Discrete manufacturing involves creating products by assembling individual, tangible parts. These parts are assembled in a specific sequence to produce the desired result. The production lines in discrete manufacturing produce products that are similar but not identical.
Since each step in the discrete manufacturing process is distinct from those before and after, this approach is often used to create complex, multipart products for automotive, aerospace, electronics and consumer goods applications.
In our discrete manufacturing guide, we’ll explain the core principles of this approach, explore common characteristics and examples and offer best practices to keep discrete operations on track.
What is discrete manufacturing?
Discrete manufacturing produces distinct items from standardized parts or components. This sets it apart from process manufacturing, which combines multiple components to create a homogenous result.
Think of it this way: In a discrete manufacturing system, parts are connected but not combined. This means products can be dissembled and potentially reused. On the other hand, process manufacturing involves merging components to form an entirely new, final product that cannot be reverted to its original state.
Vehicles are a classic example of discrete manufacturing. Parts such as nuts, bolts, rods, pistons, wheels, engines, windows and body panels are combined to create a finished product. Each vehicle produced is similar but not identical since every component used is physically distinct.
Characteristics and examples of discrete manufacturing
Three characteristics define discrete manufacturing: standardized materials, production planning and preventative machinery maintenance.
- Standardized materials: Discrete manufacturing uses what’s known as a bill of materials (BoM). The BoM lists all raw materials, parts and quantities required to produce a specific product. BoM should be regularly reviewed and updated to ensure it reflects current processes.
- Production planning: Production planning defines each stage of discrete manufacturing, which can include material preparation, sub-assembly, final assembly, quality checks and packaging. It also determines how orders will be produced, whether in large batches or customized orders, and ensures that each item is trackable through serial numbers.
- Preventative machinery maintenance : Offline or underperforming machinery impacts production timelines and can reduce product quality. To reduce this risk, companies must create and implement preventative maintenance policies that focus on eliminating potential problems before they occur.
Common examples of discrete manufacturing industries include:
- Aerospace: Aerospace manufacturing companies often leverage large-scale assembly lines that use custom parts to create mission-specific components.
- Automotive: Industrial automotive manufacturers are a prime example of discrete manufacturing. They utilize multistage assembly processes, each taking varying amounts of time to complete. This highlights the “discrete” nature of the process, where each process is connected yet distinct from the ones before and after it.
- Electronics and appliances: Consumer electronics and appliance companies provide additional examples of discrete manufacturing. These producers often channel specialized parts into precise sub-assembly cells, which are then combined to create finished products. This results in items that can be dissembled at scale — for example, you can remove an oven door or replace a heating element — but also contain small parts such as transistors or silicon chips that are not easily deconstructed.
Best practices for discrete manufacturing maintenance
High-quality materials and well-defined production processes don’t matter if machinery fails. Unexpected downtime costs money, and since discrete manufacturing relies on the assembly of parts in order, even a single break in the production line can halt production.
Four best practices can help reduce the risk of unexpected machinery maintenance:
- Scheduled preventative maintenance and operator-centric care: By scheduling routine maintenance, repair and operations (MRO), manufacturers can minimize the risk of unexpected downtime. In addition to these scheduled checks, companies should also train operators in how to perform quick checks, make minor adjustments and complete daily tasks such as lubrication of key components.
- Spare parts strategy: It’s also important to implement a robust MRO spare parts strategy. This involves balancing the need of having parts readily available with the costs associated with maintaining inventory. Two common approaches are: keeping critical spares on hand for high-wear components or adopting vendor inventory management for just-in-time parts replacement.
- Cross-functional collaboration: Production, maintenance and engineering teams — including managers and front-line staff — should regularly share data on production throughput, reject volumes, and machine performance to help identify potential failure points.
- Continuous improvement: Continuous improvement solutions are also critical. These often include lean manufacturing practices, such as limiting waste and discrete manufacturing ERP software. By using these tools, companies can identify potential issues and uncover opportunities for improvement, such as enhanced tooling or reconfigured assembly cells, leading to better cycle times or higher product quality.
Optimizing discrete operations
Reliable processes and minimal downtime lead to high-quality products. To achieve these goals, companies need to optimize discrete operations using well-planned maintenance, continuous improvement and a lean mindset.
Sustained success starts with an assessment: Where are processes performing as expected, and where can discrete operations improve? Next is expert assistance. While companies can take on the optimization process in-house, it’s often more cost-effective to connect with a trusted solutions provider.
ATS has the industry experience and operational expertise to help your team create customized maintenance programs, implement predictive analytics and deploy discrete manufacturing ERP systems that deliver optimized outputs.
