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Innovations in Manufacturing Industry

Challenges:

With the increase in competition and changing landscape of the manufacturing industry, organizations are constantly looking for ways and technologies to not only improve their manufacturing operations but also enabling efficient and new capabilities for the operations of the equipment they manufacture. Producing highly efficient machines at lower costs has become the norm.

Innovation:

• For the last couple of years the concept of “Industry 4.0” has been increasingly getting traction and so is its adoption, as technologies become widely available at lower costs. Business Cases to justify the implementation of the new technologies that enable Manufacturing 4.0 are becoming easier to put together. Applying the Industry 4.0 principles can be a double-dip for Manufacturing companies as it helps them improve their own operations and bring inefficiency in the manufacturing of customer products.

• Some of the top areas for innovation are the Internet of Things, Analytics and Machine Learning/Artificial Intelligence. The intelligence provided by these technologies makes the organizations proactive as compared to reactive, which has a direct impact on cost. Although these technologies have been around for a while and can be beneficial for almost all industries, in the case of Manufacturing they can have an exponentially positive effect.

Challenges:

Most of the Chemical Industries are aiming to gain long-term sustainability and profitable growth and have to focus on critical success factors, including:

  • • Gaining maximum return on assets while increasing margins and profitability.
  • • Supply chain efficiency while improving delivery accuracy to the maximum level.
  • • Order accuracy, on-time delivery, and customer retention improvement.
  • • Business implications of strategic decisions understanding
Innovation:
  • • With IoT becoming mainstream, there is a great opportunity for the Manufacturing Industry to improve their own Operations and the Value they offer to their customers through the increased capabilities of the products they sell. IoT would allow for a fully connected shop floor, where every machine (or part of a machine), production line, etc. would be able to report a series of measures, from location to yield, temperature, status, etc. in real-time would, in turn, translate into early identification of potential issues.

 

  • • With the right set of Analytics capabilities and a relevant set of KPIs, all this data can be collected in real-time and would allow for immediate action. Problems with yields, operating speeds, calibrations, etc. can be detected and adjusted in a much-reduced cycle-time, avoiding costly reprocessing and schedule breaks.

 

  • • This alone has tremendous value in manufacturing operations. Now, when this is paired with Machine Learning and Artificial Intelligence, the value grows exponentially, as it will allow to automate and fast forward the detection of this situation, but would also enable the automation of predictive analytics, where predictive maintenance or service of machinery and equipment can be done before more obvious symptoms are present, driving and even further increase in overall plant efficiency and utilization.

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