Usage of smart and effective sensors that gather important data points on parameters such as current, vibration, pressure, and temperature.

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Datapoints gleaned can be used to understand the working status, and reduce machine idling time, and identify exact areas where human presence and intervention is needed.

Supply Chain Management can be enhanced with an additional layer of Machine Learning that can understand inventory and demand patterns, and alert stakeholders about falling stocks.

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Machine Learning can anticipate shocks in demand and supply and help optimize precious warehouse space, while helping with vendor relations.

Predictive quality analytics extracts actionable insights from industrial data sources such as manufacturing equipment, environmental conditions, and human observations to optimize the quality of factory output. Using  I Twin IoT platform, industrial manufacturers can build predictive quality models which help them build better products.  

Machine downtime can be a major hit on factory output and threaten to compromise on time-bound assurances given to customers.

With I Twin IoT platform you can capture all IoT data, such as temperature, vibration, and error codes that indicate if equipment is performing optimally. With increased visibility, you can maximize the utilization and investment of your asset.