With the arrival of Industry 4.0 and the Industrial Internet of Things (IIoT), a digital transformation is currently underway. The manufacturing industry is beginning to use manufacturing data analytics driven by real-time production data to make better, faster decisions and enable automation across the organization.
Data analytics for manufacturing with real-time production data is changing the manufacturing industry dramatically. Let's consider several manufacturing data analytics use cases that real-time machine connectivity has made possible in manufacturing:
Automated quality control has come a long way. It’s evolved from trip sensors, drop wires, and other mechanical devices to a highly sophisticated collection of advanced optical devices. By tying these devices into data collection, sensors can add data to the stream through optics, temperature, and advanced vision applications such as thermal and infrared detection to accurately control stops. This also allows for higher speeds, lower labor, and the holy grail of any factory – "lights out" manufacturing.
Contextual awareness is critical for advanced manufacturing systems. Manufacturing analytics provides that awareness in real time. This makes companies more competitive as cost, quality, product development, and customer satisfaction are optimized. Manufacturing analytics software empowers companies to improve productivity and profitability by leveraging the massive data stream their production equipment generates. With intuitive visualization tools, dashboards, machine learning algorithms, and advanced analytics, actionable insights are available to managers and decision-makers across the company.
The cost can be significantly reduced because processes can be optimized with the insights revealed in analytics. And the growth of robotics, as well as autonomous or semi-autonomous machine decision-making, reduces labor. The same is true of predictive and prescriptive maintenance programs proven to reduce cost and increase productivity by lowering downtime and managing parts inventories better.
With real-time insights available in production, inventory management, and demand and supply planning, manufacturers can respond quickly to changes in demand. Suppose the data tells them that they’re nearing max capacity. In that case, they can add overtime, add capacity, alter processes, or adjust other aspects of production to respond and maintain delivery times.
With the increased capabilities of manufacturing analytics, there are also miscellaneous benefits. These include reduced energy consumption, safer environmental protocols, reduced compliance errors, and increased customer satisfaction.
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