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Why AI should be on food/ag’s priority list

Dec. 17, 2018

It’s no secret that food waste and loss has hit crisis levels.

The Food and Agricultural Organization of the United Nations (FAO) recently reported that nearly 1.3

Canvass Analytics' Humera Malik

billion tons of food is wasted or lost each year—the equivalent of nearly one third of all food produced. In an era where the world demand for food continues to increase, the need to stem the losses and increase yield and productivity is paramount.

The application of AI and automation is mission-critical to meeting this growing global demand, while drastically improving yield and quality across the entire food & ag value chains.  

Food & ag meets AI

In food & ag, production reliability has traditionally been more of an art form than a science. Decisions were made based on operator expertise—the lack of real-time visibility into the production process left plants consuming more raw ingredients and energy than was needed, while producing inconsistent batches. However, over the past two years, thousands of production-line sensors have begun to create millions of data points on throughput, efficiency and quality. This is a good thing.

With AI, operators now have the data, processing power and speed to predict and detect costly errors across highly complex and dynamic production processes. AI makes it possible for operators to determine the optimal amount of raw materials, energy and cycle time required to produce higher grades of product, increase yield, and, most importantly, reduce waste.

For example, where a single variable change can impact the quality, cycle time, yield and product shelf life, AI gives operators the ability to identify outlier trends when parameters fall out of spec. These operators can make adjustments when anomalies are detected—not after the process has finished. Artificial intelligence is forever changing how decisions are being made in food & ag production.

How Olam is transforming sustainability with AI

With an increasing focus on reducing food loss and waste and operating in an environmentally sustainably manner, global agri-business Olam International recently announced a transformation of its operations to boost sustainability across its entire supply chain.

KC Suresh, managing director & CEO, grains at Olam said, “Artificial intelligence is a powerful tool to help reimagine global agriculture. The insights offered by data and analytics provide opportunities to transform the way we operate and to find new ways to address challenges across the agricultural value chains. By integrating emerging technologies into our business, we are driving greater efficiencies, enhancing the sustainability of our supply chains and offering more value to our customers.”

And they are not alone.

Sustainability is a common driver for companies applying AI across the food & ag industry. For example, we have helped a large food-ingredient company in North America introduce AI into their energy-production processes. In a matter of weeks, fuel costs went down by 4% and greenhouse-gas emissions will be reduced by 10+ million pounds of CO2 per year. In this case, our AI is forecasting (in real time) the optimal power and steam generation required from the plant while minimizing gas usage. Not only has this contributed to meeting the company’s overall sustainability targets, it has helped the plant to reduce energy costs.

The time is now

The food & ag industry is increasingly under pressure to produce products with better quality and safety, while reducing waste. AI’s ability to improve reliability across the value chain—while optimizing energy, raw materials and cycle times—is why it should be on every food & ag plant’s priority list for 2019.

Humera Malik is CEO of Canvass Analytics.