Plastics processors expect a lot from their dosing and blending equipment. Flexibility, modularity, cleanability, and quick changeovers are key. And equipment must be able to handle whatever fillers or additives the processor wants to add. Moreover, “Data collection and integration into plant-wide control systems for process validation is a standard, and ease to integrate is assumed. Accuracy is a must,” says John Winski, director of sales at Coperion K-Tron. 

Chris Crittenden, marketing director at Maguire Products, agrees that high accuracy is standard:“Accuracy is often highlighted as ‘improved’ in the market for blending and dosing systems. Yet in reality, once you are accurate to +/-0.1% of a 1% setting (in grams), then, practically speaking in real production terms, it doesn’t get any more accurate.”

Accuracy is crucial because dosing is the input to the plastics compounding, extrusion, or molding process. Efficiently producing a high-quality product requires a high level of control right from the start, in the dosing and blending step. Today, there’s an increasing focus on collecting, analyzing, and using data to improve process efficiency. 

The Internet of Things

The industrial Internet of Things (IoT)—a.k.a. “Industry 4.0,” a network of equipment that’s connected using information technology—helps make data available. IoT enables process engineers to view and even control a plastics process, including dosing and blending equipment, anytime and anywhere using mobile devices. “IoT puts real-time information in the hands of process engineers so they can manage their process and bring value to customers,” says Mike Rasner, president and CEO at Advanced Blending Systems. 

Crittenden says that a benefit of IoT is in broader data access. “Improved accessibility and better methods of connectivity will simplify how different users read and see production data, allowing them to understand production costs and efficiency and to troubleshoot more rapidly.” Simplified data will benefit those who perhaps previously would not have understood the technical side of blending. “IoT will give processors in additional fields the confidence to work with material blends more directly and to consider more diverse materials or additives to improve product features and achieve cost savings,” he explains.

IoT is beginning to change the paradigm of how users interact with data, agrees Winski. “Historically, control equipment for manufacturing processes have generated tremendous amounts of real-time data for customers, but left it to the user to design how frequently to examine and use the data. The controls acted as a server and simply made the data available.”

IoT, however, “allows a user to indicate what is important to them once, and the control systems push that information to them when it is relevant,” Winski adds. “This allows users with different roles within the manufacturing process to subscribe to different information and trends that might be important to them.” For example, maintenance engineers can receive alarm conditions, while materials planners can receive data on total material fed over a given timeframe.

“The Internet of Things is dramatically changing how machines communicate and exchange data with each other and with the people who use them,” says Bob Criswell, manager, Electrical Engineering, at Conair. “Most of today’s control systems are designed for Ethernet connectivity, and through industrial networks and the Internet they can connect and communicate with almost any other device. We can use that technology to significantly reduce costs and increase ease of use, maintenance, and integration.”

“Supervisory” Functions

In 2015, Conair introduced a new generation of its ControlWorks plant-wide control platform, which has been available since 2006 to monitor and remotely control plastics processing equipment. The latest version uses supervisory control and data acquisition (SCADA) technology, which gives users the ability to look at more than one piece of equipment at a time and drill down as necessary to find information on individual machines. SCADA also allows ControlWorks to gather process data from all connected equipment and store it for analysis.

The company also introduced a tablet-based system that can replace the human-machine interface (HMI) panels that are found on almost all equipment. A single, standard tablet computer can be programmed to address the controls on multiple pieces of equipment control so that it becomes the HMI for each of them, thus saving significantly on the cost of touchscreen HMIs, says the company. According to Conair, “Supervisors and other employees authorized to perform set-up and maintenance simply carry a tablet with them into the plant and connect quickly and easily to any equipment that requires attention.”

Making data accessible to users is crucial. “The major trend that we see in gravimetric blending and dosing is the need to simplify the process on the production floor, while also optimizing material usage efficiency,” says Maguire’s Crittenden. “We are focused on users and their ability to easily get things done, and that means simple interfaces and easy controls that are intuitive for all operators.” At the same time, visualization of production is increasingly important.

Crittenden notes that small- to medium-sized businesses need effective data access that isn’t overly costly or complicated, and larger enterprises need solutions that let them better manage production by harnessing materials usage data. Maguire’s mainstream gravimetric blender range now comes standard with upgraded control features and interfaces. For example, touchscreen interfaces have new graphics and pages. “The user is only ever one or two screens away from any required feature,” he adds.

Harnessing Data Power

Most processes have closed-loop advanced control, in which data from measurements on the extruder is used to adjust feeders and keep the process in spec. Analyzing feeder data trends allows users to continually improve process efficiency. Another use of feeder data is to validate quality.

“Processors need to be able to look at either real-time or historical data (e.g., rate vs. set-point), and be able to do it quickly and easily,” says Rasner of Advanced Blending Systems. “We have offered this data collection technology with our feeders for more than eight years, but more customers are now seeing the value in it. For example, if there is a quality issue or complaint, they can pull up the data and see whether additives were added to the blend at the correct level. We see this being increasingly important in applications such as food packaging.”

Some are taking data use a step further and using it for real-time release, adds Rasner. For instance, rather than testing a film sample in a quality assurance lab, critical quality attributes can be measured in real-time on the extrusion line to ensure product quality.

Smart Feeders

Coperion K-Tron’s ActiFlow technology is an example of combining sensor data and control systems to make a “smart” feeder. Today, many compounding processes use ActiFlow to improve feeding of poorly flowing powder materials, says Winski. For example, if arching occurs in the hopper, the lack of flow is sensed by the weighing system, and the ActiFlow controller applies more vibration to the hopper to break the arch. Once the flow is again consistent, the system reduces the hopper vibration.

The company recently introduced another sensing and control technology: Electronic Pressure Compensation (EPC). Pressure compensation is needed for gravimetric feeders that are part of a closed system, where changes in pressure within the feeder hopper or discharge tube can cause an incorrect weight signal. EPC detects air pressure build-up inside a feeder and adjusts the weight signal accordingly to compensate. It offers advantages over traditional mechanical pressure compensation systems, the company says, such as improved accuracy and reliability, as well as lower initial cost and easier installation. 

With such “smart” operation of feeding equipment combined with data accessibility, equipment users have the opportunity to make intelligent decisions to run their processes optimally.