Pet food industry embarks on digital evolution

This article was published in the May/June 2025 issue of Pet Food Processing. Read it and other articles from this issue in our May/June digital edition. 

A recent trend in the pet food industry sees manufacturers increasingly turning to Industry 4.0 technologies to enhance productivity and operational efficiency. With facilities adopting new digital manufacturing solutions, they are not only optimizing production processes but also addressing labor challenges and minimizing waste. 

From advanced automation and IoT (Internet of Things) integration to data analytics and smart supply chain management, the latest innovations are reshaping how pet food companies operate, ensuring they meet the growing demand for quality products while staying competitive in a dynamic market.

Robotics can help manufacturers lower labor costs, minimize human error and improve workplace safety.

|

Source: Lyly Photography

“Automated systems now handle everything from raw material receiving and ingredient batching to packaging and palletizing, dramatically increasing production speed and throughput while reducing the reliance on manual labor,” said Scott Hungerford, automation and controls engineering manager for Burns & McDonnell, Kansas City, Mo. “These technologies not only lower labor costs but also minimize human error, leading to greater product consistency and improved workplace safety. Rather than replacing jobs outright, automation enables employees to focus on higher-value, more ergonomic tasks, enhancing job satisfaction and retention.”

Ryan Thompson, senior specialist for Industry 4.0 technologies at Kansas City, Mo.-based CRB, notes companies have various digital manufacturing strategies and different levels of maturity when implementing them. 

“Best practice is to have a governance model that allows for longer term evaluation of some technologies, measuring success and allowing for experimentation and fast failures,” he said. “Benefits are typically seen in four areas — productivity, quality, flexibility and speed — each of which has varying levels of importance for a company and can even vary from facility to facility.”

Powerful solutions

Nathan Kramer, technical resources manager for NorthWind Technical Services, Sabetha, Kan., notes that in order to help customers in the pet food manufacturing industry streamline production, reduce labor costs and eliminate inefficiencies, the company provides seamless integration between business systems and its control systems. 

“Work orders can be pulled directly from the business system into the control layer, eliminating the need to maintain formulas in multiple systems,” he said. “This ensures consistency between the order and the ingredients, while also allowing accurate data — such as material usage and labor clockings — to be sent back to the business system.”

NorthWind’s customizable Manufacturing Execution Systems (MES) solutions also deliver real-time data to those who need it most, allowing production leads to quickly see if they’re on track to meet daily goals, while helping operators gain visibility into how upstream and downstream systems — from milling to packaging — are performing, and how that performance impacts their part of the process.

“We also help reduce plant floor paperwork by digitizing operator checks and data entry,” Kramer said. “Instead of relying on manual logs or printed forms, operators can complete required checks through our system, making the information immediately available to supervisors and support staff. This not only reduces errors and delays but also supports compliance and traceability efforts.”

NorthWind is also actively developing artificial intelligence (AI) capabilities within its platform, PlantIQ, to address complex challenges that traditional software can’t easily solve, such as predictive analytics, process optimization and system diagnostics. 

“By combining deep industry knowledge with advanced digital technologies, our solutions help pet food manufacturers become more agile, data-driven and efficient,” said Nathan Kramer of NorthWind Technical Services.

“We’re also working on a semi-automated solution for measuring kibble density and dimensions, which reduces the time it takes to do manual checks while improving consistency and product quality,” Kramer added. “By combining deep industry knowledge with advanced digital technologies, our solutions help pet food manufacturers become more agile, data-driven and efficient.”

Hungerford noted Burns & McDonnell leverages a comprehensive engineer-procure-construct/design-build approach to embed digital solutions directly into facility design, yielding seamless alignment between infrastructure and operational goals from the outset. 

“This unified methodology not only streamlines implementation but also minimizes inefficiencies that often arise when digital systems are retrofitted into existing operations,” he said. “For pet food manufacturers, the adoption of digital manufacturing tools is transforming every facet of production. Digital checklists, for example, are now routinely used to enforce rigorous safety protocols and reduce human error during audits.”

Gray AES offers model-driven MES frameworks that allow clients to standardize operations across multiple facilities, enabling faster deployment and continuous improvement, predictive analytics for asset maintenance and raw material variability, and integrated track-and-trace systems that provide complete lot-level visibility, supporting food safety and recall readiness.

“Our approach has been instrumental in our customers’ ability to reduce downtime, improve batch consistency and enhance planning cycles with centralized recipes,” said Amanda Flowers, senior director of digital transformation for the Lexington, Ky.-based company. “We provide industrial Internet of Things platforms to collect and contextualize data from equipment and sensors, cloud and edge architectures to enable scalable, secure data visibility across sites, and advanced analytics and dashboards for OEE, energy consumption and predictive maintenance.”

Enhancing operational efficiencies 

Industry 4.0 involves connecting physical and digital worlds in manufacturing. Technologies include Internet of Things (IoT), artificial intelligence and cloud computing. 

|

Source: ©AIMANJUNOH – STOCK.ADOBE.COM

Many processors are turning to data analytics and IoT to enhance operational efficiencies and improve quality.

“With the rise of ChatGPT in 2022, we really began to see a huge uptick in interest in AI and machine learning,” Thompson said. “For pet food manufacturers, we’ve seen a few common use cases. Using the ideal production run, or a ‘golden batch,’ operations can be informed when deviating from ideal conditions and encouraged when operating on that golden path. This is a great way to get started, since it delivers value quickly, begins to build a digital culture and does not require specialty roles like data scientists.”

Other analytics use cases on the rise include cleaning optimization and scheduling optimization. These can reduce the amount of time an asset is unavailable by looking at production volumes over the long term and developing changeover strategies to reduce production downtime.

“IoT can be useful depending on the level of sophistication of current automation systems,” Thompson said. “Most modern facilities already include digital instrumentation and PLC control, so leveraging that data becomes easy. For older systems that are manual, adding IoT sensors can deliver value at a low cost. An example is installing sensors to know when a production line is down (and integrating that into an OEE system), using vibration sensors to perform predictive maintenance on motors, or using temperature sensors to monitor heat exchangers and steam traps.”

Hungerford noted IoT sensors and automation technologies are being deployed to optimize critical processes such as extrusion, batching and packaging, which have yielded significant benefits, including enhanced workflow efficiency, improved product consistency and measurable reductions in labor costs.

AI is another game changer in the industry. AI-driven tools are optimizing pet food formulations for both nutrition and cost, enabling manufacturers to develop personalized diets based on pet health data and market trends. 

“Machine learning algorithms are also being used for predictive maintenance, continuously monitoring equipment health and predicting failures before they occur,” said Scott Hungerford of Burns & McDonnell.

“Machine learning algorithms are also being used for predictive maintenance, continuously monitoring equipment health and predicting failures before they occur,” Hungerford said. “This approach minimizes unplanned downtime and facilitates smoother, more reliable operations.”

Quality control has also benefited from technological innovation. Inline detection systems, such as metal detectors and X-ray machines, automate the inspection process identifying contaminants in real time and reducing the risk of recall or brand damage. Computer vision and machine learning further enhance quality assurance by detecting product defects and inconsistencies that might escape human inspectors. These systems help every batch meet rigorous safety and quality standards, which is critical in an industry where consumer trust is paramount.

In NorthWind’s controls and MES systems, it captures data not only from machines on the plant floor but also from external sources like ERP systems or quality systems, thereby bringing these data points together and providing a unified view that supports better decision-making.

“For example, we can display quality metrics alongside the specific control points that influence them, helping teams quickly identify the root causes of variation,” Kramer said. “We can also combine bin level data from the floor with inventory levels from the ERP system in a single report. This eliminates the need for manual data collection and reconciliation, allowing users to spend less time gathering information and more time acting on insights to improve processes, maintain quality, and stay ahead of daily production demands.”

Digital challenges

The shift toward automated, digitally driven manufacturing processes brings significant opportunities and equally significant challenges. 

One of the critical hurdles that Burns & McDonnell has identified involves integrated complexity.

“Legacy systems often clash with modern automation technologies, creating compatibility issues that disrupt operations,” said Scott Hungerford of Burns & McDonnell.

“Legacy systems often clash with modern automation technologies, creating compatibility issues that disrupt operations,” Hungerford said. “For example, manufacturers report difficulties connecting IoT-enabled equipment to aging infrastructure. To address this, we employ phased implementation strategies, such as incremental MES rollouts paired with API-enabled ERP bridges. This approach preserves data continuity while modernizing systems. Our partnerships with technology providers also enable tailored Industry 4.0 road maps that prioritize interoperability, seeing that new systems work seamlessly with existing equipment.”

Another challenge is the wide variety of business systems in use today, along with the unique needs of each customer. 

“No two environments are exactly alike, which makes a one-size-fits-all approach unrealistic,” Kramer said. “To address this, we take an agile development approach and deliver custom solutions tailored to each customer’s specific workflows and systems. This flexibility allows us to adapt quickly to changes in scope and requirements. Customers can start using portions of the solution as it’s being developed, which gives them a faster return on investment compared to a traditional waterfall approach.”

The industry is experiencing a surge in demand for more individualized, sustainable and tech-enabled products, driven by changing consumer expectations and rapid advances in digital technologies.

“Ensuring that business processes are aligned to allow for agile ways of working and empowering front-line personnel to act on this data is critical,” Thompson said. “Similarly, ensuring personnel are appropriately trained and involved throughout the digital transformation process will build alignment.”

Read more about pet food and treat processing on our Operations page.