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The Move to Quality 4.0: Understanding Emerging Technology Use-Cases

Continuing on our journey into 'Quality 4.0', this week we take a closer look at emerging technologies and a few of their current and projected applications. 


Emerging technology is an ever-evolving piece of this transition and some aspects are in early stages of development. However, our streamLABS product and solution teams are identifying trends and keeping an eye on these advancements to ensure use-cases are discussed with industry thought leaders. Here are just some areas we will be focusing research on in 2018 and beyond, primarily to enable and support the industry’s move to Industry 4.0.

  • Machine learning & Natural Language Processing: Bringing a new pharmaceutical drug to market takes on average about 12 years and can reach into the billions in R&D costs. Industry leaders are now seeking more efficient methods of approaching the drug development process and machine learning is emerging as a key possibility to help bridge these gaps. While experts agree that the next 10 or so years will see a disruption in drug discovery caused AI, the key will be how effectively will AI help to determine the biggest drug winners. Specifically for QMS systems, Artificial Intelligence, through Natural Language Processing can be useful for organizations looking to leverage both structured and unstructured data embedded in these systems to gain additional insight not readily available through standard forms of querying and trending.
  • Blockchain Technology: Current explorations into use cases such as Supply Chain Transparency and traceability for product recalls have emerged as of late. Seeing the value of the technology, our very own archiveIQ solution is being built using blockchain technology ensuring trace-ability and integrity of archived data. Learn more about archiveIQ here.
  • Connectivity to Manufactured Operations: Exploring new modes of connectivity between manufactured operations and quality management systems is an area that will gain momentum in the next few years. As companies take the manual tracking out of the equation, use cases are being presented where quality issues are being automatically entered into a QMS in real time both on the operations side and the complaint intake side.  This tech will begin playing a significant role sooner than you might think!


Check back in with us next week as our INSIGHTS team covers the final Move to Quality 4.0 installment on Analytics & Big Data, and please, let us know your thoughts!