Digital Manufacturing: Definition and Examples

Written by Coursera Staff • Updated on

Digital manufacturing is an approach to manufacturing that uses computer systems to improve machines, processes, and productivity. Learn about its benefits while exploring real-world examples, and discover how to apply digital manufacturing to your career.

[Featured Image]:   A male, wearing a green shirt and a female wearing a black and white patterned top, sitting in front of her laptop, are meeting to discuss the latest strategy.

As digital technology has increased in importance in many industries globally, computer-based tools and systems are also being used to enhance manufacturing operations. With this technology, real-time analytics can reduce bottlenecks, decrease inventory, shorten manufacturing times, and more.

Often referred to as manufacturing’s fourth revolution, or Industry 4.0, the manufacturing industry's digital transformation enables companies to streamline production processes and increase competition in the global marketplace.

Read on to learn about digital manufacturing, including its benefits, examples, and careers in digital manufacturing.

What is digital manufacturing?

Digital manufacturing is an integrated approach that uses computer technology to improve manufacturing operations. As manufacturing facilities increase the number of automated tools on the ground, companies need digitized systems on the business end to monitor, analyze, and model all of the machines to optimize the process. The goals of digital manufacturing include efficiency (“lean-ness”), flexibility, design, and integration.

According to McKinsey, digital manufacturing investments have led to 30 to 50 per cent reductions in machine downtime and 15 to 30 per cent improvements in labor productivity [1].

Watch this video to learn more about digital manufacturing and design technology:

Types of digital manufacturing

There are three main types of digital manufacturing. Each corresponds to a different part of the manufacturing process, from product design to production, resource management, and customer satisfaction.

  • Product life cycle: The product life cycle begins with engineering design and moves on to sourcing, production, and customer service management. At each step, data analytics can account for revisions and monitoring that can impact the entire life cycle.

  • Smart factory: With smart machines and sensors, workers receive real-time data about the functions they are performing. This feedback forms the connection between operations teams that monitor the machines and the information technology (IT) teams that deal with the back-end systems like SAP. Both use business intelligence (BI) tools to analyze, track, and improve performance.

  • Value chain management: The point of value chain management is to minimize resources and continuously assess value at every stage of the chain so organizations can integrate processes, keep inventories lean, and satisfy customer demands.

Benefits of digital manufacturing

Digital manufacturing has many benefits for the manufacturing industry as it streamlines and evolves processes to suit the 21st century.

  • Increased efficiency: An integrated, digitized manufacturing process eliminates errors that may arise due to incorrect data, which is common with manual or paper-based systems. 

  • Faster innovation: Advanced technologies, including updated machinery and IT systems capable of connecting, can provide data analytics and visibility and accelerate innovation.

  • Customer satisfaction: Digital manufacturing increases brand awareness and loyalty because businesses can remain in tune with customer needs and wants.

  • Cost reduction: With more precise control and insight over the supply chain, businesses can optimize inventory levels and delivery statuses to reduce costs at all levels of the manufacturing value chain.

Examples in the real world

The concept of “digital manufacturing” can be challenging to envision without examples. Here, we explain how organizations use two tools, big data analytics and cloud computing, in the real world: 

Big data and analytics tools

Data analytics tools like AI and machine learning can help break down the manufacturing value chain into actionable insights for demand forecasting. 

For example, a car manufacturer uses these supply-network management tools to visualize the flow of raw materials and manufactured parts through the network, ensuring operational efficiency and reducing energy consumption. Engineers can then mine the data to understand why certain equipment modes fail and use predictive analytics to adjust maintenance schedules continuously.

Cloud computing

The aerospace industry uses cloud computing to integrate its complex supply network. To manufacture a jet turbine engine requires hundreds of individual parts, some of which may be produced in-house and others outsourced from vendors. Cloud computing tools enable suppliers to collaborate efficiently: Engine makers can share 3-D models of their design and solicit pricing, delivery, and quality information from each supplier. This transparency reduces risk and labour. Boeing’s recent all-virtual design reduced time to market by over 50 per cent [2].

Jobs within digital manufacturing

If you’re interested in digital manufacturing, many career paths cover the spectrum of business operations, supply chain, engineering, and cybersecurity roles. Here are some jobs that play an important role in digital manufacturing:

  • Digital manufacturing manager (or specialist): An individual skilled in creating and implementing an entire multi-year manufacturing strategy and plan.

  • AI or machine learning engineer: Engineers create predictive analytics and program robotics to assist in the manufacturing process.

  • Supply chain analyst: Analysts use data to conduct demand forecasting and planning, eliminating errors, boosting efficiency, and decreasing time and costs.

  • Cyber security analyst: Cyber security professionals (can also be managers or leads) protect computer networks from cyberattacks and unauthorized access.

  • Business intelligence analyst: Business intelligence (BI) analysts help make sense of the data and provide companies with actionable insights. Management consultants are similar in that they take on projects to create leaner, more digitized processes in manufacturing, production, or supply chain outcomes.

  • Cloud architect: A cloud architect is responsible for an organization’s cloud computing system, developing the application design and systems for managing and monitoring the cloud system.

  • IT technician: IT technicians typically install, troubleshoot, and fix computer hardware and software.

Learn digital manufacturing and design technology.

Start your career in digital manufacturing. Designed with input from the manufacturing industry, the Digital Manufacturing & Design Technology specialization from SUNY-Buffalo provides the knowledge and skills needed to succeed in the industry.

Article sources


McKinsey & Company. “Preparing for the next normal via digital manufacturing’s scaling potential,” Accessed June 4, 2024.

Keep reading

Updated on
Written by:

Editorial Team

Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact...

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.