How Simulation Enables Continuous Manufacturing 

When you brushed your teeth this morning, the toothpaste you used was likely made using a very advanced manufacturing process. From weighing and mixing the raw ingredients, capping, filling, and crimping the tube, stamping and packing it for shipment, all the steps needed to make your breath minty fresh likely happened in the same facility, by highly coordinated machinery, one right after the other. This kind of uninterrupted, smart production process is called continuous manufacturing.

What is Continuous Manufacturing?

Continuous manufacturing is a type of manufacturing with no interruptions between each production stage. In this process, equipment is dedicated to specific tasks, and the material being processed is in constant motion. Because continuous manufacturing usually means operating 24 hours a day, this production process can create high volumes of identical products quickly.

Industries using continuous manufacturing include:

• Oil
• Steel
• Paper
• Cement
• Food and beverages
  
• Pharmaceuticals
• Electronics
• Automobiles

Batch Manufacturing vs. Continuous Manufacturing

Both continuous process and batch manufacturing are widely used today, with batch being the standard industry process. In batch manufacturing, production occurs across multiple steps, often with stops between each step to evaluate the product, perform maintenance on the equipment, or even ship the product to another facility for further processing. These frequent stops can add considerable time to the production schedule.

Unlike batch manufacturing, continuous manufacturing combines all the production steps into one integrated flow. This steady production stream helps manufacturers speed production times, reduce human error, and improve product consistency without these stops.

Batch production is common with small companies and companies testing new products. But for companies that produce large quantities of the same product, continuous production may be the better investment.

The benefits of continuous manufacturing include:

• Shorter production times made possible by eliminating the need to stop equipment for repeated resetting, which creates better schedule adherence
• Consistent goods because once the automated process is set, products are always produced to the same specifications
• Reduced risk of human error because staff are less exposed to the product so human contamination is greatly reduced
• Flexible batch sizes/simplified scaling is enhanced because quantities can be changed by extending or shortening the duration of the production run
• Automated monitoring and predictive maintenance via constant analysis throughout the entire system, which provides greater control over critical processes

What are the Challenges of Continuous Manufacturing?

While continuous manufacturing can help companies save time and improve product standardization, it does come with some challenges:

• Initial investment is high due to the upfront expense of the automated machinery and square footage required
• Limited flexibility as a result of the exacting specifications of constant production, which don’t lend themselves well to product customization
• Unplanned maintenance means stopping a continuous system for one machine, which takes the whole process offline
• Inventory buildup can be an issue if consumer demand lags, causing manufacturers to struggle to offload their high volumes of products

How Does Simulation Improve Continuous Manufacturing?

Because continuous manufacturing is fully automated, information is constantly analyzed throughout the entire system. This is particularly helpful through the use of digital twins. By providing a connected, virtual replica of in-service machines within the manufacturing process, digital twins give workers a real-time perspective inside the equipment to accurately inform decisions about performance and maintenance.

For example, a digital twin of an industrial mixer can alert the manufacturer when the friction between materials puts the motor at risk of strain or failure. Without the constant feed of digital information simulation provides, factory workers would have to make assumptions based on what they can see with their own eyes — which is a fraction of what’s actually happening.

The Role of Hybrid Analytics in Digital Twins

New hybrid calibration capabilities increase the accuracy of predictive analytics even more. By mixing simulation-based digital twins with physical sensor information, factory workers can implement virtual sensors and reduce the number of physical sensors required, thereby also reducing costs.

With hybrid analytics, digital twins can be deployed at scale to track different equipment’s operation in a wide range of conditions. In addition, each deployed twin can be calibrated based on the data monitored from its connected asset, guaranteeing that the digital twin behaves as closely as possible to physical systems and equipment.

Benefits of Digital Twins in Continuous Manufacturing

Once a digital twin is deployed, users can expect a 25% increase in product performance and maintenance cost savings up to 20% over the product’s lifetime¹. These competitive gains result from the many benefits digital twins provide, such as:

• Real-time monitoring across complex systems
• Predictive maintenance that prevents downtime by tracking the past, providing deeper insights into the present, and predicting future behavior
• Improved operational efficiency through process automation
• Informed financial decisions about materials and equipment

Continuous manufacturing is a great leap forward for many companies committed to moving their production methods into the next era of smart, integrated manufacturing. To learn how innovative technologies are helping companies across industries transform their operations, read more about digital twins, or get a free trial of Ansys Twin Builder.

References

1. “Unlocking the Value of Digital Twins with Ansys Twin Builder,” Ansys.