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How Robots and AI Are Transforming the Food Industry?

Automation in the food industry in manufacturing, processing, packaging, maintaining safety standards, and waste management, can help upscale its revenue and boost its capacity.

How Robots and AI Are Transforming the Food Industry?

Automation in the food industry aims at reinforcing aspects that are elemental to its sustenance but underachieving. Despite the industry being one of the largest, greater dependence on human labor to execute repetitive functionalities has deflated its economy. The ratio of production to demand is severely short. This, at times, disrupts the demand-and-supply chain causing inflation in foodgrain prices and food shortages.

An effective answer to this crisis is the incorporation of robotics and AI in the food industry. Several companies in food production have taken decisive steps in this direction. Various levels of functionalities, for instance, manufacturing, packaging, and delivery can be made efficient by constituting robotics in the food industry. On the other hand, artificial intelligence development can lead to the automation of processes that are performed manually, make production cost-effective, and minimize risks and errors.

A detailed analysis of the role of automation in the food industry is essential to understand the application of robotics and artificial intelligence comprehensively.

Table Of Contents

Challenges Faced By The Food Industry Today

The food industry has undergone a paradigm shift in character due to upheaval in the consumer demand curve and rigid environmental regulations. There is pressing urgency to better food quality, meet the ever-rising demand, ensure food safety, and also incorporate statutes on environmental issues like plastic ban, carbon emissions, etc. Companies have found a comprehensive solution to these challenges in the food industry through robotics and automation. 

The following infographic outlines the challenges in the food industry and the solutions—

  1. The food manufacturing enterprises that lack automation have reported a greater margin of error due to manual processing and no control mechanisms.
  2. Frequent disruptions in the demand-supply chain owing to limited production tolerance have also been a massive hindrance in the growth of the food industry.
  3. Manual execution of repetitive functionalities in the food industry has not only been costly and time-consuming, but also interfering in innovation.
  4. The process of data collection, structing market insights and following consumer trends has been rather strenuous to complete through traditional methodologies leading to delay in decision-making and eventually impacting the revenue model.

challenges in the food industry

How AI Can Upgrade The Food Industry?

In nearly every sector of the economy, companies have invested in artificial intelligence services in the handling and management of a range of functionalities. In the food industry, the utility of AI is substantial. For instance, the use of pattern recognition in sorting food products, and data science in structuring random data can be advantageous. Deep learning in processing and packaging, and machine learning in revenue prediction can be deployed for better outcomes.

Trend Forecasting in Food Industry

Trend forecasting is a method that enables decision-makers to take appropriate action based on predictive analysis. In the food industry, ML-based algorithms can render detailed insights into the upcoming ups and downs. This can prove to be an excellent tool for anticipating customer preferences and keeping the trends under inspection.

Integrating trend forecasting in the food industry can provide impetus to companies in achieving their revenue targets. Manufacturers can make informed decisions as per the insights and make adjustments to their functioning to make profits with food data accordingly.

New Product Development Using AI

A remarkable food product is an amalgamation of consumer preferences, healthy character, and a sustainable process of manufacturing. By collecting insights from consumer trends, AI can lead to new product development.

AI-powered programs can form new recipes and design new products. It deploys computing, machine learning, and data analytics to make food products tastier and easier to cook. Cognitive abilities to cater to human requirements are also applied by AI chefs. A prominent example is Chef Watson by IBM that can be a great companion to chefs in the kitchen in examining dishes and suggesting recipes.

AI in Food Processing and Product Sorting

Packaging and shipping manufactured goods to the markets in the food industry are two of the most crucial operations in the food industry. The process, however, is so monotonous and tiresome that the error quotient in the case of human involvement increases to detrimental levels. Thus, automation in food packaging can provide an effective solution to this problem.

  1. AI-based systems to execute packaging operations can reduce the margin of errors to a non-existent level. 
  2. AI-based solutions in the food industry can provide impetus to the rate of production to sustain the demand-supply chain.

AI in food processing renders intelligent solutions employed through a variety of tools and approaches. These include laser and X-ray technologies, high-resolution infrared cameras and spectroscopy. These technologies are utilized at the input channel to evaluate food commodities and sort out bad products through in-depth scanning and thorough examination. In comparison, traditional systems could only discriminate between good and bad items based on their appearance.

The deployment of AI-based systems in food packaging and product sorting has also several economic benefits. On one end, the cost of manual labor is cut, and only operational cost remains. While on the other end, sanitation of impeccable standards through cleaning food processing equipment is assured. Furthermore, decision-making through predictive analysis and demand-supply chain management are also kept in balance.

AI in Food Safety

AI-based systems and robotics can be sterilized and, therefore, are suitable for the food industry. It is due to this characteristic that the possibility of contamination in food products is reduced to zero. This in turn reduces the risk of foodborne diseases and food poisoning.

In several cases, food grains like wheat and pulses, and oilseeds like mustard and sesame are stored unpackaged in large godowns over longer periods of time without refrigeration. This is done to maintain a buffer stock to meet demands in extraordinary circumstances. However, these grains do get contaminated in humid conditions and lead to the development of various diseases and symptoms in humans.

The role of AI in food safety is to ensure such instances of errors do not occur. Additionally, as a solution, AI-based automated systems can measure and identify the contamination status of a food product efficiently. This is made possible by Next-Generation Sequencing or NGS.

NGS (Next-Generation Sequencing) is a method of sequencing that strengthens food safety and security through data collection, analysis, and extensive testing. It can measure contamination and prevent possible hazardous implications through genome examination.

EN (Electronic Noses) are basically electronic sensing devices that examine odors to determine food quality and food spoilage. The application of the device also consists of data acquisition and data analysis through machine learning algorithms to identify degrees of falsification and read the manufacturing process.

AI in Food Waste Management

It is estimated that a total of 17% of the food produced globally is wasted. Out of which, 7% is wasted in retail and services. The economic cost of that percentage is approximately USD 1 trillion per year!

These insights put light on the inefficient management of food waste. Integration of AI and ML-based systems not only at the stage of manufacturing but at cultivation can enhance decision-making capacity and reduce instances of food waste.

  1. AI can monitor the growth of plantlets and crops and predict or notify when the fruits, vegetables, or grains are ready for harvest. 
  2. In addition, deep learning can also provide insights into what fertilizers to use to expedite growth. 
  3. AI-based food analytics and tracking systems can give information on the shelf life of the product and trace the most suitable period of sale.

All these methods would help in the overall reduction of food wastage by helping manufacturers in product management, assuring food safety, and reducing wastage.

AI in Supply Chain Management

Like every major industry vertical, the food industry has its own massive supply chain system. The inclusion of AI in the supply chain has wide applicability, such as inventory management, demand forecasting, and more. The operation commences at the primary level of food crop cultivation and runs up to packaging and delivery. Let’s take a look at these steps in brief in the following section.

  1. Smart Farming-– AI can use to monitor crop growth, alert against instances of infestation, measure humidity and temperature, soil moisture and nutrients retainment, etc., to aid in farming.
  2. Healthify Junk Foods— By running deep-learning algorithms, AI can be used to prepare healthier renditions of food labeled as junk by customers. The need to address junk-food addiction can also be addressed in an efficient manner through this mechanism. Hoow Foods, a food formulator platform, aims to transform junk and addictive food products into healthier renditions. Their procedure involves matrix analysis of the food product, ingredients mapping, and redesign of constituent elements.
  3. Machinery maintenance— AI can be used to generate alerts when a piece of equipment or machinery is due for servicing. This is a cost-efficient practice as maintenance, if delayed, can be costly.
  4. Automated Food Packaging— AI can be integrated with robotics to automate food packaging. AI can bring design improvements, ensure pin-point accuracy, detect faulty products and forward it for removal or renovation. 
  5. Food Sorting and Quality Control— As previously mentioned, AI-assisted machinery can automate the process of sorting packaged food products. Similarly, equipped with high-end techs like IR spectroscopy, AI can easily detect food spoilage ultimately reducing revenue deficit.

AI in the food industry

Transformative Role of Robotics in the Food Industry

From the stage of sowing seeds to processing the harvest, cooking, adding the secret ingredients, packaging, and readying the product for delivery, the application of robotics in food industry is nothing short of transformative. This can be facilitated through drones, armed bots, and heavy machinery programmed to carry out standard functionalities.

The utility widely aims to influence agriculture through smart farming and predictive analysis, and automating food packaging, food sorting, and storing. Let’s study these sections in brief.

Robotics in Agriculture

Agriculture is an extensive activity. It includes various sub-sections like horticulture, floriculture, poultry farming, dairy farming, and so on. The indulgence of robotics in agriculture can automate and escalate routine tasks like plowing, soil monitoring, harvesting crops, measuring water levels, collecting milk and eggs, etc. Two-armed robots, drones, and heavy machinery can be programmed to carry out tasks with efficiency.

Smart farming promotes the usage of technology to enable scientific methods of cultivation. For instance, drone technology can promote scientific farming by performing spatial analysis, moisture measurement, and field reconnaissance. This is made possible by the high-quality infrared camera setup installed on the drone. Similar is the case with machinery and other types of equipment operated in cultivation. These include tractors, harvesters, combines, planters, sprayers, and many more.

Robotics in Food Delivery

So far the implications of robotics in food delivery are concerned, drone technology is the major case in point. Drones are already used in the contactless delivery of goods and groceries. This is not only cost-effective on the operational level, but also saves time, reduces cost, and enhances efficiency. Drones are equipped with sensors and stereo-vision cameras to improve accessibility and avoid instances of accidents. The method is also sustainable as it replaces fuel exhaustion that is there in conventional methods of delivery.

Robotics in Cookery

The use of robotics can also be applied to the cookhouse. These are mostly in the form of two-armed robots that imitate human behavior and decision-making skills while cooking. The robots, thereafter, apply deep-learning mechanisms to develop their own cookery skills. To enable imitation, the robots are equipped with sensors and optic cameras.

Recently, a UK-based company, Moley Robotics,  constructed a robot inherently for cooking. The robot can skillfully add and mix ingredients, flip bread and stir meals, and cleanse utensils effectively. 

Robotics in Food Manufacturing

The implementation of robotics in food manufacturing has already penetrated the industry. The efficacy applies in sorting, grinding, extrusion, agglomeration, mixing, etc. Another notable type of machinery includes an armed robot. These can be multi-joined or overhead-picking arm robots called ‘delta robots’.

For instance, a US-based startup, Zume, commissioned Vincento, a robot to perform smaller tasks in preparing pizzas, such as, making the dough, and baking the crust thoroughly and properly.

Robotics in Food Packaging

The involvement of robotics in food packaging in the industry, as per a survey conducted by the Association for Packaging and Processing Technologies, estimates to be 94%. The implementation of robotics has resulted in enhanced productivity with more than 100 products processed and packaged seamlessly.

Additionally, the integration of robotics in food packaging can enable a sustainable approach and ensure confirmation of the environmental regulations set by the government. Machinery can be geared with biodegradable and sustainable materials to use in packaging. Outside of these usages, robots can also box, sort and warehouse products as programmed.

Benefits of AI In The Food Industry

The yield on investment in robotics and AI in the food industry will be monumental over the next several years. It has been estimated that the market valuation for automation in food processing will reach $29.4 billion by 2027. The investment would be meant to escalate the rate of manufacturing products, automate packaging, ensure food safety, and manage food wastage. Larger implications of these provisions would be aimed at culminating manual labor and replacing direct human contact with a machine-embraced approach to carrying out tasks.

To summarize, the benefits of robotics and AI would have lasting impacts on the following aspects of the food industry—

  1. Facilitating a consumer-centric approach in food manufacturing— Factories with a massive production rate are equipped with AI-powered machinery to automate food manufacturing. ML algorithms continuously study consumer trends to enhance product quality and devise new recipes. 
  2. Efficient food packaging and sorting— AI in food packaging, sorting, and warehousing can facilitate an increased rate of production and cut costs on shipping.
  3. In-depth computation to ensure food safety standards— Robotics can be programmed and integrated with AI to guarantee food safety standards and ensure the units are streamlined with the legislation.
  4. Environmental-friendly food waste management— AI and ML-based programs can effectively ensure a sustainable food waste management cycle by installing checkpoints during the process of food manufacturing, and, in turn,  generate an economy of $127 billion a year by 2030.
  5. Reduces additional expenses and optimizes costs— Automation can relay economic advantages as it reduces expenses on human capital, and infrastructure maintenance, and enables an efficient cleaning process.
  6. Enhances customer experience— Integration of AI also improves customer experience through neural learning of market trends and consumer preferences.

Challenges of Using AI In The Food Industry

Integration of robotics and AI in the food industry, as has been emphasized throughout the article, presents extensive advantages. However, the industry could face financial stress and social adversaries through unemployment. The challenges of using AI in the food industry are explained below.

  1. High Installation And Maintenance Cost— Owing to the ever-increasing business demand for AI incorporation, the cost of installing the automation apparatus has increased. In the food industry, the utility of AI efficiently applies to minimizing the margin of error and streamlining with customer trends.
    Powering the food industry with AI can be expensive due to the operational and functional aspects. For operating AI-powered machinery, the need for a dexterous task force is needed. Similarly, the cost can also shoot up depending on the functionalities AI is deployed to carry out. The greater the usage, the more the cost.
  2. Job Cuts—Automation of functions in the food industry, specifically on the scale of manual labor, would lead to massive job cuts. This contention comes from the question of whether AI would replace human labor.
    While it can be said that losses in jobs would occur due to the integration of AI and robotics, alternatively, the demand for highly skilled and high-paying jobs on an operational level would witness a significant rise.
  3. Concerns Regarding Unethical Practices— By now it is evident that AI can improve the standards in the food industry to excellent levels. However, concerns regarding the manipulative usage of AI to only build profit while ignoring quality have been put forth. At times, companies prefer unethical methods of making addictive products to make a profit. Therefore, AI deployments must be regularly monitored and checked for any breaches.
  4. High Dependency on AI—Utmost dependency on AI, from carrying out simple tasks to high-level decision-making, can have disastrous implications. Triggering decisions based entirely on datasets can have downgrading impacts on food quality and resource management.

Future of The Food Industry With AI

The food industry is constantly losing value owing to undue dependence on conventional approaches. It has not only led to a widening margin of errors but also held back what the larger potential the industry is capable of accomplishing. With automation and AI-powered machinery, the future of the food industry can become more advanced. Some instances include the following—

  1. Smart Kitchen and Robot Chef— Kitchens at homes and restaurants can also be integrated with artificial intelligence to maintain food safety standards and aid in cookery. Additionally, robotics can also be added to the kitchen to aid in manufacturing, checking food quality, and upkeeping the cleanliness of types of equipment. In the preceding sections, we have already discussed Chef Watson by IBM that aids chefs while cooking and suggests recipes. 
  2. Research Labs for Food Processing— Growing food in a controlled setting as in the case of research labs, can aid in optimizing quality and assuring consistency in the rate of production. Datasets collected from the labs can then be put to use in a wider setting to attain maximum output and efficiency.
  3. Equitable To Safe and Quality Food— The advantages that AI’s utility brings to the food industry can be used to build strategies to ensure wider access to safe and nutrient-rich food. This use case would have lasting implications in countries grappling with food insecurity. 

How Appventurez Can Facilitate Your Business With Artificial Intelligence Solutions?

At Appventurez, we follow the advancing utility of AI-based technologies in various industry verticals with enthusiasm. The utility of automation through the integration of AI-based systems and robotics has been widely acknowledged by our team of developers. If you run a food business, perhaps a restaurant chain, or are planning on building an on-demand food delivery application to cater to the rising demands in your locality, a long-term collaboration to build a bespoke application is needed.

With the expertise amassed over the years through hundreds of mobile app development projects, we guarantee world-class product delivery that not only provides a seamless user experience but also fulfills its market requirements. For a two-way communication channel during the development process and an on-time delivery of the product, collaborate with Appventurez today!

Artificial Intelligence Solutions

FAQs on Robotics and Automation in Food Industry

Q. Why automation is important in the food industry?

The food industry needs automation to effectively address the challenges holding back its potential. AI-based systems and robotics in the food industry can reduce the margin of error, elevate the rate of production, collect and structure data to render effective decision-making insights, and automate repetitive tasks.

Q. What is the role of robotics in the food industry?

Robotics in the food industry has wide applicability across segments, such as making cultivation efficient through mechanization, assorting raw material into manufactured goods through a systematic approach, ensuring safety standards, and better packaging.

Q. How is AI used in the food industry?

Implementation of AI-based solutions in the food industry is done in food processing and packaging, food safety and waste management, and revenue analysis.

Q. How do you automate a food business?

Automation of a food business can be done at several levels through robotics and AI technologies, such as manufacturing and packaging, food ordering, safety standardization, stock management, and cost-benefit analysis.


Anand Prakash

Co-founder

One of the Co-founders at Appventurez, Anand specializes in sales and business development as its VP - Sales and Presales. He supervises the pre-sales process by upscaling on establishing client relationships. He skillfully deploys instruments such as cloud computing, automation, data centers, information storage, and analytics to evaluate clients’ business activities.

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