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The Impact of Big Data and Analytics on Manufacturing [Infographic]

December 15, 2016

7:00 pm

As you may know, big data and software analytics have had a tremendous impact on modern industries. Industry disruptors like Google, Tesla, and Uber have used the many benefits presented by big data to expand into new markets, improve customer relations, and enhance the supply chain in multiple market segments.

IDC Research projects that revenue from sales of big data and analytics will hit $187 billion in 2019, up from the $122 billion recorded in 2015. One of the areas that stand to benefit greatly from this growth is the manufacturing industry, with revenues from this industry projected to reach $39 billion by 2019.

The manufacturing industry has come a long way from the age of craft industries. Back then, the manufacturing process involved slow, tedious production processes that yielded a few products at a time. The invention of the assembly line in the early 20th century signaled the beginning of a manufacturing revolution, one that matured with the integration of lean manufacturing in factories across the globe.

Effects of Big Data on Manufacturing Companies

IT has played the biggest role in this revolution. Automated processes and mechanization have resulted in the generation of large amounts of data, more than most manufacturing companies know what to do with. For instance, a factory sensor can generate thousands of data points when scanning for defects along the assembly line.

When fed into analytical software, such data can yield valuable information to improve manufacturing processes and increase productivity. Some notable effects include:

Cost Savings

Big data can help change the way manufacturing processes are carried out. The information produced data that can help reduce the cost of production and packaging during manufacturing. Additionally, companies that implement data analytics can also reduce the cost of transport, packaging, and warehousing, which can in turn help cut inventory costs for massive savings.

Improved Quality and Safety

Many manufacturing companies now use computerized sensors during production to sift through low-quality products along the assembly line. With the correct software analytics, companies can use the data generated from such sensors to improve the quality and safety of products instead of simply discarding low-quality products after production.

Many vehicle manufacturers are subjecting their massive pools of data to software analytics to help generate simulation models before production. These simulations help reduce risk while improving the quality of the vehicles being introduced into the market.

Improving Workforce Efficiency

Manufacturing companies can also use big data to improve management and employee efficiency. Big data analytics can be used to study error rates on the production floor and use that information to assess specific areas where employees are excel and where they are under-performing.

The same set of data and information can be used to improve production speed on the production floor, especially for manufacturing plants that often work with large volumes. Analyzing the data that uses software analytics can help managers single out product.

Better Collaboration

One of the perks of having an IT-based data collection and analysis infrastructure is improved information flow within the manufacturing organization. The synergistic flow of data and information within management, engineering, quality control, machine operators, and other facets of the organization enable them to work efficiently together.

The data-driven environment is also primed for quick feedback mechanisms, which enables each member of the workforce to implement changes quickly and effectively.

Challenges for Manufacturing Companies

Despite the many benefits companies stand to enjoy from big data, many manufacturing companies aren’t taking full advantage of such data to transform operations.

Part of the reason is that manufacturing, being an old-school industry, has traditionally been slower to integrate innovative IT solutions compared with software-centric companies. Much of the IT infrastructure on the factory floor was developed before the cloud, inexpensive storage, and ubiquitous connectivity were born, which explains why most manufacturing companies have been slow to innovate.

Manufacturing is also much more complex compared to other industries that have implemented big data techniques. Shutting down assembly lines to implement software fixes can result in huge losses that can bankrupt the company. Additionally, factory production can’t run on beta versions of software, as this would possibly result in death or injury in plants dealing with vehicles or other sensitive equipment.

Companies must also know how, when, and where to mine data and what the right analytical tools to produce meaningful data are. In the US, there is dire need for over one million data analysts and managers who can help make sense of big data.

Despite these and other real stumbling blocks, big data stands to benefit manufacturing in multiple ways. The manufacturing sector is worth about $11 trillion, with much of the sector still lagging behind in terms of uptake of digital technologies.

Big data and the accompanying analytical software can help take this industry to unimaginable levels of growth within the coming years. Check out this big data infographic for an illustrate look into the issues and future of big data.

 

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Vikas Agrawal is a start-up Investor & co-founder of the Infographic design agency Infobrandz that offers creative and premium visual content solutions to medium to large companies. Content created by Infobrandz are loved, shared & can be found all over the internet on high authority platforms like HuffingtonPost, Businessinsider, Forbes , Tech.co & EliteDaily.

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