Wayne Labs has more than 30 years of editorial experience in industrial automation. He served as senior technical editor for I&CS/Control Solutions magazine for 18 years where he covered software, control system hardware and sensors/transmitters. Labs ran his own consulting business and contributed feature articles to Electronic Design, Control, Control Design, Industrial Networking and Food Engineering magazines. Before joining Food Engineering, he served as a senior technical editor for Omega Engineering Inc. Labs also worked in wireless systems and served as a field engineer for GE’s Mobile Communications Division and as a systems engineer for Bucks County Emergency Services. In addition to writing technical feature articles, Wayne covers FE’s Engineering R&D section.
You have several data islands of automation, but by giving each data context — and with help from AI — you can keep the aging equipment and gain knowledge of your process.
Plants often have aging equipment that works fine, and it may have sensors, but in many cases that data never connects with data from other siloed processes. Why not connect all the data together with intelligent networks and use AI to get a better understanding of the whole process?
Rather than a hodge-podge of sanitation and cleaning records scattered everywhere, why not tie them together digitally so they’re available in minutes or hours rather than days or weeks?
While the mixing and blending of liquid ingredients into a liquid product is an exact, controlled process, combining dry ingredients has unique challenges that have been difficult to control with automation. Finally, sensors and automation are here to help.
Some new ERP providers are building their systems from scratch totally on AI, but can their systems fulfill all the demands that manufacturers have expected from conventional ERP over the years?
Older facilities, in many cases, can be maintained to protect ingredients and finished goods. However, attention should be paid to drainage systems, along with monitoring environmental temperatures, humidity and airflows in critical spaces.
This visual overview, featuring images and videos of robotics applications in the food industry, illustrates what is possible with modern vision systems, artificial intelligence and robotics in a range of applications — from agricultural harvesting to serving up RTE meals, smart palletization and carcass cutting.
The world of smart packaging comprises many parts — intelligent equipment, recyclable materials, captivating art and lots of data — but pulling it together is a challenge. However, if done correctly, it benefits everyone in the supply chain from producer to consumer with timely information.
You know the origins of all your ingredients and everything that happened during the processing, cooling and freezing of your product, but what can you know about your product once it leaves your premises? This is the job of the track part of track-and-trace.
As if the cost to produce cultured meat products isn’t a severe enough hurdle, some state governments have made it almost impossible to enter the market.
For cultured meats to succeed in the market, they will have to prove themselves cost-effective to produce, be as food-safe as their conventional counterparts and gain acceptance from consumers — though some states have already banned FDA-approved cultured meats.
Artificial intelligence is being applied in industrial controls, but manufacturers need to know where their data is processed and who has access to it.
Ever notice how ChatGPT or CoPilot saves all your AI chats? While this can help solve future problems more quickly, private data accumulated from an OT system saved on the public internet is a disaster waiting to happen. Fortunately, in most cases AI is embedded in the process and data stays private and protected.