According to Global Industry Analysts Inc., the IoT analytics market will reach $40.6 Billion by 2024. Additionally, Statista predicts that the global market will reach $1.6T by 2025 and that 75B connected devices will be in use. Indeed, IoT deployment has gained significant traction in various industries such as autonomous vehicles, insurance, and telehealth.
One particular industry that is beginning to reap the rewards of IoT technology is the food & beverage industry. Overtime, IoT has enabled the integration of computation and networking with physical processes to help food manufacturers address labor shortages, proactively address maintenance, and, more importantly, improve productivity. However, there are still way more use cases to uncover for automation in the food and beverage sector.
It’s no surprise that the pandemic has upended the food and beverage industry. Factories were forced to shut down, and the ones that remained open were forced to lay off many of their employees. Outside of factories, people’s food consumption patterns also began to change. These events have clearly translated to rising food prices and have forced food manufacturers to not only update existing technology but apply new automation in their facilities. Here are three ways IoT technology is addressing issues in the food & beverage industry.
Predictive Maintenance VS Preventative Maintenance
Despite the initial friction that came along with the pandemic over two years ago, the food and beverage industry is still navigating unstable supply chains, and volatile levels of consumer demand. They’re also navigating this rugged terrain with less labor at their disposal. Therefore, the last thing that any manufacturing company needs is to deal with failing equipment and unexpected downtime.
Fortunately, new types of predictive maintenance through remote monitoring allows early detection of future problems that can extend machine health and lifespan. In many ways, technology is also working in tandem with artificial intelligence. For example, while AI is applying forecasting algorithms to their approach to predictive maintenance, IoT is the technology that monitors machines and equipment, which is more efficient than the status quo of preventative care. It can also do so cost-effectively. A study from Deloitte found that predictive maintenance will save companies $630B by 2025.
Examples of predictive maintenance are expanding in the food and beverage industry, but an interesting example came to light recently from our team working with a craft cold brew coffee maker. The brewery was seeing inconsistent operations of critical steam boilers used in their brewing process. The ‘misfiring’ led to sporadic failures with other adjacent equipment integrated with the boiler. To address the issue and get ahead of any larger scale failure they installed pressure and temperature sensors, as well as downstream vibration sensors as part of a case-specific IoT plan. The sensors revealed rapid pressure drops and vibration spikes on a localized compressor.
Without the use of technology in this case, the coffee brewer would have never identified the true root cause of the inconsistent operations. Real-time notifications delivered from the sensors and into the cloud enabled the company to alert product staff of needed maintenance when the issue is occurring, which diverted any downtime.
Improve Safety with Remote Monitoring
When people discuss safety in the manufacturing setting, it’s not uncommon for people to imagine images of workers in close quarters giving each other Covid. While this is undoubtedly a real-world concern, when it comes to the food & beverage industry, safety is highly imperative to both workers and consumers.
With that said, these companies dealing in perishable goods end up being impacted in different ways due to the time-sensitive nature of their products. As such, supply chain issues have only exasperated this problem. In fact, according to the National Restaurant Association, over 95% of operators experienced supply delays or shortages of crucial food or beverage items in 2021.
Additionally, the data companies receive from sensors, and other IoT technology is invaluable. For example, monitoring temperature fluctuations within processing facilities and storage facilities are essential for food and beverage safety. These temperatures can directly impact the quality of these products. Knowing this and the impact of ongoing labor shortages, it would make sense why these companies are looking to take the next step and embrace what Industry 4.0 has to offer, such as improved efficiency and safety.
However, retrieving this data is one of two roadblocks that prevent companies from receiving the total ROI of IoT deployment. Manufacturers that lack remote monitoring are not only spending more time than necessary extracting valuable data, but they also end up inadvertently forcing more employees to remain onsite, which poses transmission risk and exposes these employees to potential hazards that stem from faulty machinery and other impending failures.
When failure is imminent, it’s essential to have a robust monitoring system that can send an alert to service teams directly and give a higher level of overall visibility into these machines through actionable data.
Unleashing Commercial IoT’s Real Benefit: More Revenue
While preventing downtime and ensuring safety are vital, when you talk to commercial executives in the food and beverage sector their eyes really start to light up when you get to how IoT can improve their top and bottom lines. The holy grail for powering IOT-led revenue gains is found in the data.
If retrieving data is the first roadblock preventing companies from achieving the full ROI of IoT deployment, the second roadblock is making sense of this data. While many companies in the food and beverage space rely on sensors, they can’t interpret literally the piles of data it throws at them. Some of these companies rely on PLCs and receive their data through a data dump download but having data for the sake of having data is not only pointless, but it also requires end-users to take time from their daily tasks in order to sift through mountains of data.
That’s why food manufacturers, breweries and other consumer goods companies that are making the most of their use of IoT are focused on delivering concise, actionable, intelligence data to drive productivity gains. Increasingly, ‘digital twins’, or the act of using virtual representation that serves as the real-time digital counterpart, is the way to turn data overload into captive data streams.
These captive data streams can easily indicate a deviation from baseline process behavior to predict potential productivity gains. This actionable data adds tremendous value to food and beverage manufacturers looking to give their IoT data a voice without the unnecessary noise.
For example, breweries need to rely on robust cleaning processes in order to bring a safe beverage to market. Boiler pressure and temperature, turbidity rates (how hazy the beer is) and clean-in-place-cycles can be constantly monitored from anywhere. With that in mind, sensors are constantly monitoring the efficiencies of various equipment including tanks, pumps, boilers, chillers, generators, etc.
So, instead of solely relying on sensors to provide tons of data on tons of equipment, the use of a digital twin can help convert all that messy data into actionable business intelligence. Furthermore, by creating a digital twin, these organizations are building a virtual sandbox to test production changes in a non-production environment.