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10 Ways Machine Learning Is Revolutionizing Manufacturing In 2019

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10 Ways Machine Learning Is Revolutionizing Manufacturing In 2019

10 Ways Machine Learning Is Revolutionizing Manufacturing In 2019

Machine Learning

  • AI has the potential to create $1.4T to $2.6T of value in marketing and sales across the world’s businesses, and $1.2T to $2T in supply-chain management and manufacturing.
  • By 2021, 20% of leading manufacturers will rely on embedded intelligence, using AI, IoT, and blockchain applications to automate processes and increase execution times by up to 25% according to IDC.
  • Machine learning improves product quality up to 35% in discrete manufacturing industries, according to Deloitte.
  • 50% of companies that embrace AI over the next five to seven years have the potential to double their cash flow with manufacturing leading all industries due to its heavy reliance on data according to McKinsey.
  • By 2020, 60% of leading manufacturers will depend on digital platforms to support as much as 30% of their overall revenue.
  • 48% of Japanese manufacturers are seeing greater opportunities to integrate machine learning and digital manufacturing techniques into their operations than initially believed according to McKinsey’s landmark study, Digital Manufacturing – escaping pilot purgatory.

Bottom Line: The leading growth strategy for manufacturers in 2019 is improving shop floor productivity by investing in machine learning platforms that deliver the insights needed to improve product quality and production yields.

Using machine learning to streamline every phase of production, starting with inbound supplier quality through manufacturing scheduling to fulfillment is now a priority in manufacturing. According to a recent survey by Deloitte, machine learning is reducing unplanned machinery downtime between 15 – 30%, increasing production throughput by 20%, reducing maintenance costs 30% and delivering up to a 35% increase in quality.

This article originally appeared on forbes.com To read the full article, click here.

Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously.  To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:

  • Advanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
  • Raw information handling and analytics speed
  • End-to-end business transaction tracking that spans technologies, tiers, and organizations
  • Intuitive, easy-to-use data visualizations and dashboards

If you would like to learn more, click here.

 

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