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In the modern data-driven economy, competing successfully and making sound investment decisions is a competitive endeavor that is also costly. It is for this reason that you are likely to hear discussions in professional business circles about big data and big data analytics. In the manufacturing sector, manufacturers look for ways that drive production, enhance efficiency, and increase innovation. This is where big data becomes highly useful. Big data allows companies to achieve productivity, gain efficiency in operations, and uncover new insights that drive innovation. With big data analytics, manufacturing companies can get information and patterns that will enable them to improve their processes, efficiency of supply, and identify aspects that affect production.

Below are some ways in which big data is used in improving production.

  1. Ensuring asset performance and efficiency

Profits in manufacturing rely mainly on the maximization of the value of assets. As such, the performance of assets can increase productivity. Reducing asset breakdowns can reduce inefficiencies resulting in the prevention of losses. Due to these reasons, manufacturers focus on maintenance and, in turn, try as much as possible to improve the performance of assets. Data from machine logs can be used to measure asset performance. With the internet of things (IoT) now in use in the industry, connected assets will allow performance to be measured in real-time. This is an excellent achievement for producers.

  1. Improving processes in production and supply chain

In the world that is increasingly getting interconnected, manufacturing processes and supply chains have become increasingly complicated and long. This has increased the need to shorten these processes and optimize supply chains to make them effective. This is made possible by big data analytics.

With analytics, manufacturers can choose a specific area of the supply chain or production and examine it in detail within a very short time. The analysis allows them to account for specific activities one at a time as well as production tasks. With this, manufacturers can identify bottlenecks in operations and components of manufacturing that needs to be replaced. Big data analytics can be used to reveal dependencies. This enables manufacturers to improve their production processes and, in the process, come up with alternative plans that will address the problems.

  1. Enhancing product customization

Big data analytics is changing product customization by making it possible to predict the demand for the products in the market. Unlike back in the day when manufacturing of products was focused on the scale rather than the product itself, the product has become a center of attention for modern manufacturing companies today. Big data allows manufacturers to detect changes in the behavior and needs of customers, therefore giving manufacturers lead time and opportunity to stay ahead of the game. Tools that allow engineers to gather, analyze, and visualize feedback from the customer almost in real-time have been developed. These tools allow them to identify areas that need to be tweaked in the production process to satisfy the customer and increase profits.

  1. Warranties and recalls

Recalls and warranty issues are among the leading worries for manufacturers. These issues can spiral dangerously if they are not tracked and addressed on time. Big data can help find out potential areas of weaknesses in manufacturing processes and correct them before they even occur. This will not only save money but will also make product marketing simple.

Generally, if big data and big data analytics are used well, they can boost manufacturing by introducing critical aspects of efficiency and allow manufacturing executives to make sound decisions. It gives them a competitive edge and will increase profit margins, an essential component for survival.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief


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