Digital Manufacturing: Definition, Benefits, Methods, Examples

Digital manufacturing refers to the use of a computer-based system consisting of various tools and software for simulation, analytics, 3D visualization, and business and manufacturing collaboration. Often, these tools and software programs are cloud-based. They enable a manufacturer to connect and integrate manufacturing operations into a streamlined whole. With this centralized computer system, manufacturers can have a seamless, connected flow of data related to all their processes and products. Data recorded by the IIoT devices can be analyzed to help enhance product design, optimize fabrication and supply chain logistics, and improve customer satisfaction. As a result, manufacturers are likely to see reduced operating costs, shortened lead time and time to market, and improved product quality.

Three primary aspects of a manufacturing business are impacted by a transition to digital-based operation.

1. Product Life Cycle

The product life cycle starts with the initial engineering designs, iterations on those designs, and design validations. It then transitions to the production planning phase, which includes material sourcing and procurement, product fabrication, and ongoing customer service. It's important to consider how digital manufacturing strategies can contribute to each step in the product life cycle.

2. Smart Factory

A smart factory is a digitized manufacturing facility that uses an interconnected network of communication mechanisms, machines, and computing power. Many of today's factories are already equipped with high levels of automation, with machines like cameras and barcode scanners. However, these devices are not interconnected. The data independently collected by each separate system must be manually interpreted and coordinated between devices. 

With the use of an interconnected array of smart machines (machines equipped with technologies like artificial intelligence and machine learning) and IIoT sensors, manufacturers are provided with real-time data about each process that is executed in the factory. An automated feedback loop is created between the data collection devices, the computer systems that analyze the data, and the machines that fabricate the products. Therefore, these smart machines aren’t just collecting and analyzing data, but are actively learning the optimum manufacturing parameters from experience as fabrication machine settings are automatically adjusted. Smart factories undergo constant, automated continuous improvement due to the power of interconnected digital devices. By combining operations technology with information technology, manufacturers obtain greater visibility into all their factory’s processes and machinery. This allows them to dramatically improve efficiency and quality.

3. Value Chain Management

The value chain management aspect of digital manufacturing concentrates on minimizing resource use and assessing the value of materials and unfinished products at each stage of the manufacturing chain. Its purpose is to help manufacturers identify bottlenecks in their processes, decrease inventories and stay lean. By using IIoT devices and smart machines, manufacturers can effectively monitor the flow of materials throughout the factory and rapidly adjust operations to improve efficiency and respond to unforeseen challenges.

Digital manufacturing has presented manufacturers with a solution to improve product quality, increase profitability, and enhance customer satisfaction. It allows manufacturers to harness the power of digital devices and reap its many benefits. Some of the advantages of digital manufacturing include:

1. Increased Efficiency: One of the biggest advantages of digital manufacturing is the increased efficiency of a manufacturer’s processes and logistics. A robust, well-integrated, digitized manufacturing operation optimizes production processes and cycle times leading to greater profitability.
2. Continuous Improvement: Machine learning and automated feedback control loops in digital manufacturing ensure that manufacturing processes are always being improved. Smart devices can automatically identify and resolve issues in processes by changing various machine parameters without human intervention. The range of the types of data that digital manufacturing can deliver to operations teams allows companies to effectively plan process improvement initiatives. Additionally, digital manufacturing helps improve product quality. It is a direct result of increased efficiency and augmented manufacturing processes made possible by machine learning. 
3. Enhanced Customer Satisfaction: Digital manufacturing leads to increased efficiency which results in improved product quality. It makes sense that increased efficiency and better quality translate to enhanced customer satisfaction. Digital manufacturing also helps manufacturers to quickly adapt to changing demands of customers.
4. Faster Innovation: Digital manufacturing makes data related to all of a factory's processes and materials easily accessible to development engineers. Manufacturers can analyze the data to quickly identify flaws in their designs and processes. This leads to innovation and better-designed parts being realized on a much quicker timescale than simple manual and paper-based manufacturing operations.  
5. Reduced Costs: More data availability over machinery and processes allow manufacturers to reduce costs due to improved efficiency at each stage of the manufacturing process. For example, manufacturers can accurately forecast raw materials that a machine can process per day resulting in the reduction of inventory levels to optimum levels.

Converting a manufacturing operation from a traditional system to an automated, digital system can be challenging. There are several factors manufacturers must consider to ensure a successful transition. The steps below describe how to successfully implement digital manufacturing infrastructure into an existing manufacturing operation.

1. Define the need and goals for digital manufacturing: Before beginning a transition to a digital manufacturing platform, define the goals you’d like to achieve by making these changes. Common goals include improved productivity, higher sales, increased labor satisfaction, and reduced waste—among other things. Once the goals have been established, think about what digital manufacturing capabilities will be required to achieve those goals. 
2. Design the infrastructure: Once goals have been established, you can consider exactly which features will help you reach them. For example, if improved productivity is particularly important, you may consider emphasizing ease of use and robust integration of tools and devices to accomplish this. On the other hand, if scale-up is more important, you may consider an easy-to-replicate digital architecture. Additionally, if compatibility with existing IT infrastructure is desired, it’s a good idea to consult with a platform provider to ensure seamless implementation. Platform providers will help establish functional and technical requirements for the new infrastructure. Alternatively, manufacturers themselves can design their own digital manufacturing platforms as well.
3. Implement the digital manufacturing infrastructure on a small scale: Before the new infrastructure is implemented factory-wide, a preliminary pilot phase should be conducted to test the effectiveness of the platform. Most organizations will introduce the new platform into the workflow of just one process to get a feel for how it will work. During this preliminary phase, it’s important for company leadership to explain the potential benefits the platform has to offer for not just the company, but the individual employee who will have the opportunity to skill up with the latest technology. Additionally, leadership should be well-trained enough to understand the system and should be attentive to their staff’s feedback on the platform. Once the platform has been tested enough and its effectiveness has been verified, it can slowly be expanded to the entire factory.
4. Expand the digital manufacturing infrastructure factory-Wide: Once the preliminary test phase has been completed, operations engineers can begin slowly expanding the platform to the entire factory. By methodically expanding implementation production line by production line, a manufacturer can verify successful operation for each new area of implementation. As the platform’s success is verified and brought up to speed across the entire manufacturing space, company leadership should continue emphasizing to employees the benefits of the platform. Change is not always easy, and many employees may have trouble adjusting to the new platform at first. Therefore, it’s essential for managers to set an example by using the new functionality themselves, and by clearly communicating the benefits it offers.
5. Continuously improve processes through the digital manufacturing platform: Manufacturers can begin seeing the benefits digital manufacturing has to offer as soon as the platform is implemented factory-wide. At this point, manufacturers can begin exploring new ways to apply the new capabilities to improve efficiency. Maintaining documentation on the historical baseline for various key performance indicators like machine runtime, fabrication cycle time, and machine downtime allow manufacturers to easily compare the performance of a machine with others. This comparison produces a unique opportunity for manufacturers to improve processes and harness the power of digital manufacturing.

Digital manufacturing technology combines information technology (IT) with operations technology (OT) to create a well-connected and robust smart factory. Digital manufacturing is present in many applications today and its use only continues to grow. Below are four examples of digital manufacturing in the real world:

1. Industrial Internet of Things (IIoT

The “Internet of Things” refers generally to interconnected devices that can collect, interpret and transmit  data. The Industrial Internet of Things (IIoT) is the exact same thing—but for industrial purposes. IIoT is a series of sensors and devices that supply real-time data related to every process on a factory floor. This allows for increased visibility of machine performance and the supply chain logistics which consequently provides manufacturers with the data needed to effectively reduce downtime and inventory and improve product quality. IIoT sensors can be used to monitor virtually anything—from factory floor machinery to lights and HVAC systems.

2. Big Data Analysis

Another application of digital manufacturing in the real world is big data analysis. With so many connected devices providing massive amounts of data, it would be exceptionally difficult for an individual to sift through and analyze all of it. Instead, data analytic tools like machine learning and AI help interpret and analyze big data to provide manufacturers with the insight needed to strategically plan maintenance schedules, curate demand forecasts, and allocate materials. Additionally, manufacturers can wield big data analytics to increase efficiency, reduce lead times, and ultimately improve product quality.

3. Cloud Computing

Cloud computing is the foundation of digital manufacturing that makes IIoT and big data analytics possible and effective. Cloud computing allows users to access computing resources (such as data storage, applications, development tools, etc.) via the internet, without the need for additional software or hardware to be maintained on the user’s device. The on-demand access to computing resources via the cloud allows manufacturers to quickly retrieve, analyze, and transmit data. Computationally intensive tasks such as machine learning and simulation can also be done on the cloud—effectively reducing costs and increasing manufacturing efficiency. Because computing resources can be accessed on-demand anywhere, manufacturers obtain a high degree of mobility for acquiring and analyzing data.

4. Robotics

Though robotics has been present in manufacturing environments for years, digital manufacturing makes automation much more efficient and effective at completing sophisticated tasks. While previous systems may have required a human operator, digital manufacturing enables robotics to automatically complete tasks through machine learning. Whether it's mechanical arms assembling parts or autonomous robotic vehicles handling factory logistics, robotics present in digital manufacturing centers evaluate and optimize themselves.

There are many career paths within the field of digital manufacturing,  covering the full spectrum of manufacturing activities, from business operations and supply chain roles to engineering and cybersecurity. Below are some careers within the digital manufacturing discipline:

1. Machine Learning Engineer: Machine learning and AI engineers are responsible for designing the programs and predictive analytics of the robots that assist in manufacturing.
2. Supply Chain Analyst: Supply chain analysts use the big data transmitted and analyzed by IIoT devices to develop demand forecasts, helping to reduce waste, and lead times.
3. Cybersecurity Analyst: Cybersecurity analysts are responsible for the protection of sensor networks and devices in a digital manufacturing facility. Cybersecurity analysts protect manufacturers against cyber attacks and unauthorized users.
4. Business Intelligence (BI) Analyst: BI analysts interpret big data and use it to plan and gather business intelligence and use it for the benefit of all areas of a firm's operations.
5. Cloud Architect: Cloud architects oversee a manufacturer’s cloud computing systems. They design and develop the applications and systems used on the cloud and help bridge the gap between complex manufacturing problems and solutions in the cloud.
6. IT Technician: IT technicians are responsible for the installation, troubleshooting, and repair of various hardware and software in a particular business.

Digital manufacturing offers businesses a solution to improving product quality, enhancing customer satisfaction, and increasing productivity and efficiency all packed into one set of robust, versatile solutions. Manufacturers new to digital manufacturing can learn from the mistakes and trials of those who pioneered this new approach to manufacturing. Newer converts stand to benefit greatly from the competitive edge they will gain. As high-tech, digital devices become more prevalent, it’s only a matter of time before smart factories and digital manufacturing become commonplace.