Drying with IIoT and Cloud-Based Data Management
Access to more and better information about the drying process can improve your operations.
A smarter world has emerged around us. The Industrial Internet of Things (IIoT) revolution is changing the way companies are doing business much as the Internet of Things is changing everyday life. Crosscutting technology advancements such wide device availability, coupled applications and increased opportunities for constant connections allow processors to harness the power of digitalization to more safely and efficiently produce products, goods or services.
No more is the industrial processing sector lagging behind the consumer market in computing technology. Here are 10 ways the new frontier is changing the old models of dryer operations as we know them.
1. Maintain a Constant Connection with Solution Providers
A digital relationship adds value to a single-point-in-time contact. When companies work with vendors and machine manufacturers, they do it in a linear way. Yet, to get the most out of a drying equipment purchase, manufacturers in the process industries need access to drying process expertise. They can get this by attending drying seminars, requesting site visits and field engineering evaluations, and simply by calling. These interactions — based on single-point-in-time interactions — flow in one direction, however. This is the lone-business model, where the processor requests support from the dryer manufacturer “as needed.” The dryer manufacturer does not have access to processor data because it is generally stored in silos.
The new frontier is a model of collaboration. A processor can be constantly connected to a solution provider, with access to enterprise expertise. Processors already have the sensors in place, collecting data. Cloud-based management, or the digital relationship, can enable a back-and-forth flow of information analytics between the processor and the equipment provider. Both can see a dashboard that centralizes and synthesizes data in real time for meaningful insights. IIoT data management interconnects information to help processors realize new business models, optimize internal processes and achieve cost savings. It allows companies to take advantage of the supplier’s process knowledge, full time and sustainably.
2. Gain Access to Better Customer Service
The digital intimacy of cloud-based management is designed for long-term operational success.
With information displayed on a web-based dashboard, a user can pinpoint at-risk parts and components before they fail. Service records can be viewed on a time-stamped basis, and reports generate data that can show how much money was saved or how much more could be with preventive maintenance.
Yet, it is not just maintenance that can improve; the thermal process can improve as well. The processor and solution provider can work together to make sure the processor is getting the most from the dryer. This works because the service model is based on the facts. Unlike the single-point model, the constant connection in the collaborative model can help drive a processor’s competitive strategy, its culture and organizational design.
3. Achieve Sustainable Processing Through Connectivity
Like a Fitbit watch that never stops offering insights, IIoT enables an organic, continuous, real-time connection to optimize processing. After all, it does not make sense to monitor and collect dryer data — energy usage, for instance — unless it can be put to good use.
Two field evaluations can illustrate how IIoT improves processing. In any thermal process, when upstream operations change, product entering the dryer can have a higher moisture content. As a result, more energy may be required to dry the entering product to the process specifications.
Such was the case at one processor, where product entering the dryer had varying moisture content. The processor reached out to the dryer manufacturer, and drying engineers address the problem by optimizing bed depth to ensure optimal product retention. The changes saved the processor 12 percent in energy costs.
They did not last, however. Five months later, the company requested another evaluation. When the field engineers returned, they recommended the same changes. The drying engineers explained to the processor that the same adjustments had been made during the previous evaluation. The processor’s varying infeed conditions were pushing the drying process out of specification.
This became a turning point for the processor. The company realized the value of being connected continuously to processing expertise. By trusting the data, those energy savings will not disappear again.
4. Use Existing Data to Drive Business Decisions
From paper reports generated by chart recorders to Excel spreadsheets from programmable logic controls (PLCs), processors have long had access to critical information. Often, however, it was buried in volumes of emails, exchanged through private discussions, hidden within spreadsheets and housed on laptops. With IIoT management, it is possible to pair one chart with another, to analyze the data to gain insights that were not possible before, and to ask questions and find answers that can affect management decisions, staffing and operating conditions. Simply put, IIoT makes data relevant.
Over time, changes in recipes and operating parameters — whether due to operator preferences, turnover or process constraints — can lead to significant losses in energy efficiency. For instance, one processor added cloud-based data management and discovered that nearly 20 percent of the time a dryer was energized, it contained no product. By tracking energy use and the time during which the dryer was energized, by day and by shift, management was able to pinpoint inconsistencies in the operations. A review of the entire process allowed the processor to reduce energized time without affecting product and prevented this waste of energy.
5. Manage the Human Element More Effectively
When a dryer operator is asked to get as close to the target moisture point as possible, there is a natural tendency to overdry. Overdrying is a common practice, and one processing deviation can dramatically affect batch results and yield. When feed is overdried, too much water is evaporated, which has to be replaced with raw ingredients. Access to continuous, real-time monitoring with hardware, software and ongoing process expertise, combined with technical support, enables the operator to consistently reach the desired moisture target without overdrying.
An example can illustrate potential improvements. Suppose a dryer operator traditionally collects samples and measures the moisture content level in a laboratory. Then, the operator returns to adjust the dryer controls as needed. The process is slow: dryer retention time can be 25 to 30 minutes, combined with time to analyze the product in the laboratory. All the while, production time and product can be wasted. Moreover, if testing suggests that the product is too dry, the process must be repeated. Without continuously automated data monitoring, the operator must take measurements and make adjustments.
When the operator uses cloud-based tools that reduce time-based moisture deviation, a reading can be captured every second. As the inline moisture sensor takes a reading, an algorithm written to control the dryer can manage the temperature setting to consistently achieve the desired output. This digital relationship gives the operator confidence that systems are calibrated and that processing is efficient.
6. Discover Hidden Opportunities for Improved Efficiency
IIoT enables processors to ask questions they did not know needed to be asked. With continuous online access to expertise and data on the cloud, an expert can view and interpret the dryer processing data. Service records can be viewed and data interpreted on a time-stamped basis. This provides insights processors might not otherwise have and allows them to investigate anomalies (like why was the dryer energized 30 percent on Wednesday when it averages 8 percent on other days). Time-stamped data allows the processor to see the big picture and take action based on history.
Here is another example. In the old models of production, it was difficult to manage from behind. Suppose the plant manager sees the dryer was energized two hours out of an eight-hour shift. He asks what happened and suggests adjustments to reduce that time. The next day, the data shows the dryer was energized only one hour. The plant manager can acknowledge the energized reduction but also ask what was done differently. With IIoT, the opportunity to continuously ask questions, based on data, keeps production striving toward efficiency.
Being able to monitor critical processing parameters in real time means you will not have to wonder if your process is producing a safe product.
7. Achieve Better Asset Utilization
Every piece of equipment on a plant floor contributes to the effectiveness of the total plant production process. Each and every moment the dryer is not working — planned or unplanned, for product changeover or maintenance — can negatively affect overall effectiveness. Therefore, the fewer the stops, the better for overall results. IIoT capacity metrics can demonstrate how much a dryer is down due to maintenance, and the insights can enable new business decisions. For example, if a dryer is down 60 percent of time, then there is 40 percent more capacity available for running more product or selling more contracts. Such data could even justify investment in a new production line. Data gained from IIoT can help the plant manager have a better view of the entire production for better asset utilization.
8. Connect Data with People to Improve Performance
IIoT can drive competitive insights based on facts to better integrate an organizational structure and its capabilities. Such insights create trusted, human-connected solutions that improve businesses. For instance, if a conscientious dryer operator is making good decisions for his shift, controlling moisture according to specifications and saving money, the plant manager will have access to this information and be able to champion him. By integrating the human instinct to connect with people and expertise, IIoT can eliminate information silos, bring full employee engagement into any business process and help solve problems quickly to improve performance.
9. Verify Processing Parameters
Validation ensures that pathogens such as Salmonella and Listeria are controlled when producing food for human consumption. In nut roasting, for instance, log reduction is based on defined parameters such as retention time, product temperature, process air temperature, air velocity, product moisture content and process air humidity, with sensors correlated to a known validation. Being able to monitor critical processing parameters in real time means you will not have to wonder if your process is producing a safe product. IIoT enables processors to validate that a roaster is delivering the desired kill step every time.
If a process interruption occurs, an IIoT-connected tool in cloud-based management services can warn the operator. This might happen because of a change in temperature, moisture or time retention. Or, perhaps a burner goes out. An alert gives the operator an opportunity to do something about it, have the product closely checked or keep it from being shipped. This ensures food safety for the consumer as well as protecting the brand. It also can save product that would potentially have to be discarded. Being able to reduce the amount of waste that a facility produces means there is more sellable product.
10. Recognize New Insights to Ensure Continuous Improvement
Being able to ask the hidden questions and discover new efficiencies is part of the culture of IIoT. It can change behaviors that people begin to see. An IIoT cloud-based service can nurture and develop the right enabling patterns of behavior and cultural attributes of excellence. The information that has been buried in spreadsheets is synthesized in meaningful ways that are transparent, so that the human element can become vested in the process, to continuously aim for efficiency.
In conclusion, as the old models of production change, there is an increasing opportunity to harness the power of digitalization to more safely and efficiently produce products sustainably. By 2050, the needs of approximately nine billion people will require approximately three times our current resources. At this time, challenges will accelerate for the deficiencies of resources and the enormous production of current waste.
Sustainable business models will help processors get there, focused on safe and efficient feed processing that saves energy, and with digitalization that provides integrated operational connectivity. Sustainable processing must meet present needs without compromising future viability. It is not just a corporate responsibility: Sustainability directly relates to maximizing efficiency, minimizing waste, finding cost savings and discovering increased profitability.