Advanced Analytics in Manufacturing

Data, statistics, and analytics have been an integral part of manufacturing for a long time, especially in

  • improving quality of products using techniques like statistical process controls, lean, six sigma etc.
  • process simulations
  • product performance analysis
  • artificial intelligence methods for process planning, assembly line balancing etc.

An article by McKinsey presents how the use of advanced analytics may reveal further opportunities to increase yield, save costs, and improve quality.

Some of the key views presented in this article are:

  • Advanced analytics using historical data to identify patterns and relationships to optimize yield
  • Getting important insights by looking at previously isolated data sets, aggregating them, and applying analytics techniques
  • Taking real advantage of the abundance of real-time shop-floor data
  • Using advanced analytics like neural-network techniques to measure and compare the relative impact of different inputs on yield, quality, inventory etc.

Advances in hardware technologies, connectivity, and computing capabilities open up enormous opportunities for transforming manufacturing. Some of these include:

  • Intelligent machines that not only generate data for analysis but also have built-in capabilities to analyze and even take their own decisions/actions
  • Software applications that provide real-time insights by looking at data from
    • Shop floor operations
    • Sales and service operations
    • Customer usage, wherever possible
    • External data from social media, user forums, etc.
  • Insights to plan interventions at an individual employee level for quality and productivity improvements
  • Various opportunities to plan manufacturing that improve timely delivery, reduce inventories, and support product customizations
  • Various opportunities in supply chain management

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