By Cory Garlick, CPG, regional industry manager, Rockwell Automation
When it comes to food and beverage options, the choices are numerous. Do you want organic, locally sourced, craft made, single serving, gluten free? These endless choices make consumers happy, but producers frustrated.
In addition to meeting the various consumer demands, food manufacturers also face production, supply chain and resource challenges. The rising cost of raw material, and the increasing cost of maintaining aging infrastructure, diminishes profitability. And, as more changeovers are needed to keep up with the constant change in consumer tastes, food and beverage companies also struggle with inefficiencies.
So, what’s the best way to address these competing challenges? By using your own data. Here’s how data used by machine learning and predictive analytics can help you make informed decisions to increase efficiency.
Use Your Machine Data – Wisely
The great news is the machine data you need already exists. While new equipment can be designed “smart” to deliver data, you can also get data from older equipment. It’s available through technology implemented over the past decades, including sensors, components, programmable logic controllers (PLCs), drives, historians, databases, human-machine interfaces (HMIs), and more.