Industry 4.0: A Practical Application in Ceramic Kilns
The ceramic kiln industry offers many opportunities for innovation, where Industry 4.0 capabilities can be leveraged to unlock additional value.
Industry 4.0, also known as the Industrial Internet of Things (IIoT), is proving to be a revolutionary trend that will shape the industrial landscape in the coming years. Adding intelligence to physical objects has never been as easy and inexpensive as it is today. However, even though the concept of Industry 4.0 has been given a lot of coverage from the media, it has been reported that fewer than 20% of manufacturers have any kind of strategy in place related to Industry 4.0.1 The ceramic kiln industry offers many opportunities for optimization, where Industry 4.0 capabilities can be leveraged to unlock additional value.
The first step when starting an IIoT project is choosing a use case. Out of the hundreds of possible projects, it is important to choose one that suits the company’s objectives. These types of projects can be divided into the following categories:2
- Asset utilization
- Real-time optimization
- Smart energy consumption
- Remote monitoring and control
- Predictive/preventive maintenance
Perhaps the easiest business case to implement is the use of digital management tools. The visibility that digital dashboards give to data allows for improvements in performance in the order of 20-30%. Product loading information in a tunnel kiln is critical in order to maximize its production. Many times, a kiln car is under-loaded, making the equipment less efficient both in terms of yield and energy consumption.
Figure 1 shows the weight of cars measured before entering the kiln. Note that the standard deviation is quite high, which indicates that, in this case, some cars are entering the kiln with an average of one or two pieces missing. A dashboard containing both the weight and a photograph of the car or cars that do not comply with the predefined minimum load weight can help reduce the number of under-loaded cars entering the kiln, which in turn increases productivity and total yield.
The traditional quality control strategy where product is randomly inspected for possible defects is increasingly shifting to a preventive approach involving real-time monitoring and advanced digital techniques. Advanced simulation tools like computational fluid dynamics (CFD) software enable the creation of the so-called digital twin—a complete digital representation of the performance of a kiln under different circumstances. CFD tools can predict the temperature uniformity within a kiln under different conditions so that any deviation from regular operation can be attributed to a change in a critical variable.
Figure 2 shows experimental and CFD air flow data for a convection oven. A digital twin would be created by repeating different operating conditions and storing all available results in a database. This database can then be consulted by the equipment to compare current data and decide any changes needed in the kiln’s operation.
Smart Energy Consumption
Many people do not know how much energy their kiln should use and the impact different process variables can have on their energy consumption. Digital technologies allow for the real-time comparison of measured values against theoretical ones.
Commercially available software* can calculate instantaneous and total gas consumption for any given process. In addition, heating and soaking times can be accurately predicted based on load mass, configuration, size, temperature cycle, kiln size, and other relevant process variables. Results measured from real-life processes are typically within 10% of the calculated theoretical values, so any deviation higher than that may be attributed to abnormal operating conditions.
In a recent project in a shuttle kiln, the model showed that gas consumption was 30% higher than the theoretical gas consumption calculated using the software. After careful on-field measurements, excess air entering the kiln via a damaged kiln bench was found to be the culprit. After repairing the kiln bench and installing a new pressure control system, gas consumption was reduced by 25% (see Figure 3).
Remote Monitoring and Control
Cloud-based solutions for remote monitoring and control are increasing the visibility of kiln performance, allowing for experts to analyze and provide feedback without the need to be on site. Companies with multiple sites over the world can easily compare and benchmark kiln data and allow for collaboration within the company.
In addition, remote assistance by the original manufacturer of the kiln is made easier and less expensive. It is important to carefully select the variables to be monitored, as this will determine the success of the project. For kilns, the minimum information to be monitored includes: temperature, air and gas flows, internal pressure, oxygen levels, and load mass, along with any other process variable that directly impacts the kiln’s efficiency. Figure 4 provides an example of a dashboard that displays some of these process variables for real-time monitoring.
Even though preventive maintenance efforts have been around for many years, data quality and volume coupled with improved machine learning algorithms are revolutionizing the field. Expensive equipment to have on stock like kiln fans can be monitored to detect when maintenance or replacement needs to take place. Critical variables like fan vibration, speed, current, temperature, and pressure can be monitored and compared against preconfigured alarms to detect when a maintenance service will be required.
Maintenance can be scheduled based on operation data and not by calendar weeks, which increases asset availability and minimizes unplanned downtime. Typically, asset availability can increase 10-15%. However, to make the most out of this kind of project, it is important to partner with a company that has a deep knowledge of the asset, since a required level of expertise is critical for the success of the initiative.
Plan for Success
Industry 4.0 projects have not been as popular as initially expected by many experts. In many cases, the lack of a clear strategy or roadmap for implementation is responsible for the slow adoption rate. The best approach is to define a set of concrete projects based on areas where success has been common in many companies.
Potential areas for success include: asset utilization, real-time optimization, smart energy consumption, remote monitoring and control, and predictive maintenance. These types of projects have been found to provide quick wins that can build the necessary confidence to eventually embark on more complex and rewarding projects, such as those involving artificial intelligence or big data.
1. Breunig, M.; Kelly, R.; Mathis, R.; Wee, D., Industry 4.0 after the Initial Hype: Where Manufacturers are Finding Value and How they Can Best Capture It, McKinsey Digital, 2016.
2. Baur, C. and Wee, D., Manufacturing’s Next Act, McKinsey & Co. Operations, June 2015.
*such as Nutec Bickley’s Kiln10® software