Big Data

Smart Manufacturing: Can Big Data Help Improve Production and Efficiency?

Smart Manufacturing

Big data news has been highlighted for all the wrong news mostly. We can’t help it though. Things like the Cambridge Analytica scandal only seem to push forward the wrong side of big data technology.

But the larger picture is far bigger and less ominous. Big data tech news these days show that there is real interest in using the technology.

Since the first industrial revolution that witnessed large steam powered factories set up all over the world, mass production has always been about using the latest technologies. Today, firms are looking towards harnessing big data through smart manufacturing.

How Does Big Data Tech Help Manufacturing?

Smart manufacturing is all about using the latest and innovative technologies to make decisions that would not be possible by today’s human standard.

Artificial Intelligence (AI) and Internet of Things (IoT) are already being used in various fields to increase quality, efficiency and an overall better operational control. But the next big step is integrating big data to enhance the manufacturing process to a whole new level.

Large volumetric and unstructured, big data is all about analyzing and making sense of the data to extract meaningful information. This can be trends, any relationship between the data points and even patterns that would otherwise skip the eyes.

Considering that with IoT and even standalone computers and machinery used in manufacturing, there is tons of data being produced daily. With big data, not only can all of this be collected into a single storage, but can be analyzed to find deeper and hidden connections.

This can help manufacturers optimize their production, seek out bottleneck areas and gain insights on how to improve the processing.

Process Optimization

With decreasing cost of computing, big data can play a key role in optimizing processes of any manufacturing system. Proper analytics combined with real time addressing can seek out inefficiencies and even help in fine tuning production.

This can also help in avoiding large downtimes. Real time monitoring and big data, for example, can help management and production crew identify the subtle changes in machine characteristics and do preventive maintenance. The down time for maintenance will be much smaller than a breakdown repair.

Quality Check and Defects

Using an array of different sensors, manufacturers can utilize the power of big data analytics to detect defects in their products, at any stage of manufacturing. With early detection, they can adjust or correct the issues long before these are manually detected.

At a larger scale spreading over months and even years, the defects can be even pinpointed to causes that might never be identified.

Product Redesign

Big data analysis is not only useful on the processing floor, but it goes much down the supply chain. In fact, it goes to the end and touches the consumer. Customer feedback, with a proper campaign, can be massive data in itself.

Random and without much sense, the data can be broken down into meaningful trends and even identify popular features and reveal avenues of improving the product. Even things like knowing which locations show potential for customer growth can be extremely important in capturing more markets, establishing supply chains and reducing costs of reactive performance.

Predictive Maintenance

Not to be confused with preventive maintenance, predictive maintenance saves a lot of time and money if unwanted and unforeseen changes within machineries and processes are not detected. With big data collecting data sets such as temperature, speed, tolerances, etc., even a subtle difference offset from standard can reveal a much larger issue with the manufacturing machines.

With this, manufacturers can detect possibilities of breakdown much earlier. They can even look at the trends (both current and past) to determine a rough estimate of time left before a breakdown happens. This helps in scheduling the maintenance where there is minimum disruption to production and keep processes running as much as possible.

Supply Chain

With big data at their side, manufacturers can examine the complete supply chain, up to their suppliers.

Other things that they can look at include inventory management, finished goods storage and even schedule raw material orders based on what their data analytics show.

Big Data Analytics to Grow Much More

In other big data technology news, a research shows that the analytics market is set to grow beyond $745 billion before the end of the decade, showing a CAGR of 13.5%. 

Taking into account size, last year the North American big data analytics market was worth just above $101 billion. Even then, it is expected that USA’s rapid growth in the field will keep it at the forefront.

IoT, AI and other data collection and processing technologies are going to be crucial in helping big data analytic grow.

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