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Putting the Intelligence in Smart Manufacturing
September 4, 2019 Blog

 

The First Industrial Revolution was said to have started back in 1760 (almost 260 years ago), prompted by the introduction of steam engines. The advent of the assembly line, and then data-enhanced automation, further enhanced the manufacturing industry and brought on the Second and Third Industrial Revolutions, respectively.

History has shown that manufacturing is a sector that has been shaped by some significant changes. Nevertheless, experts are saying that the new wave of technological evolution IR4.0 looks set to bring be the most significant change yet and will trigger an industry-wide paradigm shift.

Just like many other industries, manufacturing has certainly benefited tremendously from the rise of big data-driven analytics and cloud computing. However, combined with a number of other advanced technologies that are also reaching maturity, such as artificial intelligence and cognitive computing, IoT and machine-to-machine (M2M) learning, we are now close to approaching the era of “smart factories”.

What makes smart factories different (and better)? According to McKinsey & Company, smart factories use these interrelated technologies in order to generate digital intelligence across their entire value stream. The end goal is for the factories to be able to respond in real time to issues pertaining to quality control, equipment outages as well as other production challenges by creating “processes that govern themselves, where smart products can take corrective action to avoid damages and where individual parts are automatically replenished.”

Smart manufacturing facilities can, for instance, implement lean manufacturing practices and keep stocks always to a minimum of what is required (never too many or too few), track a machine’s performance in real-time or predict equipment failure well in advance to avoid downtime.

Among the myriad of benefits that manufacturers stand to gain by harnessing IoT and advanced analytics technologies to make processes smarter include:

  • Increased productivity and uptime
  • Improved process efficiencies
  • Faster innovation
  • Reduction in asset downtime
  • Enhanced operational efficiency
  • Create end-to-end operational visibility
  • Improvements in product quality
  • Lower operating costs
  • Optimised production scheduling
  • Better overall equipment effectiveness (OEE)

Nevertheless, getting to that point of intelligence won’t be simple. For a long time, manufacturers have relied on legacy systems that are based on proprietary or outdated technologies. The problem with that is they can’t be easily integrated with new technologies and applications without costly customisations. As a result, they become inflexible and their extended functionalities, severely limited.

On top of that, manufacturers also have to contend with rising complexity of these new technology implementations. In trying to ensure that the millions of data points, devices, equipment and other interlinked moving parts run smoothly and are synchronised across the entire value chain, unprepared manufacturers could easily find themselves getting tangled up in a web of interdependencies.

In order to choose the right technologies and solutions that can address their unique requirements and specific needs, and deal with the complexities, it is recommended that manufacturing firms work with a partner that has both OT and IT expertise in data analytics in order to “co-create” their IoT and advanced analytics solutions.

To learn more about the wisdom of a co-creation approach and how Hitachi Vantara can leverage 100+ years of OT experience and nearly 60 years of IT expertise to help manufacturers get smarter for Industry 4.0, click here.

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