| Summary: | In the field of Intelligent Manufacturing there are some topics that have gotten lots of attentionin the past few years. The virtualization of shop-floor equipment, the easy access to the machineinformation or the collaboration among shop-floor equipment are examples of the latest trends inthis field. This technological developments in software, hardware and data treatment can have ahuge impact on how the shop-floor is perceived, analyzed, interpreted and operated.In this context, SelSus - Health Monitoring and Life-Long Capability Management for SELF-SUStaining Manufacturing Systems was developed. This project comes as a new synergetic diag-nostic and prognosis environment fully aware of the condition and history of all machine compo-nents within a system or factory, making use of a Sensor Cloud and a Wireless Sensor Network.Presently, smartphones are one of the most used electronic devices and they have many sensorsand built in functionalities that can be used in the industry for monitoring the process of machinesand operators' interaction with the manufacturing system. Following this idea, the main focusof this project is the development of an Android mobile application that allows the capture andmonitoring of important information related to the machines and system state. This applicationhas two main functionalities: an interface to show the machine related data and analysis, both inreal-time and non-real time, and a tool that allows the user to capture data from the various sensorsbuilt in the smartphone. This equipment will be used to its fullest in terms of how much data itcan acquire.The main goal in the industry is to reduce costs, which can be achieved by reducing the downtime of the machines. If the machine fails, the production line in which that machine is integratedstops, which results in a waste of production time and may also damage raw materials. Thedeveloped application will help make predictive maintenance and prevent unexpected failures inthe machine. This can be achieved, as all data will be sent to the Sensor Cloud and treated asadditional information for a specific machine. The main objective is to check the state of themachine and try to predict failures so that maintenance can be performed beforehand, avoiding itsloss of performance.
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