Big Data & Manufacturing

Be ‘4th Industrial Revolution Ready’ with SkillUp Online

Discrete Manufacturing & Big Data

Discrete Manufacturing is the industry where distinct items are produced; it could be automobiles, furniture, toys, smartphones, and airplanes etc. The manufactured product in this discrete manufacturing industry is simply identifiable and distinct from the process manufacturing industry’s products which are not easy to identify.

Over the years discrete and high technology & semi-conductor companies have adopted lean techniques and Six Sigma to accelerate production, maximize throughput, rationalize costs and minimize variability. With emergence of Industry 4.0 (IoT) the environment is undergoing transformation. Big Data generated through connected cyber physical devices drives simulation and simplifies the operations. Advanced tools consume data from various sources and enhance every aspect of manufacturing: Product Lifecycle Management, Improve batch processing time to Customer Experience!

Why Big Data Cannot Be Ignored
  • Research & Development: Big Data boosts R&D productivity significantly. Access to real time information across domains help to accelerate product innovation. Feedback on proto types and products from customers is real time as well. This helps improve the Product Design features at a faster pace.
  • Industry 4.0 Framework: IoT compliments Six Sigma and lean manufacturing techniques. It helps in optimising production, waste management and drive continuous improvement. Big Data platform serves “Early Warning” and hence minimizes scrap and rework.
  • Value Based Pricing: Big Data is now enabling manufacturers achieve “Value Based Pricing”. Big Data enables identify potential markets and undertake segment analysis for business opportunities, competitive strength and customer sentiment and use combined information help make an informed decision.
  • Multivariate Analysis: Big Data helps discrete manufacturers non-production time of production equipment and supports enterprise asset management department to minimise it.
Challenges
  • Manufacturing companies have to find a way to handle and process the unprecedented amount of data. 33% of data generated could be useful, however only 0.5% is available for analysis. Current production standards, systems and workforce are not prepared to handle the Big Data challenge.
  • Bringing IoT capability to Legacy Manufacturing Equipment: Manufacturing equipment lasts nearly from 10 years to 20 years. While they were ahead of their time when they were designed but most of them do not have IoT Plug In capability. This is a major show stopper for Manufacturing to implement Big Data Tools in their processes.
  • Infrastructure for ever growing data: Manufacturing facilities tend to have many devices that produce more data – Big Data. Dealing with Big Data is complex. Most manufacturers are interested in how can it give them better insights while they do not have proper Big Data Analytics skills?

Smart Manufacturing Challenges

The following are the challenges:

  • Multiple Types of Data and their Lifecycle Management.
  • Defining Data Processing Architecture.
  • Prescriptive Data Analytics in Industrial Plants.
  • Data Protection & Security Policy Definition and Implementation.

Advantages of an upskilled Workforce

  • An upskilled workforce will be able to easily manage Big Data challenges to benefit the business by reducing cost, improving production capability, effectively predict machine failure for preventive maintenance and more.
  • Expert production specialists with training on how to make best use and analysis of the Big Data will set your organisation to adopt Industry 4.0 framework easily. Also reap rewards significantly and quickly.

How Can SkillUp Technologies help you leverage Big Data?

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