Over the last decade, advancements in machinery and automation have provided manufacturers with a wealth of data about their operations. Unfortunately, their understanding of the meaning and usefulness of that information has lagged behind their ability to collect it. How we segment and parse data, how we mine it for patterns that teach us new lessons about the future of our operations, depends on how well we understand the real value of what we have.

Many companies have explored data analytics through big datasets. Few have developed the insights they expected from these assets. The missing link is a clear connection between the use of data and the ways to make incisive business decisions.

The real value of data

Today, we can combine advanced application engineering, process data, and marketing knowledge to find insights that help run businesses more effectively and profitably through new methods and mindsets. These analyses create better outcomes for manufacturers in all industries, including food processing.

The combination of AI and advanced mathematical tools makes it possible to access these insights and transform existing datasets into predictive assets. The advanced mathematical algorithms accessible through AI enable individuals to see patterns in their data that the human brain can't perceive on its own. Once AI makes these patterns clear in nearly infinite amounts of information, manufacturers can make well-founded decisions based on them.

AI and automation

Like automation, AI has been met with concerns about job loss and decreased worker value. Instead of replacing human workers with electronic tools, AI will enable people to expand their experience and accomplish analytical results that otherwise would lie beyond their capabilities. AI makes it possible to formulate a question about a dataset and receive an analytical answer based on patterns that only a well-designed algorithm could recognize.

Automation enables human workers to opt out of repetitive tasks that are physically taxing but otherwise unrewarding. Just as automation has improved processes and spared human workers from tedium, drudgery, and even danger, AI will broaden the understanding of businesses and their potential. While automation improves physical aspects of the workplace, AI now finds new ways to improve the company's vision of its future and even the overall plan of its physical plant. This combination of hypothetical and practical will become invaluable to companies that care about optimizing their opportunities.

The transformative power of practical secrets

AI can help food processors discover the trends that unlock the secrets of greater yields. Some of those secrets lie in the timing of interconnected events and decisions. Others are revealed through the analysis of otherwise invisible patterns in production data. Once processors increase those yields, the increased output goes on to enhance cash flow, which then frees up assets for business improvement. Meanwhile, as processors make individual jobs more rewarding, they minimize employee turnover and make room for better opportunities. The overall impact is positive for every aspect of the company's business.

At the same time, AI can help processors transform their approach from reactive to proactive. Instead of waiting for trends to appear and trying to figure out how to capitalize on them, AI enables food processors to know when to expect them and how to make them productive. These predictive capabilities improve scheduling of everything from production to maintenance—and they eliminate the emergencies that result in all-hands-on-deck overtime to fix a problem that could have been foreseen and forestalled.

The challenges of innovation

Every new technology inspires fascination with its capabilities. The interest in AI has reached global proportions. Companies look for ways to use it. Without a knowledgeable plan for implementation, they may overestimate what it can offer them and how readily it can produce those results. The biggest and most primary question to address before planning AI implementation is "What do we want this to do for us?" If a food processor lacks a clear vision of what to expect from the technology, they will have difficulty selecting a meaningful solution—and are likely to be disappointed in their results because of poor planning. This can result in multiple investments as the facility chases a solution that continues to elude them.

As food processors consider implementing AI, they also need to ensure that their automation systems can coordinate with the new technology they plan to add. AI and automation cannot work optimally if each operates in a miniature world of its own. If the plant's current automation lacks the versatility to optimize integration with AI—or simply cannot benefit from it—then that opens the way for other questions about how to proceed.

Beyond the costs of technology investment and the need to ensure smooth integration with existing automation, food processors also need to explore available training assets and the extent to which their workforce will need to learn new processes. This is a scenario in which a collaborative approach can yield big dividends for the plant operator who brings their workforce into the integration process early enough to assess aptitudes and plan ahead for instruction. Once employees see the benefits of a well-planned AI implementation, their enthusiasm will go a long way toward technology adoption.

The value of change

Perhaps AI's most important contribution to the food processing industry will be AI's ability to free producers from their own expectations. This is an industry that has taken a hands-off approach to new tools and techniques. Once AI makes the future clear from the patterns it discovers in accumulated data, those revelations will enable the industry to optimize the productive parts of its traditions and update the parts that simply have been slow to change. 

The question is not whether AI has the ability to contribute to the food processing industry. The question is whether the food processing industry is ready to ask AI the right questions. If so, the intelligence that is integral to both automation and AI will move the industry forward toward new successes that set aside old habits.