by Prateek Joshi
A coherent data collection system can open new doors for industrial operators in the food and beverage industry. To build this system, they need to use internet of things sensors that can collect data in a continuous manner. It should be a key component for companies looking to streamline their operations.
Collecting and storing data is critical, but it’s certainly not enough. Extracting insights from that data and leveraging them properly is still a significant challenge. In a recent industry survey of manufacturing professionals, it was revealed that only 12% automatically take action on their data insights.
Food and beverage companies are employing artificial intelligence applications that can process and analyze data about critical assets such as water, chemicals, and labor to optimize their operations at every level. As the food and beverage industry continues to use AI, the industry is improving product quality and producing more SKUs, which are driven by continued efforts to keep safety standards at specific levels. These standards include their equipment, resources, and company performance.
The food and beverage industry had estimated revenue in 2018 of $90.1 billion, but continues to be very complex and involve many moving parts. As competition becomes more intense between companies, small improvements are becoming necessary to stay ahead of competitors.
We’ve moved away from a few early adopters to an increasing number of food and beverage operations using or attempting to use these technologies in their day-to-day operations. These technologies provide the ability to collect a wealth of data at nearly every point of the food and beverage manufacturing process.
Here are three ways food and beverage companies can use AI in their daily operations to streamline production and improve their bottom line in 2020 and beyond.
Reducing unplanned downtime
Unplanned downtime can be detrimental to large and small food and beverage operations and costs companies $50 billion annually. The use of AI applications can analyze thousands of incoming data points from existing systems and alert operators to impending maintenance issues before they become problems. This can significantly extend the life of equipment by catching problems with critical assets before they impact production.
AI applications also have the potential to determine the root cause of equipment downtime or safety incidents. This ability leads to centralized data readouts that can prevent redundancies and improve team collaboration. To continue expanding production, the ability to have complete control and insight into the operations can be the difference between an average and extraordinary year.
Improve company efficiency
Nearly half (48%) of manufacturing professionals say their companies use spreadsheets or other manual data entry documents for monitoring their company’s workflows. But the use of these data entry tools can bring its own set of problems, including the inefficient use of resources and the possibility of costly mistakes.
AI can automate processes and tasks to uncover inefficient uses of company resources, allow employees to view large amounts of data in real-time, and decrease the unintentional mistakes that can be caused by manual data entry. Almost half (49%) of manufacturing professionals also said that they are using AI to increase efficiency in their business processes. Companies can solve inefficiencies on production lines just by utilizing data analytics. In addition to that, they can improve the process efficiency and yield of production facilities while maintaining optimal product quality control.
The use of these machines to perform tasks in food and beverage production that previously required human labor can significantly reduce errors and inconsistencies and improve overall efficiency. These pieces of technology are also already being used to measure the size and weight of products that allows companies to stay in accordance with food safety standards and regulations.
Automate micro-decisions to gain proactive insights
Repetitive jobs that require constant supervision are better suited to AI. The ability to have a machine perform laborious tasks can significantly free up workers and allow them to focus on more cognitively involved tasks, especially as the food and beverage industry faces issues with less interest from younger people in joining the industry.
But the challenge remains in how to implement these forms of AI and automation in the food and beverage industry and the manufacturing space as a whole, with 49% of respondents to a recent industry survey saying that automating tasks is a top business challenge.
AI applications can bridge the gap for workers who are taking on more data-centric tasks in their jobs and help the food and beverage industry bolster its future workforce.
With a mature data collection and analysis infrastructure, AI can help automatically uncover ways to increase efficiency. On top of that, it can save money and keep operators informed of upcoming issues. However, a majority of manufacturers (84%) recently said their data infrastructure was not able automatically and continuously act on their data intelligence. This leaves opportunities to further utilize AI.
Operators in the food and beverage industry need to find ways to monetize the oceans of data they already collect. Despite this realization, business challenges remain in tracking budget and costs. They need to connect production yield, sensors and IoT hardware with the financial realities. When companies embrace these pieces of technology, they have the ability to gain insights through every stage of production.
As companies continue to grow their operations, the use of spreadsheets and other manual processes becomes cumbersome and inefficient. It slows down a company’s ability to grow. By shifting the company focus toward the increased use of technology, the food and beverage industry has the opportunity to profoundly impact its operational efficiency and drive growth.