Products are becoming more and more complicated-and manufacturers are having a harder time keeping up. 92% of manufacturers have reported that their products have become more complex over the last half-decade.
When it comes to time-series data, there is no shortage of options. Cloud-based, data-lake, open source, and historians are all readily available solutions for data storage, along with lower prices for sensors, and wired or wireless offerings for data aggregation.
There are several different architectures and protocols that can be used to gather data on the factory floor. The two most common protocols are very different, which makes them worth comparing for their effectiveness in IIoT - OPC UA and MQTT/Sparkplug.
AI-guided selling enables analytics to move from descriptive to predictive and prescriptive analytics. The process uses customer and sales data for a scientific, data-driven approach to understand buyer processes and behaviors.
Data is the new Black Gold but if you are gathering data and not using it effectively then you are paying for data transmission and storage andiIt just becomes white noise and adds no value.
Blockchain has proven an effective salve for the dwindling trust in today's supply chains. It enables a network-wide protocol that helps reduce "trust tax," or the costs of maintaining trust.
As an industrial manufacturing engineer writing and speaking about the supply chain for many years, as well as being in the field helping companies for most all of my career, I wanted to pass on some thoughts and information for those of you that are considering this type of deployment option - especially if your mission-critical business depends upon a working cloud.
The complexity of mineral processing and manufacturing plants - how Artificial Intelligence can help
Industry 4.0 encapsulates not only manufacturing but also mineral processing plants and the differences between these should be considered carefully in the deployment of 4.0 solutions such as Artificial Intelligence (AI).
Even when you can connect directly to whatever it is that you are measuring and design the system yourself, you might encounter issues. Inconsistencies can arise from power failures, wifi outages, faulty or damaged equipment.
Modern manufacturers face key challenges to reaching their Industry 4.0 potential. MarkLogic knows data is your greatest asset to better serve customers, improve products, and navigate those complex environments.
Commentary from Ramona Schindler, General Manager Machine Tool Systems, Siemens Switzerland. Most shops, even the smallest ones, have obviously been gathering data and logging it in a production-schedule format of some kind for many years.
"What makes the digital thread so important is that to leverage all the data, you need to also manage how the data connects to the rest of the operation and how it flows from one process to another."
Data connectivity and collection has evolved past the workarounds and silos that long-plagued industrial ecosystems. New technology is transforming data accessibility-without interrupting your vital processes or requiring new equipment.
Many companies are striving to create real business value from their various streams of information, a serious data-driven approach. Measurement, monitoring and access to real-time data are extremely important to reaping the benefits of Industry 4.0
By tapping into existing maintenance or equipment logs, a manufacturer can apply machine learning to predict which connected devices or machines will be in need of servicing or forecast required inventory levels across warehouse locations...
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