From Concept to Use Cases: Big Data Analytics in Manufacturing

Bhagyashri Kambale | March 07, 2022
FROM CONCEPT TO USE CASES
Big data analytics in manufacturing is all you need to improve your business's efficiency, quality, and productivity in today's data-driven industry. It helps you transform your business data into actionable analytics to make informed decisions on business processes and operations.

“Data is the new science. Big data holds the answers.”

– Pat Gelsinger, CEO at VMware

The significance of manufacturing industry data analysis is critical, and many manufacturers have recognized this and have started incorporating it into their manufacturing operations. According to Research and Markets, the manufacturing sector market was worth $904.65 million in 2019 and is predicted to grow to $4.55 billion by 2025.

In this article, we'll look at the importance of big data in manufacturing, its applications, and how some of the industry's major players are incorporating it into their manufacturing processes and operations.

Why Do Manufacturers Need Big Data?

Big data analytics in manufacturing helps manufacturers find new information and identify trends. This enables them to improve operations, increase supply chain efficiency, and identify variables that affect production.

Many leaders from the manufacturing industry recognize the importance of big data and have either started applying it to their business or are planning to do so.
  • According to a KRC research report, 67% of manufacturing executives considered investing in manufacturing data analytics, especially in the face of pressure to minimize costs in this volatile market.
  • According to MicroStrategy, 59% of organizations worldwide are using big data analytics.

Big Data: From the Past to the Future

Herman Hollerith invented the first punch card tabulating machine that marked the foundation of data processing. Hollerith's tabulating device was utilized to process data from the 1890 United States Census. Later that year, in 1911, he formed the Computing-Tabulating-Recording Company, which evolved into IBM. It is now based in Armonk, New York, with operations in more than 171 countries.

This international corporation develops computer hardware, software, and middleware, and provides hosting and consulting services in different sectors, ranging from mainframe computers to nanotechnology. The company is a significant research institution that has set the bar for the number of U.S. patents generated annually by a firm for the last 28 years (as of 2020). 

Companies Using Big Data Analytics 


Amazon

The enormous benefit of big data is its capacity to assist businesses in innovating and redeveloping their products. Essentially, big data has evolved to generate additional revenue streams by enabling innovations and product development. Before developing new product lines or redesigning old products, organizations begin by fixing as much data as possible.

How does Amazon make use of big data?
Most people are familiar with Amazon Fresh and Whole Foods Market. This is an excellent illustration of how big data can benefit the growth of innovation and product creation. Amazon uses big data analytics to get a foothold in a vast market. Amazon's experience in data-driven logistics enables the creation and achievement of more value. By focusing on manufacturing analytics, Amazon Whole Foods deciphers how customers purchase products and how suppliers engage with the store.

PepsiCo

Big data enables supplier networks to operate with increased precision, clarity, and insight. Suppliers achieve contextual insight throughout supply chains by utilizing manufacturing data analysis. Essentially, providers can overcome previous limitations using big data analytics.

How does PepsiCo leverage big data to optimize its supply chain?
PepsiCo is a consumer packaged goods company that depends mainly on massive amounts of data to operate its supply chain efficiently. The organization is committed to restocking the shelves of shops with the proper quantities and varieties of products. Clients give reports on their warehouse and point-of-sale inventory, which the company uses to reconcile and estimate production and shipment requirements. This way, the corporation guarantees that shops have the appropriate products, in the appropriate quantities, and at the appropriate times. Read our latest infographic to learn more about increasing the efficiency of your manufacturing business. 

Big Data in Manufacturing: Use Cases


Supply Chain Management

Big data allows manufacturers to track their products' actual position. The ability to track is one of the most important features offered by big data to manufacturers. Traceability is important since many products released by manufacturers are lost or hard to trace. Barcode scanners and radio frequency transmission equipment can set up a parcel's coordinates. These devices broadcast the product's location, pinpointing its exact location.

Identifying client needs is a challenge when predicting market trends. Big data assists by predicting client requests and assisting with product delivery timings. This type of forecasting can help businesses improve their profits and workforce by looking at their supply chain.

Production Management Once businesses have discovered market requirements, the same analytics for manufacturing can assist them in evaluating the volume of products necessary in the market. Previously, when big data analytics did not exist, businesses relied on human estimates, which frequently resulted in excess or insufficient production. This technique has been deemed obsolete because of its inaccuracy. Instead, organizations gain intuitive insights from the data they collect and analyze using big data analytics for manufacturing.

Machine Maintenance

When a company manufactures something, it intends to maintain its machinery, from how it currently runs to what changes are required to keep it working properly. These robots' sensors may continuously collect data. Device data helps firms determine when and how much maintenance a machine needs. Big data analytics can help manufacturers keep track of their machinery by assessing and improving their efficiency.

Daily Production

For a company to run properly, they must monitor their daily activities, production capacity, and financial performance. Big data analytics can help manufacturing organizations by giving intuitive insights from numerous sources. These sources include operating machines, databases tracking unit production, and employee records. This data can help corporations make profitable improvements.

Quality Assessment

Quality control is important in manufacturing since the products must be of the highest quality. Big data analytics can also help here by providing vital information about any changes in the development process.

Businesses recognize the need to utilize technological breakthroughs as manufacturing transforms. Big data analytics helps enterprises not only track and forecast market demands but also maintain quality measurements and standards. This ensures product quality and increases profitability for a manufacturer's products.

Final Word

We understand the significance of big data in manufacturing, and the sooner you start collecting data on your manufacturing processes, the sooner you can implement the latest advancements. Therefore, delve further into big data, data analytics, and data science services to assist your manufacturing organization in growing and blooming to the next level.

FAQ


Is data science the same as big data?

No, data science and big data are not synonymous. Big data collects varied and complicated data, whereas data science is a multidisciplinary area that tries to generate broader insights from data.

What purpose does data serve in manufacturing?

Manufacturing data provides a deeper insight into market trends, a complete grasp of client needs, and predicts future trends. In a nutshell, it includes everything necessary for manufacturing companies to maintain a competitive edge.

How are manufacturing data defined?

Manufacturing data refers to all data, information, materials, and documentation developed or generated in connection with the product’s manufacturing. This includes manufacturing and control data as well as additional data and documentation requested by or submitted to a Regulatory Authority.

Spotlight

Kinze Manufacturing

At Kinze Manufacturing, we live and breathe agriculture. We are farmers, too. That’s why Kinze is the recognized technology leader and innovator of row crop planters and grain carts. Since our founding in 1965, we’ve taken pride in our products and worked hard to bring the most reliable row crop equipment to farmers fields.

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