Objetivo
Thanks to ThingSight, manufacturing SMEs will be able to anticipate and avoid equipment failures by embedding a predictive maintenance solution within their products. ThingSight is an Internet of Things (IoT) Analytics system which generates and collects data from machinery and provides a flexible, scalable and easy-to-use analytics tool to help manufacturers in their daily machinery support and maintenance activities. This disruptive innovation provides important benefits for manufacturing SMEs: reduced equipment downtime (40%-60%) increased effective manpower utilization (75%-80%), increased production capacity (15%-40% for the short term, and 75%-80% for the long term), reduced labour and material costs (35%-60%) and increased machinery operating lifetime (33%-60%). ThingSight is particularly targeted at European SMEs (manufacturers and maintenance providers) which cannot afford the implementation of ad-hoc IoT systems. While existing alternatives are costly and require a high investment, the innovation of ThingSight primarily comes from our successful pay-as-you-grow model based on the number of devices. In Phase 1 we will conduct a research on the optimal algorithms and techniques for descriptive analysis, advanced analysis and machine learning. Additionally, we will select potential technological partners for the project. We will also develop a Business Plan to analyse the economic viability of ThingSight and prepare a detailed Financial Plan. ThingSight will contribute to the overall EU’s industrial growth strategy by providing advanced IoT tools to help manufacturing and maintenance companies to become more resource-efficient, by reducing machinery maintenance costs and increasing equipment lifetime operation.
Ámbito científico
- natural sciencescomputer and information sciencesinternetinternet of things
- natural sciencescomputer and information sciencesdata sciencebig data
- social scienceseconomics and businessbusiness and managementbusiness models
- social scienceseconomics and businessbusiness and managementemployment
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SMEINST-1-2016-2017
Régimen de financiación
SME-1 - SME instrument phase 1Coordinador
28037 MADRID
España
Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención.