Digital Manufacturing: Definition and Examples

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Digital manufacturing is an approach to manufacturing that uses computer systems to improve machines, processes, and productivity. Here’s what you need to know.

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As digital technologies have increased in importance in many industries around the globe, computer-based tools and systems are also being used to enhance manufacturing operations. With these technologies, 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 digital transformation of the manufacturing industry enables companies to streamline production processes and increase competition in the global marketplace.

Read on to learn all about digital manufacturing, including what it is, benefits, examples, and careers in digital manufacturing.

What is digital manufacturing?

Digital manufacturing is an integrated approach to manufacturing that uses computer technologies to improve manufacturing operations. Manufacturing facilities are increasing the amount of automated tools on the ground, so 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 Deloitte, digital manufacturing investments have led to an average increase of 10 percent in production output, 11 percent in factory capacity use, and 12 percent in labor productivity [1]. McKinsey reports even higher numbers, 30 to 50 percent reductions in machine downtown and 15 to 30 percent improvements in labor productivity [2].

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

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Introduction to Digitial 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 to resource management to customer satisfaction.

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

  • Smart factory: With the use of 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 that processes can be integrated, inventories can stay lean, and customer demands can be satisfied.

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 that can be connected to each other to provide data analytics and visibility, speed up 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 detailed control and insight over the supply chain, inventory levels and delivery statuses can be optimized to reduce costs at all levels of the manufacturing value chain.

Examples in the real world

The concept of “digital manufacturing” can be difficult to envision without examples. Here, we explain how two tools, big data analytics and cloud computing, are used 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, so they can ensure operational efficiency and reduce energy consumption. Engineers can then mine the data to understand why certain equipment modes fail, and use predictive analytics to continuously make adjustments to maintenance schedules.

Cloud computing

The aerospace industry is using 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 different vendors. Cloud computing tools enable suppliers to collaborate with efficiency: 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 labor. Boeing’s recent all-virtual design reduced time to market by over 50 percent [3].

Jobs within digital manufacturing

If you’re interested in digital manufacturing, there are many career paths that 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 the creation and implementation of an entire multi-year manufacturing strategy and plan.

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

  • Cybersecurity analyst: Cybersecurity professionals (can also be manager or lead) are in charge of protecting computer networks from cyber attacks 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 the hardware and software in a computer system.

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.

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Article sources

1

Deloitte. “2019 Deloitte and MAPI Smart Factory Study, https://www2.deloitte.com/content/dam/insights/us/articles/6276_2019-Deloitte-and-MAPI-Smart-Factory-Study/DI_2019-Deloitte-and-MAPI-Smart-Factory-Study.pdf.” Accessed September 1, 2022.

Written by Coursera • Updated on

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