Industry Insights
Food Manufacturing: The Last Frontier for Automation
POSTED 05/24/2024 | By: Jim Beretta, A3 Contributing Editor
Robotic automation solutions are a common sight in many manufacturing sectors and have been a mainstay in the automotive sector since the 1950s. The global pandemic spurred an increased interest in both fully automated and collaborative robot (cobot) solutions not only in large manufacturing operations, but also in small and medium facilities. The exception, however, has been in the food production sector, which has been slow to adopt robot solutions, remaining the last frontier to automation.
Trends
During the height of the global pandemic, there was a rush to automate in every industry. With every sector dealing with labour shortages, supply chain issues and production delays, robot automation solutions moved from a “nice to have someday” to “how fast can we implement it”. After all, robots don’t get sick, don’t take vacations, can run 24/7/365 and don’t take personal days. In the food industry, many facilities didn’t have teams of engineers who had been dealing with automation solutions for years, which made robot automation difficult to implement, train and maintain.
“After a push for automation in the food industry during COVID-19, we are seeing a slowing and reprioritization of automation projects. Instead of automating challenging processes, many companies are looking at upstream processes that provide a faster return on investment since they are more automatable. Palletizing/depalletizing, case packing, tray processing and box assemblies are more straightforward to automate, less complex and can offer a proof of concept for employees that robots are not stealing jobs which can grow a culture of automation,” said Mike Bannister, vice president of sales at Convergix Automation Solutions.
Consumer purchasing changed during the pandemic, and the online shopping trend has continued even after bricks and mortar stores reopened. Suppliers had to rethink how to maintain stock. Instead of full retail display pallets of each item, suppliers are requesting mixed pallets of partial orders for display. Scott Lang, president and CEO of Motion Controls Robotics Inc, saw an increase in demand for modular pallets that are self-contained, easy to move and can be delivered in weeks rather than months. “The modular pallets have a built-in forklift so they can be moved quickly to where the demand is. In addition, they work like building blocks that can be configured to any floor plan. They are also intuitive — more or less ‘plug and play’ — simple to use for employees who may not be familiar with robotic applications.”
Credit: Motion Controls Robotics
“The Smartphone effect is encouraging robot manufacturers to think differently about automation. With innovation in artificial intelligence (AI) and vision as well as machine learning (ML), we can ‘teach’ the robots to troubleshoot and enable preventative maintenance. The Internet of Things (IoT) and cloud-based applications can be paired with virtual reality (VR), and an employee on the plant floor can interact with someone from our company in real-time to diagnose, troubleshoot and fix most problems without the need for a service call,” said Bannister.
Challenges
The food processing sector has a number of unique challenges that make robot integration difficult. Robot hardware and strict sanitary and washdown protocols are not compatible, and food grade oil and lubricant is required to meet health and safety regulations. In addition, the design of many traditional robot arms and end-of-arm-tools leaves areas that are difficult to sanitize completely, increasing a risk of bacteria being introduced into the production line.
In addition, the North American market has been slower to adopt automation, and therefore there is a significant education required when customers are exploring automation solutions in the food industry. The industry tends to take an all-or-nothing approach to automation, and therefore is unaware of the innovations of the last few years. There continues to be a heavy system integration business model whose revenue is proportional to time spent versus number of products sold. With the SKU variation inherent in the food industry, often solutions are over-engineered, and perform inconsistently when sometimes simpler is better. “Many potential customers have no idea of the solution possibilities with advances in vision, artificial intelligence (AI) and machine learning (ML). We often hear ‘you can do that?’ when we propose a solution,” said Harley Green, vice-president, strategic solutions, Soft Robotics.
In addition, customers are demanding more system flexibility. “One supplier wants product in 5-gallon buckets, while another wants the same product in single serve containers. The product is produced on the same line in the same plant, and singulation isn’t effective or possible. Customers want to be able to move from bulk pack to single pack seamlessly, or pack a box of the same flavour and a box of six different flavours at the same time. Flexibility, agility, ease-of-use and nimble applications are going to be a continuing trend,” said James Skelding, vice-president of sales and marketing, Motion Controls Robotics.
Employees in the food production facility are adept at troubleshooting and problem solving on the fly, removing subpar products or catching errors downstream without stopping the production line. “Humans can handle chaos; robots cannot. Production facilities, especially those built in the 1960s–1980s, were designed for human employees. It’s not a matter of swapping a robot into the space an employee occupied. If each task needs to be singulated, that requires a huge footprint, multiple robots and that increases the initial expense, complexity and maintenance,” said Green.
There has been a cultural shift in the social environment in recent decades, which the pandemic expedited. Social drivers such as health concerns, cold repetitive environments and a change in the social environment have resulted in fewer people entering food manufacturing, as the jobs are no longer as respected as in past generations. Coupled with increased hygienic concerns and the demand for more traceability, the food sector has struggled to find sufficient labor to meet demand. “We are located in Switzerland, on the border with France. The dairy industry is one of our main sectors, and we were able to leverage our expertise in sensitive environments such as semiconductors and medical equipment. Europe is farther ahead in food industry automation than North America,” said Mathias Konne, North American business head-food of Stäubli Group.
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While many of the larger food manufacturers have a culture of innovation, these companies were built through years of acquisition of smaller companies. The corporate head office may have the structure and mindset to automate on a large scale, but the legacy plant locations can pose a barrier or challenge to automation. “Legacy food production sites may have 8-foot ceilings, and we cannot roll a robot in on a tow motor. The most successful automation installations in the food sector occur in locations that allow for it,” said Bannister.
Another challenge to automation in the food sector lies with decision-making. While other sectors, such as the automotive industry are well-versed in robot-integrated automation solutions and have experienced automation engineers and robot programmers on-staff, automation in the food industry is a new concept for many facilities. While a food automation solution makes sense in the corporate offices, without the support and expertise on the plant floor, it is doomed to fail. The quality assurance division may have different needs and expectations from the process engineering division, such as the need for hard data to request changes from suppliers or upstream processes to create better quality, consistency and throughput. While robotic solutions can provide that data, it still needs to be distilled, analyzed and reported and that requires expertise that may not be available at the plant floor level.
Solutions
One of the advantages (and disadvantages) of a robotic solution is the amount of data that can be generated. For a manufacturing sector relatively unfamiliar with automation, collecting and analyzing the data can be unmanageable. The IoT and AI can facilitate processing large volumes of data, pinpoint gaps or quality issues and provide the evidence to support changes. “ML, AI and vision applications can lead the way to continuous improvement. Upstream problems will impact downstream processes; if you catch the problems at source and remove defective products earlier in the food manufacturing process, you can reduce scrap rate without halting or delaying the production. Yield is king, so better consistency equals higher revenue and less waste,” said Green.
Stäubli Group has been able to leverage their expertise in other sectors to, quite literally, build a better robot for the food manufacturing space. Instead of retrofitting an existing design, the hygienic environment robots are fully enclosed, with pressurized arms to prevent water and bacteria from entering the robot and increased gaps between segments for better washability. They use only food safe lubricants and other materials. “Rather than adapting and hoping for the best, we design specifically for the food sector. Of course, when artisanal cheese became a high-end product, the capital expenditure was easier to justify since margins were higher, which helped ROI,” said Konne.
Credit: Stäubli Group
One of the challenges with any type of food processing is the lack of uniformity. Another of the changes in consumer habits that was driven by the pandemic is an increased demand in ready-to-eat (RTE) options, which usually involves multiple food processes, any of which can change the shape, consistency or size of the ingredients. Humans can adapt to the variations, but robots have a harder time. End-of-arm-tools (EAOT) with soft grippers that mimic human hands provide a good alternative, especially when equipped with vision and AI solutions. “Consumers expect consistency in the presentation of food. For example, if one chicken breast is placed breastbone up in a tray, that reduces visual appeal. EOAT with vision ensures uniformity. In addition, innovation in recent years allows robots to bulk process tray picking as quickly as a human employee, with less risk of accidental exposure to harmful bacteria. Many robots equipped with ML self-clean in between runs,” said Green.
Future of food automation
Food manufacturing may have been the last frontier of automation, but no more. Robotic automation is moving upstream in the food production cycle, as robot harvesting and laser weeding are gaining traction. Green advised there is a continued demand for a high level of flexibility and end-to-end solutions.
“The Smartphone effect will continue to push ease of operation, with people willing to extend the ROI if AI, ML and vision allows plant employees to troubleshoot and problem-solve,” said Skelding. Konne added the IoT will allow real-time monitoring that will increase proactive maintenance. Food manufacturing facilities will continue to boldly go where none have gone before and robotic automation will continue to lead the way.
For more information on automation and food, check out the A3 on-demand webinar on the same topic and look for an interview with Motion Controls Robotics CEO, Scott Lang in a future episode of A3 | The Robot Industry Podcast.