What Is Discrete Manufacturing?

What Is Discrete Manufacturing?

Factories involved in discrete manufacturing build parts and assemble them into subsystems and finished products. Both the production and assembly processes are categorized as discrete manufacturing.  

The processes deployed in discrete manufacturing are not continuous, so each one can be started or stopped individually. In many cases, processes can run at varying rates without interfering with overall production.

Examples of products that result from discrete manufacturing include vehicles, computers, furniture, appliances, and clothing. These items can often be disassembled when they are no longer needed, so their component parts can be refurbished, reused, and/or recycled.

Implementing Industry 4.0 technologies in discrete manufacturing—enabled by intelligent edge solutions—can lower costs, increase efficiencies, and reveal new advantages. As discrete manufacturing becomes more sophisticated and automated, businesses are capturing, analyzing, and acting on data across their operations faster and more effectively.

Discrete vs. Process Manufacturing

Manufacturing processes are grouped into two categories: discrete and process.

Discrete manufacturing processes include the production of individual parts as well as their assembly into a final product. Discrete manufacturing examples include automobiles, appliances, and consumer electronics.

Process manufacturing is associated with formulas and recipes and is used to produce beverages, chemicals, pharmaceuticals, and some consumer goods, such as toiletries and paper products. In process manufacturing, raw ingredients are combined and/or refined continuously or in batches.

Unlike discrete manufacturing, commodities produced by process manufacturing cannot typically be disassembled into component parts, although some end products can be recycled.

Discrete Manufacturing in Vertical Markets

An incredibly diverse array of products is produced with discrete manufacturing. Key markets include the most complex products and rely on supply chains that are also complex and multifaceted, with multinational sources. 

Five leading markets invest heavily in discrete manufacturing and new technologies that support production quality and efficiency:

• Automobiles and auto parts
• Electronics and computers
• Consumer goods
• Aerospace, aviation, and defense
• Machinery and heavy equipment

Each of these verticals is being shaped by the industrial intelligent edge. Their operations produce large volumes of data every day, which can be leveraged with near-real-time analytics to find ways to improve business outcomes.

Some Assembly Required

Discrete manufacturing includes both the production of the components themselves and their assembly into subsystems and finished products. 

Some discrete manufacturing processes have a long history, such as the assembly line established a hundred years ago by the Ford Motor Company. While assembly lines are still common in today’s automotive industry, most of the assembly tasks are now completed—or at least supported—by AI-enabled robots and other high-precision, computer-assisted manufacturing (CAM) systems and tools.

Audi provides one example of today’s approach to auto manufacturing. Working closely with Audi engineers and technicians, Intel created a scalable, flexible machine learning platform for Audi’s automated factory. This serves as a foundation for future innovations, enabling the company to increase efficiency and reduce costs.

John Deere, a leading manufacturer of agricultural equipment, is using Intel® AI and machine vision technologies to automate the welding process and control for defects, including porosity caused by gas that’s trapped in the weld.

Benefits of IoT in Discrete Manufacturing

Discrete manufacturing is evolving rapidly as manufacturers increase the level of automation enabled by AI, machine vision, real-time data analytics, and high performance computing in the cloud and at the edge. 
These and other advanced technologies merge the digital world with physical objects through IIoT. Starting with data capture and analysis at the edge, IIoT supports many advanced manufacturing functions at the heart of the Fourth Industrial Revolution, or Industry 4.0. 

As information technology (IT) and operational technology (OT) converge in these new platforms, manufacturers can connect data to operational systems in real time and synchronize supply chain, order management, and delivery functions with production systems. 

By generating a software-defined infrastructure that merges IT and OT, manufacturers can integrate key processes that were previously confined to data silos. This allows them to improve product quality through automated quality control measures, reduce waste by thorough process analysis, optimize costs, and spark new business opportunities by making critical data available to more people.

Smart factories involved in discrete manufacturing deploy AI, machine vision, advanced robotics, and real-time data analytics to optimize everything from parts inventories and labor scheduling to quality assurance and testing. The scalable, flexible approach enables car companies to offer fully customizable vehicles instead of fixed option packages and to innovate quickly in response to marketplace demand or regulatory requirements. 
The auto factory 4.0 still features an assembly line, but the promise of mass customization is setting innovative businesses apart.

Operational Technology Gets an Upgrade

Until recently, discrete manufacturing processes have relied on operational technologies that are delivered as a proprietary, integrated system from a single vendor. The manufacturer can get locked into the vendor’s equipment and software and is dependent on that vendor for costly upgrades and maintenance contracts, often for ten years or longer.

Many of these legacy systems are now being replaced or supplemented by scalable solutions based on Intel® technology. For example, industrial PCs (IPCs) powered by Intel® processors can consolidate and run a variety of manufacturing workloads on a single device that is purpose-built for scalability, manageability, and security.

This open, converged approach to enterprise resource planning (ERP) enables manufacturers to apply the latest technologies in machine vision, artificial intelligence (AI), and real-time data collection and analytics to accelerate, control, and verify production processes.

The first step in the transition from legacy systems to an open solution is to build infrastructure that can accommodate an integrated technology stack. System design must include a detailed plan to scale the solution once it is fully tested and proven to address a valid business problem. Over time, multiple single-purpose devices and systems can be consolidated in a scalable, shared platform that improves operational efficiency, enhances security, reduces costs, and enables innovation.

Intel and its ecosystem of partners offer hundreds of precertified intelligent edge solutions that are designed and built for the rigors of the factory. Together, Intel, its technology partners, and customers can propel even the most complex and demanding discrete manufacturing operations toward greater efficiency, productivity, and innovation.