How will big data affect lean manufacturing?

Big data and artificial intelligence (AI) have been increasingly important in many industries. With the ability to streamline production processes and maximize efficiency, they also have the potential to help lean manufacturing in many ways. In the coming years, big data is expected to play such a critical role in manufacturing that up to 47 percent of lean manufacturers believe that without big data and AI, their business models will become obsolete within three years.

What is Big Data?

Big data refers to large volumes of data that a company deals with on a daily basis. Big data analytics is the process of breaking down that data into more manageable and meaningful segments. Big data is often used to automate and improve lean manufacturing processes using artificial intelligence (AI), which supplements or replaces human labor.

Reducing Waste

Manufacturing companies like C Tek continually strive for ways to maximize efficiency, which necessitates eliminating waste. Big data can help remove waste, and in turn improve efficiency, by identifying the most economical and practical solutions available to improve and streamline the manufacturing process.

Better Response Times

For companies involved in the production of goods, response time and support for customer concerns and inquiries is generally slow compared to other sectors. AI and data analytics, however, can help companies respond faster to customer concerns, which allows them to make all necessary improvements more quickly and make their processes more lean.

Preventative Maintenance

Problems with equipment and machinery can cause delays in production and product delivery, which in turn can negatively impact customer service and a company’s bottom line. Big data can use technology and software to identify problems with equipment and machinery much faster than humans, which in turn allows systems to remain operational and reduces downtime. Specifically, it involves adding sensors to machinery to monitor changes to hardware and performance that indicate problems. Those issues are addressed more rapidly, which decreases downtime and causes fewer disruptions to the production cycle.

Compliance and Transparency

By teaching employees how to use machine monitoring equipment and software, advanced technology improves compliance, traceability, and transparency. It can also track usage scenarios, facilitate training for using various types of equipment on the manufacturing floor, and ultimately create a safer and more secure work environment for people and machinery. Production volume and quality both benefit as a result.


With all the advantages that it provides to a company, big data ultimately creates a higher level of quality and customer satisfaction. Incorporating software and analytics into the manufacturing process provides a clear picture of performance and quality across the development and supply chain. This allows companies to identify and address areas that need to be fixed or modified to minimize waste and maximize efficiency in order to deliver higher-quality products and services.

To date, many companies in manufacturing have already started to incorporate big data and AI into their business practices. Nearly 50 percent already use a defined digital strategy, and about 80 percent have already launched an IoT initiative. For recommendations on using big data in lean manufacturing, ask the experts at C Tek.