General objective is to develop a unique digital system one-stop shop integrating several technologies or technological approaches which will be implemented in different phases along the shipyard’s working cycle.
Main technologies and applications will concern:
- Sensors and IoT: A set of sensors able to collect critical technical parameters depending on the machine and phase to be monitored will be implemented both in shipyard and on boat. In detail, on ship the sensors for the monitoring of electrical system (possible parameter: electric voltage), hydraulic system (possible parameter: water temperature and pressure), propulsion system (possible parameter: power supplied by the motor over time) will be integrated. Instead, in the shipyard the sensors for monitoring the operating status of some critical production process machines (possible parameters: machine temperature, duty cycle, pressure, oil level, working time, etc) will be installed.
- Advanced Business intelligence and Artificial Intelligence: The scope of data collection is to prevent naval failure events and machine downtime. The technology level of IoT sensors and the possibility of processing large amounts of collected data and representing the information obtained from them, justifies the need to refer to Artificial Intelligence techniques to make decisions objectively and quickly, not replacing the human operator, but supporting him adequately. Starting from historical and statistical data, the project could identify advanced machine learning and deep learning algorithms to predict malfunctions of machine parts, identify process inefficiencies and establish correlations between physical phenomena in production processes and the final quality of mechanical-physical processing. Indeed, data will be stored and used for real time analysis and historic analysis by applying a machine learning approach and sophisticate algorithms able to combine measures and data coming from different sources in order to provide, at the end, input, warning, alerts as support and suggestions for decision making process. The aim is to determine the presence of anomalous behaviour during the operation of a machine and the residual useful life time of certain components. At the same time, extensive monitoring of the information characteristic of the entire supply chain can be useful to support business decisions and, if necessary, optimize networks. The phases of collection, cleaning, validation, integration and aggregation are carried out automatically and allow the transformation of data into information and to store them, make them available and presentable in a simplified and effective form, so as to be able to support the decision-making process of the company. The areas of application of Business Intelligence are multiple and cover in addition sales, management control, product analysis and cross-selling. It is necessary to use an advanced system of business intelligence to analyze business performance throughout the supply chain and to support business decision-making processes in conditions of uncertainty and provide alternative scenarios. The use of a adavanced business intelligence system makes it possible to identify any problems of the company and, above all, ensures adequate support in the change and consequent adaptation to new business dynamics.
- Mixed Reality - Using digital supports such as Microsoft Hololens - based maintenance interactive manuals, engineers can perform more complicated maintenance and repair tasks on their own at sea. To further enhance operational readiness, the ship’s engineers can also request remote assistance from the Operational center.
- Cyber Security - Because ship maintenance management systems are increasingly integrated with operational systems, they are often seen by hackers. One of the project objectives could the design end the development of a robust cybersecurity framework to protect the data used in maintenance operations or communication activities.
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