Why do many PoCs fail? Free explanatory materials provided.
The introduction of predictive maintenance faces different "barriers" at each phase, causing many companies to stagnate along the way. The main hindrances are the "lack of clarity in ROI" at the pre-implementation stage, "low data quality" during the prototyping phase, and "enormous operational costs" during the production phase. At the root of all these failures lies a structural issue: the absence of an "AI-Ready data infrastructure" that assumes the use of AI. Clearly defining measures for each phase is the shortcut to success. Please take a look at the materials for a roadmap to promote projects without failure.
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Download All Catalogs![[Data] Predictive maintenance that directly improves profit margins: Preventing losses from unexpected shutdowns and digitizing the expertise of skilled workers.](https://image.mono.ipros.com/public/catalog/image/2117351/IPROS11579754503005051160.jpeg?w=120&h=170)
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NTP Corporation is a company that designs the future of manufacturing from the front lines of the industry. We do not engage in consulting that is solely based on documents. We redefine the roles of consultants and engineers, deeply immersing ourselves in the front lines of our clients' businesses and delivering tangible results in the manufacturing field through fast implementation that directly connects strategy and technology. Please feel free to contact us first. Professionals who understand the field will propose suitable solutions.
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