Its Supply Network

Before committing more volume, Nova uses the MaaS Supply Chain Simulator (SCS), a discrete-event what-if simulator (D12.1), to test disruptions such as a supplier outage or a sudden rise in demand. The simulation reveals a single-source risk, and Nova decides to split future capacity across two providers.

Solutions involved: MaaS Supply Chain Simulator (SCS)

10. Assess End of Life: Deciding with Evidence

When the batch, or the tooling used to make it, reaches the end of its life, the LCA-LCC Toolkit (LCT) supports the assessment of its environmental and life-cycle cost impact (D12.1). The Repair-Reuse-Recycle Toolkit (R3T) then recommends the best circular path: repair, reuse or recycle (D12.1).

Solutions involved: LCA-LCC Toolkit (LCT), Repair-Reuse-Recycle Toolkit (R3T)

Where to Go Next

• The Solutions Suite lists all 23 solutions, grouped by feature.
• The Reference Architecture explains how the solutions are organised across the Cloud MaaS Marketplace, MaaS Consumer and MaaS Provider environments.

Sources: MaaSAI deliverables D5.1 (§3), D6.1, D8.1, D10.1 and D12.1.