Manufacturing

crf

The purpose of this use case is to produce high quality products with specific minimized time delivery while increasing product competitiveness and client/supplier satisfaction. The I-BiDaaS framework will analyse and correlate industrial/manufacturing data originating from various automotive production processes (such as data from sensors, transportation system, infrastructure, transportation suppliers, components suppliers, logistics flows, data from local sensors related to the consumption of components) and will minimize response and product production times. I-BiDaaS solution will be able to combine all this information and proceed to real-time re-planning of the procedures needed so that the manufacturing process continues without interruption and avoid excessing costs and financial damage.

 

Manufacturing has come a long way since the days it involved slow, tedious production processes. The invention of the assembly line in the early 20th century signalled the beginning of a manufacturing revolution, one that matured with the integration of lean manufacturing in factories across the globe. Automated processes and mechanization have resulted in the generation of large amounts of data, more than most companies know what to do with. Despite the many benefits companies stand to enjoy from big data, many aren’t taking full advantage to transform operations.

Much of the IT infrastructure on the factory floor was developed before the cloud, inexpensive storage, and ubiquitous connectivity. Manufacturing is also much more complex compared to other industries that have implemented big data techniques. Additionally, factory production can’t run on beta versions of software, as this may result in injury or death. Companies must also know how, when, and where to mine data, and what the right analytical tools to produce meaningful data are, therefore real-time data analytics tools are essential.

manufacturing