Trending in a vacuum drying process to achieve an endpoint analysis has been a holy grail for decades. Although the mechanical side of the drying process hasn’t changed dramatically, the monitoring and control has. We have new sensors and program algorithms to finally know what the process is doing and how to control it. Imagine running an entire drying cycle without an operator in less time. New monitor and control options can reduce process time by 30% and reduce the number of operators required.
Most drying problems are solved by more heat, more vacuum, and longer runs. Inadequate sensing of the product being dried and the vapor removal process have left engineers and operators blind as to what is taking place in the closed system. Breakthroughs in sensor technology have made it possible to place them in areas where they transmit useful data, not just data. The instruments are also designed to meet industry standards for the harshest environments like explosion proof, ATEX, or CIP applications. Wireless technology has also made these sensors easier and less expensive to install.
In today’s vacuum drying world, an operator will not know the initial moisture content of the batch. A 1 or 2 percent moisture difference in a batch makes a great difference in the final drying time. But still, the batch drying time is probably set to the batch size of the dryer. Several times during the drying process, the operator will pull a sample to check the LOD (loss on drying). In checking the samples, he will also notice the drying phases listed below. This information is insufficient for him to make reputable conclusions about the process or make process changes to help the process be efficient. He is like a sailor with a sextant, not a GPS.
In theory, the five phases of a drying cycle are easily understood: 1) Product warm-up; 2) Surface moisture removal/Constant rate; 3) Sticky, balling, physical change; 4) Residual moisture removal/falling rate; 5) Bound moisture removal.
Although you may not have all phases, you will have at least three of them. Product warm-up, constant rate, and falling rate is a simple drying application. If the product has physical changes during the drying cycle or has bound moisture, it will require setting changes to offset those characteristics. When charted, the data can illustrate the product entering and leaving each phase. Trending compares real-time data to history to ensure the product is drying at an optimal rate. Many things can slow the drying process but only a real-time sensor can pinpoint the problem and fix it.
Once the trending history is complete we can create benchmarks to evaluate a drying process. Temperatures throughout the closed cycle are the most important. Tracking temperature in the product and its vapors are critical in a data log. Vacuum measured from the inner vessel to the vacuum pump is used to measure process efficiency and mechanical dryer efficiency. To control the process, we use sensors to monitor the performance of the TCU (temperature control unit) and the SRS (solvent recovery system). The TCU is providing heating media to the dryer and cooling media to all heat exchangers. Constant monitoring of the temperature delta will allow the system to compensate for process changes.
In a closed drying system, we want to create an equilibrium of the perfect environment for the drying phase at hand. In a manual system, it’s too difficult to make constant changes and record the large amount of data for the process. With a PLC-based system the sensors and algorithms can work together.
The algorithms are the key to controlling the process. These are the mathematical equations that are used by operators every day without their knowing it. Product based algorithms automatically compensate for the parameters of product limitations, safety limitations, and quality limitations. The algorithms and the PLC are also more attentive, faster, and sensitive to product change than the human operators. Not only does this increase efficiency, but it allows the vacuum dryer to operate itself. This efficiency can be expressed in increased output or decreased product cost.
Gregg Muench is the V.P. of business development at GEMCO. He has 35 years’ experience in tumble blending and drying.