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Manufacturing Technology Insights | Sunday, July 31, 2022
IIoT is transforming business. Manufacturers have had more data ever since.
FREMONT, CA: Companies now have an almost infinite capacity to collect and retain data thanks to the IIoT. This translates to information regarding the efficiency, output, and machinery used on the packing line to manage that line. Decisions based on this information can and do improve plant performance and processes generally.
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However, without automation and a streamlined data collection and analysis strategy, data harvesting becomes an exercise determining the types of data and the amount needed to provide the knowledge needed to pinpoint the problem.
Despite challenges, manufacturers recognize the importance of accurate information and are looking at ways to implement it to improve packing lines and procedures. The industry's rapid adoption of IIoT has flipped the situation from one of insufficient data collection mechanisms to one of having too much information. This introduces a new difficulty: mastering the art of making sense of voluminous information. Without data architecture professionals who can offer insightful analyses and practical next actions based on the information gathered, manufacturers have reached serious snags.
The amount of data plant managers and executives need to collect and analyze often overwhelms them. Data from existing equipment connected to the IIoT can be used in four ways, thanks to data management and productivity solutions.
Manufacturers might be lucky to have a month's worth of data if manufacturers don't have data collection systems. It's also safe to assume that their data only covers intervals of half an hour. Improvements in IIoT implementation have made examining data at the minute and even second levels feasible, which can shed light on what's going wrong and why.
Your printer's data management features, which save a multitude of information, sync with the cloud. The weight of resources is shifted from data gathering to analysis when measurements are streamlined and simplified, with data traveling directly to the cloud. At this point, data management technologies are useful. Manufacturers with access to these resources can drill down into the data to get insights into short- and long-term trends.
A one-size-fits-all approach doesn't work when amassing and organizing information. Problems frequently arise when deciding what to do with the collected data after it has been identified. Data on many plants currently requires more work to acquire and interpret due to the data collector's subjectivity and the plants' individuality being studied.
But if data already exists in a clean, consistent, and usable shape via data management technology, it becomes a single exercise. Managers at the plant can utilize this information to isolate the most pressing issues and determine their origin. Teaching and standardizing best practices and processes throughout the plant is made possible with the help of statistics and mathematics, namely the evaluation of trend lines and control charts.
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