Machinery Maintenance is costly. For many sophisticated products or systems, traditional maintenance costs account for as much as 60 to 75% , of their life cycle costs and are continuously increasing. However, 30% to 50% of these maintenance costs are caused by ineffective maintenance management due to the lack of data to indicate when and what kind of maintenance is necessary. This type of maintenance, the one that predict when and what kind it is necessary, is called predictive maintenance (PM).
PM is now considered by manufacturers a main priority in order to increase efficiency. This interest has being raised due to the maturity of certain technologies that are making it possible: Big Data and Internet of Things.
However, only large machine manufacturing companies can afford to implement ad-hoc and costly predictive maintenance system (PMS). This makes small and medium-sized (SMEs) manufacturers to lose track in this competitive market. And SMEs in this sector are the most numerous and biggest employers. In Europe, the manufacturing sector gives employment to about 30 million people, 59% of them are SMEs. In an increasingly competitive market, where the big players are USA and China, SMEs must have access to best market technologies that fit their needs and resources. ThingSight, the PMS that we are developing, is the only solution for PM particularly tailored for SMEs (manufacturers and maintenance providers) by its cost-efficient model that offers high-level analytical insight on the state of machinery and maintenance needs. ThingSight is:
1. A complete IoT Analytics ecosystem for the whole value chain, from data generation and collection, data analysis to presentation
2. A flexible, adaptive, scalable and easy-to-use tool which will foster an early adoption and popularization among European SMEs (machinery manufacturers and machinery maintenance providers).
3. A low-cost PaaS “pay-as-you-grow” model (monthly fee: 4€/device) which is an affordable and competitive solution compared to different commercial products available.
By implementing ThingSight, machine manufacturing SMEs and its clients are expected to cut machinery maintenance costs substantially (at least 40% in downtime, 35% in labour and material) and increase machinery lifetime (by up to 60) and making them to be part of the Industry 4.0 revolution.
