Periodic Reporting for period 2 - Dig_IT (A Human-centred Internet of Things Platform for the Sustainable Digital Mine of the Future)
Período documentado: 2021-11-01 hasta 2023-04-30
The need to extract raw materials in a profitable, environmentally sound, and safe way for both the mining workforce and the communities is driving the mining industry towards innovative approaches to transform its operations. However, even though Industry 4.0 offers a wide spectrum of solutions and intelligent technologies, the mining industry is still hesitant to adopt such innovative approaches.
Dig_IT will address the needs of the mining industry to move forward towards a sustainable use of resources while keeping people and environment at the forefront of their priorities. In order to achieve that, Dig_IT proposes the development of a smart Industrial IIoT platform that will improve the efficiency and sustainability of mining operations by connecting cyber and physical systems. The platform will collect data from sensors at 3 levels: human, assets and environment, and will also incorporate both real time and historical market data.
Dig_IT’s overall objectives are:
• A secure, smart IIoT platform that will improve the efficiency and sustainability of mining operations by connecting cyber and physical systems.
• On-line measurements of asset-bound mining operations through the monitoring of critical assets (i.e tools, machines, vehicles).
• Online distributed measurements of higher accuracy than current methods for broad area sustainability measurements.
• A Smart Garment for mining personnel sensing Occupational Health, Safety and Environmental (OHSE) parameters, biometrics, and situational awareness.
• Big Data optimisation through improving data quality aiming to minimise unused data and increase accuracy of analysis
• Digital Twins (DTs) of the physical mine entities, systems and processes to gain insights on mining operations, including Geotechnical DTs, Fluid Dynamics DTs and assets DTs.
• A predictive operation system and predictive maintenance agents with increased fidelity for process optimization and predictive maintenance of equipment
• An Intelligent Toolbox for OHSE to support operational awareness and decision-making based on bio-signal analytics, air-quality forecasting, spatiotemporal person & asset tracking
• A Decision Support System (DSS) integrating data streams, existing subsystems, data analysis and intelligent systems, using bespoke visualization of processes, objects and parameters, aiming at increasing the sustainability of the mining operations
The data acquisition activities in WP2 have been finished, achieving milestone 2 and 3 (MS2 and MS3). The main outcomes of these activities are two prototypes: (1) the low capex sensor bundle for the monitoring of environmental parameters; and (2) the smart garment. Both prototypes are already gathering data in the use cases. Besides, other instrumentation has been deployed in the use cases to monitor assets and assess geotechnical risks. In WP3, the design of the architecture of the platform, communications infrastructure and cyber-security arrangements have been completed, achieving milestone 4 (MS4). MS5 is almost achieved. The connection of sensors and actuators has been successfully tested for all kind of devices at least in one use-case. However, the connection of all the devices from all use-cases is on-going in the framework of WP6 ("System integration"). The development of digital twins in WP4 is in progress, initial versions of the models were developed to proceed with the initial integration steps. However, the validation of the models was delayed due to delays occurred in WP2 and thus final integration of the digital twins was postponed. Likewise, the modeling activities related to the intelligence layer (WP5) have continued during the second reporting period, being also delayed by the delays incurred in WP2. Hence, the work-plan for Digital Twin and Intelligence layers was modified (due-dates postponed) in the new work-plan (Amendment of the GA approved in March 2023).
In WP6 , the evaluation framework has been improved and implemented. Thanks to the application of the evaluation procedures defined in Task 6.1 the effect of the delays in any task on another one was identified and the communication path between the corresponding leading partners was established. This process led to the definition of a new work plan aiming at catching up the delays motivated by COVID-19. Besides, during the second reporting period, the development of the data aggregator for system integration started. This is a key for the proper development of the platform and has been conducted in close collaboration with WP3.
In WP7 and WP8 the cross-cutting activities related to society and market outreach are in progress, including the definition and development of the blockchain network for sustainability compliance, an IPR seminar, exploitation and dissemination workshops, etc.
In WP9 and WP10, the activities related to coordination and ethics surveillance are continuously ongoing, leading to a second amendment of the Grant Agreement and to an improved version of the Consent Form related to the use of the Smart Garment in the mines.
Blockchain Sustainability Compliance Labelling: Dig_IT Distributed Ledger-based Sustainability Compliance Labelling (SCL), besides providing provenance of raw materials, will expose trusted sustainability information to the local communities and the public, using Smart Contracts and public ledger.
Wearables for mining will offer an integrated, fully open-source based, wearable solution that will provide improved localisation technologies, sensors to measure OHSE parameters (i.e. temperature, humidity, gases and radiation, overloading effort), biometrics sensors (heart rate, sweat and body temperature) and an AI-enabled voice processing module for emergency communications with colleagues and administrative staff in multiple languages.
Assets Digital Twins for improved maintenance: Dig_IT is developing digital twin technologies which can be employed with complex mining machinery and complex mining production systems, and which can be used with both heterogenous and homogenous fleets. Methods using digital twins for prognosis, which enable predictive maintenance and predictive production, are also being developed.
Digital Twins for mines. The Dig_IT platform will use all the acquired data to improve the reliability of 3D models carried out during the design and operating phase in order to optimize spaces and production as well as foresee instability problems during the mine exploitation.