With the arrival of Industry 4.0 and the Industrial Internet of Things (IIoT), a digital transformation is currently underway. Manufacturers have used data analysis to improve efficiency and advance their market share for many years. But the most significant change today is how data is collected. Many companies still use fragmented, traditional methods for data capture, with staff manually checking and recording factors, filling forms, and writing down operation and maintenance histories for the machines on the floor. Unfortunately, these methods are highly inaccurate due to human errors. They are also time-consuming, open to bias, and do not generate the quality of analysis required for accurate decision-making. 

Equipment connected through sensors and edge devices feeds massive volumes of data to cloud-based analytics platforms that can analyze and understand data faster than human perception. This data can then be used to drive real-time decision-making and significant process improvement throughout the company. With accurate and real-time data, manufacturers can make better, faster decisions

Automated machine data collection is driving the next generation of manufacturing analytics, unlocking a myriad of advanced analytics use cases in manufacturing that range from simple monitoring and diagnosis to predictive maintenance and process automation.

In manufacturing analytics, data capture that records events can be leveraged to increase equipment utilization, reduce cost, drive process improvement, reduce human-based errors, and do so at a depth that reveals accurate machine conditions and trends in production.


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