The AI-Powered Shift in the Food and Beverage Industry

Manufacturing in the F&B Sector Happens in Vast and Extremely Complex Factories. Predictive Quality Analytics Is a Branch of Core AI That Is Helping Manufacturers Attain Control over Their Costly Machinery Production Processes

The Food & Beverage (F&B) industry has been thriving since the 19th Century. The industry truly took form when Nicholas Appert and Louis Pasteur developed canning and pasteurization respectively. Today, this industry is a juggernaut that has the potential to cater to the entire human race.

The industry picture presented above is on a generic scale that involves the growth and consumption of packaged food, worldwide. However, AI currently is helping industries like and similar to Nestle, Pepsico, and Coca-Cola, that manufacture and package F&B products for a very large group of buyers.

Before understanding how manufacturers are leveraging AI capabilities, here are a few facts about F&B consumption-

  • 2018 will see the F&B industry garner an estimated revenue of US $90.173 billion
  • India, China, and Brazil are three of the largest emerging markets for F&B companies
  • The United States tops as the global market in F&B consumption

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Hence, the market for the F&B industry is very large and is growing extensively. To keep fuelling this machine, the industry is heavily dependent on its manufacturing arm(s) and allied ancillary units.

The F&B Nexus

The F&B sector comprises of various segments. Each segment can be categorized as an independent industry per se. Further, every segment needs inputs in the form of raw materials, equipment, logistics etc. Manufacturing is usually done using capital-intensive machinery. The manufactured goods are then distributed through various channels.

Hence this industry is an integrated chain of suppliers, vendors, utilities, labor, stakeholders, ancillaries, manufacturing etc. AI is now making significant changes to the actual manufacturing of F&B goods.

Predictive quality analytics is a branch of core AI that is helping F&B stakeholders attain control over their costly machinery. The F&B industry has welcomed this technological endeavor because it has lead to saving time and money.

Manufacturing in the F&B sector happens in vast and extremely complex factories. The process is continuous with round the clock output. F&B factories have long assembly lines that go through a series of machines in the factory’s labyrinth.

What happens if the production stops? Every F&B manufacturer’s biggest fear is facing a possible factory shutdown due to a fault in the equipment. Engineers who maintain the machinery are not always able to find faults quickly. This results in losses.

Factories also go through large amounts of downtime, even if the fault is found instantly and is fixed.

Furthermore, if the fault is irreplaceable, it could result in complete machine damage which leads to a tremendous monetary loss.

Hence, the industry sees very few new entrants. The risk is too high when compared to the gains. But, this will all be changing. New entrants and established players can now both leverage Predictive Quality Maintenance capabilities to be in full control of their machine’s lifecycles.

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What is Predictive Quality maintenance?

Predictive Quality Analytics is the technique of deriving meaningful insights about machine behavior. The process usually involves embedding sensors, software etc. on physical machines and collating raw data about machine performance. This data is then processed from a business goal perspective and applied in stages to Operation Technology, which is technology related to physical machinery.

Today, due to the surging demand and quality requirements, enterprising F&B brands are investing heavily in new machinery. This machinery allows them to explore newer avenues of pasteurization, high-pressure processing, UV treatment, and nanotechnology.

This is an additional expense with existing machinery which might be aging. Combined, it adds more pressure on a business to generate Return of Investment. With predictive quality analytics, businesses can at least not have to worry about machine maintenance.

Predictive quality analytics also substantially helps-

  • To predict bottlenecks
  • To find machine failures
  • To redefine and invent error classes
  • To find agents that are hampering productivity

As time passes, Predictive Quality Analytics will help stakeholders proactively decide the future course of action. It will help companies improve software quality and control results in test projects.

Organizations that specialize in integrating Predictive Quality Analytics intend to transform a physical machine into a digital model. Predictive Quality Analytics Platforms are then able to clearly see all aspects of a machine and help F&B brands gain actionable insights.

Consider this technology to be a hyper-advanced version of a scanning machine found at airports which detects items in luggage that cannot be seen by the naked eye. When officials use this machine for a brief period of time, they can predict if a person may be carrying something illegal.

Similarly, one of the biggest advantages of Predictive Quality Analytics is it can raise flags about machine maintenance/failure, in advance. This is especially important in larger plants and longer assembly lines where fault-finding may take days, even months. Embedded technologies on machines tag them to the nerve center of the entire plant. Nerve center operators can easily detect which cog in the entire machine system is bleeding.

Such information is key to save costly machinery from large-scale damage. The technology also substantially amplifies machine performance.

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The F&B Industry Should Act Now

This is a fool-proof chance for the F&B industry to secure their operational assets. Predictive Quality Analytics is a cutting-edge technology that resolves several critical problems for the F&B industry. Further, combining other aspects of AI with Predictive Quality Analytics opens new doors to develop future-ready products.

The only precaution that this industry needs to adhere to is choosing the right partner. Food and Beverage brands should choose their technology partners that sync with an enterprise’s expectations. There are only a handful of companies that implement Predictive Quality Analytics.

Seebo, and its predictive quality solution, is a prominent technology implementation partner that integrates industrial machine learning into manufacturing processes. Their proven track record and impressive customer testimonials indicate strong delivery capabilities in the F&B enterprise.

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