Imagine a world where smart systems, Internet of Things (IoT) sensors, and robotics combine to automate large areas of manufacturing, linking wired and wireless networks throughout the world in the making of products, and relying on both structured and unstructured big data to get the job done. McKinsey & Company describes smartmanufacturing as a “type of information system–through sensors and actuators embedded in physical objects…[where] processes govern themselves, where smart products take corrective action to avoid damages and where individual parts are automatically replenished.”

Realizing the potential of a total manufacturing transformation with use of IoT big data, Germany initiated its Industry 4.0 government initiative to spur its industrial sector. Dependent upon real-time big data for driving and making decisions in the factory, Industry 4.0 represents, according to pundits, the “fourth industrial revolution” — following the steam engine, the conveyer belt, and the first phase of IT automation. In this world, multiple factories, logistics providers, etc., will interconnect with each other in a system of people-originated and IoT big data automation — all controlled by a central system “back plane” that is capable of synchronizing and orchestrating all events throughout the supply chain and giving everyone involved full visibility of what is going on.

To execute the smart manufacturing vision, enterprise systems must be modified so they can interface with and monitor IoT sensor-based technology, along with a host of disparate manufacturing, logistics, procurement, order, and other systems that must be integrated into a single back plane system. From an IT perspective, the task can be daunting. From a vendor management perspective, there can also be looming challenges, as some vendors will be more prepared than others to participate in the effort.

Equally important will be the need to bring together the big data team with the standard data team, because for Industry 4.0-style manufacturing to work, both big and standard data must work together and be tightly integrated. This means getting both data teams engaged in a joint project so information flows can be architected that draw upon both standard and big data to drive the automation needed to run the factories. If factories are spread across different suppliers and geographies, there will also be a need to import that big and standard data architecture to others who are part of the manufacturing supply chain.

The good news is that industry standards are emerging for big and standard data interfaces that will facilitate smart manufacturing information flows.

In industries like food and beverage, sensors that generate machine-driven information and automatic alerts already are widely used to measure the temperature and the humidity of containers that food products are shipped in, and also to track shipments from their points of origin to their final shipping destinations.

“The presence of standards and regulatory compliance requirements is one of the major drivers for the implementation of sensor systems,” said V. Sankarnarayanan, a Frost & Sullivan senior industry analyst in measurement and instrumentation. “Governments across the globe have strict laws that mandate the use of sensors and other electronic devices that sense the risk involved in food contamination.”

For big data, the move to smart manufacturing systems will be transformational. Big data will be called upon to “run things,” and not just to deliver analytics.

“Tasks that are currently still performed by a central master computer will be taken over by components,” said Peter Post, head of corporate research & program strategy at Festo. “These will network with one another in an intelligent way, carry out their own configuration with minimal effort and independently meet the varying requirements of production orders.”

As big data and IoT remakes factories into optimized and highly automated plants, goods will achieve greater speeds to market, with stepped up profits for companies since more goods can be routed to market faster. Progressive companies are already investing in IoT-driven systems, which they believe will enable faster responses to changes in consumer demand and product innovation. This potentially opens up greater market opportunities for companies and more options for consumers — which benefits everyone in the value chain.

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