Large OEMs, such as Airbus, have streamlined their supply chains and reduced the number of 1st tier suppliers to a small number of large preferred suppliers (typically large companies such as Thales, Honeywell). Other constrains such as extensive risk sharing requirements, complex procurement and collaboration procedures, rules and diversity of IT systems create strong barriers for SMEs to become a 1st tier supplier of those companies. 
On the other hand, highly customised products such as commercial aircraft, often require very specific solutions developed and provided by small but innovative high-tech companies. The customer demands, e.g. for novel cabin features, must be developed and produced in very short time with close collaboration of OEMs and high-tech SMEs. This typically requires, an ad-hoc production / supply network and currently this is best served via a local cluster around the OEM.

As soon as the parties are geographically separated, the OEM and the innovative SMEs (organised in industrial clusters), need ICT solutions (technical platforms, novel governance approaches, coordination tools and services) to simplify the ad-hoc setup and management of collaborative production in the agile network and to manage the IPR, etc. 

The interoperable toolset in the EFPF platform can support the enactment of distributed production processes, support collaborations and provide vital visibility to distributed activities taking place across production networks.

Requirements of Embedded Pilot Scenarios

Experimental Support through Pilot Validations

Implementation and Validation through Pilot-1 D

Implementation and Validation through Pilot-2

Implementation and Validation through Pilot-3

EFPF project supports a circular economy scenario, from wastes to energy. The wastes producer sells its wastes to a waste management company which pre-process them and sell them again to a bioenergy company to produce energy. A part of this energy returns back to the first company that has produced the wastes as an outcome of its production processes.

The negotiation of offers and services regarding processed wastes is a very challenging procedure since it involves several organisations from different sectors (such as recycling companies) and needs fast decision making. All these procedures are conducted manually using phones and emails to select the offers and choose the best one based on specific criteria such as price, health and safety issues (regarding collection) etc. This procedure is inefficient and expensive. The three companies participating in the circular economy scenario need a solution that will provide automated bids and negotiations through an online system to obtain high-quality services and products at reasonable prices.

EFPF Online Bidding Process service provides an automated matchmaking mechanism for information requests from buyers to suppliers, to execute negotiations and business transactions automatically via configured agents. It is a matchmaking application that achieves automated negotiations and business transactions between interested stakeholders. The matchmaker’s goal is to find the best possible supplier to fulfil a request for a service or product in a fully automated way. Different decision criteria for supplier’s selection, according to several qualitative and quantitative factors, are considered by the matchmaker. It also evaluates the available offers from the providers in order to suggest the best one to the supplier. Virtual agents enable the automated communication between companies as every company is represented by an agent during the communication/negotiation phase.

Partners: KLEEMANN, ELDIA, MILOIL, LINKS and CERTH

The Predictive Maintenance demonstrator is focused on the monitoring of the operation of an edge banding machine to detect anomalous working conditions evaluating the risk of machine breakdown and take preventive actions through machine data analysis.

This experimentation has been deployed in a real manufacturing environment in the Spanish company LAGRAMA. They produce high-quality home furniture and they are located in Vinaròs (Spain).

The operator gets live information from the UI, which is accessible from the portal. The operator can monitor information, such as the failure prediction and confidence in the prediction. Sensors readings can be monitored from the UI as well to help identify the location of a fault. Working in batches means many machine stops and, of course, affects whether a machine is running all the time continuously. Predicting when the edge banding machine may need maintenance of a part or motor is a significant advance for LAGRAMA since it can prevent any part from being damaged, decreasing productivity and consequently losses and a bad image in the face of customers for late deliveries

To predict when the edge banding machine requires some maintenance operation, machine data is captured from the machine by retrofitting sensors (temperature, electric current and air pressure)  to parts of the machine.

The sensors are connected to an interface board on the Industreweb Factory Connector, which monitors the values and publishes them to the EFPF Data Broker. The Analytics component monitors these data and builds up a machine learning model. This enables the publication of a special event to the Message Broker when the machine operation values indicate some potential problem.

This way, the Risk component, which is subscribed to the Analytics Component's output topic, can evaluate if there is a risk of a machine breakdown and, in such case, this component triggers an alert to maintenance staff in LAGRAMA.

In summary, we can conclude that the value proposition for LAGRAMA is:

• Reduction of the reaction time when some problem arises during production
• Reduction of the machine downtime due to primary failure in the machine
• Avoiding failures that may affect the quality of produced goods through the detection of abnormal machine operation.

Many SMEs lack fundamental digitisation that can allow them to connect their machines and devices to digital networks without significant investments. Such connectivity and digitalisation can enable SMEs to unlock the value of their data and increase the efficiency of production processes. In a specific EFPF pilot scenario, capturing and processing relevant shop floor information is demonstrated through the use of federated EFPF solutions. The overall goal of this pilot scenario is to ensure that specific parameters in specific production machines and production environment are analysed in real-time to provide effective decision support. In aviation, large OEMs such as Airbus and Boing set detailed product specifications for suppliers. In some cases, certain production steps are only permitted under very specific and monitored environmental conditions. For example, aerospace paints may only be processed within a specific temperature range.

The implementation of this scenario is carried out at EFPF aerospace partners Walter Otto Müller GmbH & Co. KG (WOM) and Innovint Aircraft Interiors GmbH (IAI). WOM requires control of temperature and humidity in their manufacturing area to ensure consistent quality and environmental conditions required for component tolerances. Similarly, IAI needs to survey raw material stored in a freezer to avoid scrapping in case of too high temperature. When a high temperate is detected the vacuum forming machine needs to be controlled to take immediate actions.

In these scenarios, the goal is to secure the stability and quality of manufacturing processes by monitoring the relevant parameters and provide alarms in case defined thresholds are underrun or exceeded. Overall goals are to make sure that:

• Products are manufactured in acc. with relevant process specifications
• Rejects and waste are reduced
• Failures can be detected early, and intervention actions can be taken if necessary
• Record history data as proof for the correct functioning of the system even when unattended

The developed EFPF solution utilises small industrial computers and Ethernet-IP input-output modules linked to the relevant process sensors and actuators on the hardware side. All needed hardware was agreed upon between the partners. These are installed in electrical cabinets with supporting electrical equipment to solve a high-standard industrial level. The installation of all hardware and equipment into the cabinets has been done by the user companies WOM and IAI.

Through their wide-ranging applications in the manufacturing environments, it is increasingly evident that Artificial Intelligence techniques can increase process reliability and efficiency. Expanding the applications areas of AI in the manufacturing environments, in the EFPF project a specific use-case investigates the use of AI-based visual analytic techniques to ensure operational health and safety compliance. In this use case, a tool for automatic detection of facemasks has been implemented using AI-based visual analytic techniques. The tool orchestrates various systems in the spray booth area of the shop floor to ensure operational safety, compliance with relevant procedures as well as efficiency in the painting process.

The EFPF solution detects that the operator is wearing the correct face masks, checks that the required air temperature is available and opens the spray value automatically. At the same time, the extraction system is turned on and the safety lights indicate the status. The solution utilises a small computer that hosts the EFPF Factory Connector, which is responsible for establishing the connection between various hardware and software components. The AI visual analytic algorithms are tuned to process real-time video feeds. Advance machine learning techniques were used to train the models that are able to recognise compliance with relevant safety procedures (e.g. use of correct mask, the positioning of mask etc) or raise alarms if anomalies or non-compliance are detected. The Factory Connector also provides remote access and connection to the EFPF Data Spine so that the relevant data can be directly analysed to provide valuable intelligence.

The lack of capability to track and trace assets and transactions throughout the entire supply chain is one of the critical challenges that the companies face towards the circular economy. This lack of traceability hinders companies from quickly adapting, planning, and managing their assets effectively and optimised.

A solution is needed to help companies track and trace their assets at every supply chain stage and increase supply chain visibility without significantly increasing operational costs.

In particular, for  EFPF project supports a circular scenario, from wastes to energy. The wastes producer sells its wastes to a waste management company which pre-process them and sell them again to a bioenergy company to produce energy. A part of this energy returns back to the first company that have produced the wastes as an outcome of its production processes. A track and trace mechanism for the exchanged wastes over this circular closed loop is needed.

EFPF provides a Blockchain-based mobile app available to the stakeholders of the transportation (i.e. drivers etc.) to enable a secure and trusted handshake between them. Furthermore, a web application based on blockchain enables adding permissions to drivers, vehicles etc. that participate in a transportation process, monitor the various stages of the transported waste and issue a digitally signed document related to waste’s transportation and handling. Both mobile and web apps share a common blockchain back end in logging transportation information in the same blockchain instance. Smart Contracts are used as a back-end part of the two DApps (web and mobile). Identity Smart Contracts, Supply Chain Smart Contracts, Logging Smart Contracts and Notification Smart Contracts are used. The combination of the two apps (mobile and web) provides a complete solution of wastes’ track and trace in a circular closed-loop and promotes full visibility of the processes.

Partners: KLEEMANN, ELDIA, MILOIL and CERTH

The EFPF Data Spine is the interoperability backbone of the EFPF federation that interlinks and establishes interoperability between the services of different platforms.

It is essentially a collection of components that work together to form an integration, interoperability and communications layer for the EFPF federation:

• EFPF Security Portal
• Integration Flow Engine
• API Security Gateway
• Service Registry
• Message Bus

EPFP Data Spine Realisation Final Report