Pilot domain: Production

The “Production” pilot domain targets the demonstration of efficiency improvements made possible by distributed and collaborative automation. This will be pursued for a number of application areas, targeting a variety of efficiency levers and requiring different combinations of technologies.

By “distributed” it is meant here that the application covers all functional layers of industrial systems, starting from sensor or process level and extending up to enterprise level. Another dimension of distribution is over the value chain of companies or plant sites, i.e., company networks both upstream and downstream, where efficiency is expected for the entire network, not just for a single factory or production line.

We will explore, for the targeted domains, the potential benefits of new smart and connected features and build the vision of the ecosystem evolution: what are the new business cases, what are the impacts on people, on production and on processes what are the technical issues and opportunities. We will experiment some of the new features through implementation on a real systems (machine or workshop of plant) or on simulated demonstrators connected with real data.

The perimeter of the new features includes:

  • Features directly aiming at increasing human, machine, plant, or value networks performance, reducing costs, improving energy efficiency, machine health, product quality, etc.
  • Features implementing flexible connectivity across functional layers and over factory sites.
  • Features treating confidential and open information or intellectual assets in a fair and useful manner.
  • Features enabling competitive and accurate service business in such value networks, for the benefit for all participants.
  • Features connecting the plant to the virtual market of energy through technical and business interfaces.

Seven demonstrators focus on improved supervision and maintenance: networked condition and performance monitoring, maintenance, respective networked service businesses, respective support centres. The three other demonstrators are focused on operations flexibility and energy efficiency: operations management, optimization, energy usage modulation, management of multiple energy sources, in connection with the Virtual Market of Energy.

Each demonstrator requires part of the Arrowhead main technologies, to be provided or improved as part of WP6-10, and relies on specific analytic and evaluation methods to evaluate and optimize efficiency gains.

Demonstrator: Smart services in engine business

The overall goal is to improve the efficiency of maintenance cycles in test devices in the automotive industry. Those devices are deployed at various remote sites spread of over multiple continents and involve various different organizations. Maintaining the devices is costly and a short fixed maintenance cycle may cause unnecessary downtime and maintenance effort. On the other hand, fixed long maintenance cycles may result in faults not being detected in time and in the worst case with in device break downs with potential safety implications. An ideal maintenance interval depends on the operational conditions of the individual device which vary from case to case.

We propose a system which collects monitoring data from the deployed devices and triggers maintenance operations based on the automatic analysis of the data. This is done under consideration of automotive specific privacy and security considerations and the corresponding safety implications. This is of upmost importance for a new innovative service system.

Demonstrator: Manufacturing electrical enclosures, cabinets and accessories

This demonstrator is focused on production flexibility and energy efficiency in a discrete manufacturing process: the production of electrical enclosures, cabinets and accessories at a Schneider Electric (Sarel) production site. The pilot consists of understanding the energy consumption of the manufacturing process and managing it in order to optimise the energy consumption expressed either in kWh, in €, or in CO2 emissions.

Demonstrator: Lift machine efficiency

The overall goal is to enable efficiency improvements for lifts, and in a more general way for hoisting machines, with a special focus on energy. Improvements will cover the following perimeters: the recovery of energy at deceleration, the use of renewable energy sourcing (potentially photovoltaic), and an optimized strategy for multi-sources management and for energy usage.

These improvements will be achieved thanks to analytics features connected with real time measurement or data, with usage and weather forecast, with energy prices models, and with machine devices or equipment.

Demonstrator: Water distribution networks

The objective is to demonstrate potentials in terms of energy saving applicable to water distribution networks. Energy represents about 30% of total operating costs of water networks, and the energy costs will show significant increase in the coming years. Energy efficiency measures can help to save up to 30% on energy bill. In addition, modulation in energy usage can open perspectives on energy market through aggregators, or demand response mechanisms.

The objective of the demonstrator will be to prototype the tools that will give access to better energy management, and consumption modulation for demand response purpose.

Demonstrator: Aircraft maintenance

The overall goal is to leverage the usage of wireless communications and devices interoperability for aircraft maintenance to raise maintenance efficiency by allowing the maintenance operator to access any data produced by the aircraft systems or by the ground infrastructure.

Three main actors (the aircraft, the line mechanic, and the airline Maintenance Control Centre) have to cooperate seamlessly to allow efficient maintenance operations during “turn-around time”, in order to ensure aircraft dispatch on time whatever the characteristics and location of the failure to repair, the aircraft status and the airport infrastructures.

The pilot shall demonstrate that technical as well as operational impacts of data security constraints on the projected architecture are acceptable.

Demonstrator: Condition monitoring and maintenance integrated to production management in the mining industry

The plan for the intended demonstrator is to pilot mine and concentration plant advanced operations and maintenance, and their immediate interaction with control systems performances, maintenance activities, and ultimately to the ERP/MES level of the respective company network. Multiple stakeholders might be concerned:

  • Machine vendors, process vendors, integrators and system vendors
  • Mine owners and operators
  • Concentration plant owners and operators
  • Operations and maintenance services
  • Spare parts services
  • Site subcontractors

The intended technological base is a reference model describing the elements and structures of predictive maintenance in knowledge-intensive working machine and process machinery contexts. The pilot shall also include design tools, libraries, and platforms to effectively engineer such networked business applications. A proper amount of field level instrumentation is needed to make condition prediction reasonably accurate and reliable.

The idea is not to work too much on existing automation systems as such, but certain adaptation is expected to make their coordination to advanced and integrated maintenance or maintenance business possible. The heart of the pilot will be the reference model of the distributed maintenance business – and the respective portions of the expected Arrowhead framework, components, and tools.

Demonstrator: Collaborative Engineering for Assembly Automation

The objective is to create and demonstrate the collaborative engineering of engine assembly automation systems via the application of a Device Level Database (DLD) system and associated engineering tools. This DLD system will support the use of reusable software components to enable the pilot scenario of process/design visualisation, simulation, deployment and monitoring of a set of assembly stations in multiple Ford production plants, with remote service support from European machine builders provided via FDS technology.

The DLD system will be populated to form a reuse library of assembly automation stations from the real use-case data provided by Ford and progressively developed, applied and evaluated throughout the system lifecycle via the three generations of demonstrator.

Demonstrator: Self condition monitoring mobile machinery

This is a demonstration of how to implement the Arrowhead Framework on a wheel loader application. Wireless sensors, mounted on the wheels, is providing measurement data, which are sent to a gateway on the vehicle and then to a land based control centre for analysis, prognostics and maintenance scheduling.

The measurements will provide information about the condition of not only the ball bearings but also the whole drive train of the wheel loader. This information will help to reduce the wheel loader down time as well as maintenance cost.

Demonstrator: 3D localization in mines

This demonstrator is concerned with the design and implementation of 3D localization technology in the context of mining. Robust 3D localization has been identified as a critical technology for the long term vision of Zero Entry Production Area (ZEPA). The challenge is to devise technology enabling 3D localization at various levels of accuracy and scale.

Demonstrator: Condition monitoring of transportation systems

The objective is to build a demonstrator of sensorised axlebox bearings on railway wagons. A train will be equipped with sensorised axlebox bearings and communication means to make it possible to record data while the train is running with features as follows:

  • A condition monitoring system being able to calculate Remaining Useful Life (RUL) for an axlebox bearing
  • A sensorised axlebox bearing using SOA
  • Sensors, equipped with data and information security means, attached to the axle box bearings of an iron ore wagon
  • A condition monitoring system on-board a train using CoAP
  • A condition monitoring system on-board a train using OPC-UA