Wayne Labs has more than 20 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.
In an effort to allow FDA to sample water, soil and environmental conditions on USDA-regulated concentrated animal feeding operations (CAFOs), New York Sen. Kirsten E. Gillibrand introduced a bill that would provide the FDA authority to conduct microbial sampling on CAFOs as necessary for a foodborne illness outbreak investigation, determine the outbreak’s root cause or address other public health needs.
We’re told to collect as much data from our processes as we can, and there’s practically infinite storage space in the cloud—but how do you make sense of all this data?
With automation and the Industrial Internet of Things (IIoT), it’s now easier than ever to collect data and monitor production—all this in the name of managing food quality and food safety. But, with multiple sites and lines supplying data around the clock, any staff would be all but overwhelmed—without a direction in where to focus their process management efforts.
Precise control over food and beverage production is in the spotlight as health-conscious consumers are increasingly paying close attention to the ingredients and labeling of their products.
When we think of IIoT, we often consider the roles it plays in fine tuning processes to peak efficiency, minimizing downtime through predictive or prescribed maintenance, or acquiring data and processing it to improve food quality and safety. But, we don’t always think of another role IIoT can play, and that is using its capabilities to produce unique products in a very small quantity and package and ship them to individual customers.
With meat production on the rise—in fact tripling over the last four decades, according to the Worldwatch Institute—HPP (high-pressure processing) has proven itself not only to kill dangerous microbes, but also to extend shelf life by a factor of two to four times. Trouble is, with these merits, HPP meats tend to lose their color, which is a turnoff to some consumers.
Michael Taylor, former deputy commissioner for food for FDA and present co-chair of the Stop Foodborne Illness Board, suggested that in spite of all the technology, collaboration and education to improve food safety, crisis management still drives changes.
Food Engineering's recent Food Automation & Manufacturing Conference addressed several high-tech Industry 4.0 topics, including predictive maintenance (PdM). I’d like to show how you can use IIoT tools to improve your maintenance program—and maybe even better your OEE scores in the process.
In the U.S., there are 33 states, plus the District of Columbia, with some form of legal cannabis for medicinal purposes, and 10 states that allow it for recreational use. However, when it comes to specifying the level of THC, CBD, terpenes and the other 80 or so constituent components in cannabis, there's a smorgasbord of rules and regulations.
The FDA held a public hearing on May 31 to solicit oral presentations and comments in order to obtain scientific data and information about the safety, manufacturing, product quality, marketing, labeling and sale of products containing cannabis or cannabis-derived products.