The dairy industry faces several significant challenges, such as optimizing logistics and ensuring timely deliveries. These challenges can be effectively addressed through the combination of robotics and advanced software solutions.
Quantifiable improvements include an increase in production rates, enhanced operational efficiency and greater accuracy in inventory management. For instance, the introduction of robotics can significantly cut transportation time, while software systems can reduce stock discrepancies.
Many CPG companies need to install newer equipment that makes use of artificial intelligence (AI) and digital processes, and find workers who can operate it. Rebecca Marquez, director of custom research for PMMI, said research conducted by the organization found labor to be one of the most significant challenges across the board.
“Our members are seeing it, their customers, the CPGs, are seeing it,” she said. “Even keeping machine operators, who don’t necessarily have to understand that level of AI, it’s really difficult for them to keep people on.”
Companies are investing in more automated equipment as one way to cope with the labor issue, the report said. The machines do palletizing, case/tray handling and labeling. Marquez said multipacks and mixed pallets are trending, which also affects how the pallets are stacked and transported.
Robotics
A recent study by McKinsey & Company revealed that automation technologies, such as robotic picking systems, can improve operational uptime by up to 30% within a few years. This allows for faster order fulfillment and reduces the likelihood of stockouts, which can be detrimental in the perishable dairy sector.
“Robotics and advanced software technologies are crucial in enhancing efficiency within the dairy supply chain,” said Raymond Pan, general manager for the Americas at Pudu Robotics, which provides this tech to dairy companies.
For instance, the PUDU T300 automates the delivery of packaging materials, thus reducing operational bottlenecks and improving workflow efficiency.
“The T300’s advanced maneuverability allows it to navigate narrow corridors often found in dairy processing facilities, contributing to streamlined material handling,” Pan said. “Combined with software solutions like inventory management systems, which provide real-time tracking of inventory levels, these technologies facilitate timely restocking and minimize stockouts.”

Mathias Konne, North America business head, food, for Stäubli, a Switzerland-based company that provides robots to dairy processors, noted industrial cheese production presents several challenges; including direct contact with unpackaged food, high hygiene standards and regular rigorous cleaning procedures.
The company’s robotic solutions, from delivery to processing and packaging, do away with these concerns by offering safe, flexible automated production of dairy products.
Among its clients are Big Drum Engineering GmbH, which uses Stäubli TX90 HE robots to manufacture equipment for ice cream packing and filling operations; an Argentinian dairy that uses robots to handle six tons of unpackaged soft cheese per hour; and a Dutch dairy processor that utilizes two robots for de-rinding cheese wheels, impressively removing the rind in less than 30 seconds.
“Our extensive portfolio of four- and six-axis robots guarantees the systematic automation of every process on a hard cheese production line,” Konne said. “From the infeed of Euro blocks or cheese wheels, through dividing, cutting and portioning, to primary and secondary packaging with subsequent pallet stacking, Stäubli robots enable ultra-efficient hard cheese production.”
Furthermore, Stäubli WFT’s highly flexible AGV solutions transport finished pallets to the warehouse or directly to the shipping department without any human intervention.
James Newman is head of product and portfolio marketing at Augury, which offers prescriptive AI for some of the world’s largest manufacturers. He said for repetitive tasks, robotics both free up employees to work on other tasks that aren’t as easily automated, and reduce task-related injuries. Plus, because robots can improve precision and control, companies may also see higher product quality.
Software solutions
From a software perspective, the introduction of AI-driven analytics into the dairy supply chain can have significant impacts.
“One dairy producer used AI-driven insights on a single process line, in real-time, to improve throughput and yield by 1.6% annually, without reducing quality,” Newman said. “An improvement of 1.6% per line becomes a truly quantifiable number that translates across numerous metrics, including customer satisfaction, waste reduction, emissions reduction, reduced cost per product produced, etc. Quantification of improvement is becoming less of a problem than the speed at which implementation can occur.”
Utilizing software solutions that incorporate machine learning and data analytics can also provide insights into inventory management, demand forecasting and logistics optimization. Companies using these technologies report improved accuracy in demand forecasting by up to 25%, leading to better inventory control and reduced holding costs, Newman said.
Mikael Bengtsson, strategy director for food and beverage at Infor, a New York-based software provider that works with numerous dairy companies, noted by collecting and integrating data across the supply chain — from suppliers, manufacturers, customers and consumers — organizations can gain visibility, enabling better decision-making.
“Advanced analytics, including AI-enabled predictive and prescriptive analytics, can be leveraged to forecast demand more accurately,” he said. “This allows for better planning in terms of inventory, production scheduling and resource allocation, ensuring that supply meets demand without overproduction.”
Amalthea implements data analytics to optimize its goat cheese manufacturing processes.
“Amalthea has worked with Infor’s team to leverage Infor’s AI service and applied it to big data collected throughout the cheese processing,” Bengtsson said. “By analyzing the data, AI can identify inefficiencies and suggest improvements. This not only boosts yield but also minimizes waste, contributing to both cost savings and sustainability.”
Optimizing yield also ensures that the same amount of raw materials produces more product, which directly translates into cost savings. For example, in the Amalthea case of goat cheese processing, better utilization of raw milk leads to higher production volumes without additional input costs.
“Savings can also come from maximizing equipment uptime,” Bengtsson said. “When certain equipment is down, the whole process may stop, and a lot of products might need to be wasted. This is very costly and adding to waste. With software solutions, unexpected stops can many times be avoided by collecting and analyzing equipment data and predicting issues before they occur so they can be addressed upfront.”
Real-time data
Real-time data collection can originate in anything from a digital entry on the receiving dock to a vibration or heat sensor in the processing equipment. Any delay in capturing the data electronically is a sub-optimization in the decision-making process.
“Sometimes there is too much data for the human to understand but then AI can be leveraged to understand the data, analyze trends, and predict and prescribe for better decision-making,” Bengtsson said.
The integration of advanced robotics with technologies such as the Internet of Things (IoT), AI and big data analytics are expected to have a huge impact on the dairy supply chain.
“Real-time data analytics provided by advanced software solutions will enhance decision-making, predictive maintenance and overall operational efficiency,” Pan said. “These trends will drive significant improvements in supply chain performance and adaptability.”