Process management: MES/ERP blend yields performance improvement at Berner Foods

Getting a grip on real-time plant information without being locked into a custom-coded manufacturing execution system (MES) is giving rise to a whole new generation of plant intelligence solutions. For Dakota, Ill.-based Berner Foods, a configurable plant performance management system led to a 20-percent improvement in plant efficiency.
By Roberto Michel, senior contributing editor May 31, 2008

Getting a grip on real-time plant information without being locked into a custom-coded manufacturing execution system (MES) is giving rise to a whole new generation of plant intelligence solutions. For Dakota, Ill.-based Berner Foods , a configurable plant performance management system led to a 20-percent improvement in plant efficiency.
Berner Foods is a contract manufacturer of processed cheese, salsa, and dips. CIO Troy Grove says deployment of CDC Factory, a real-time performance management system from CDC Software , allows plant operators and managers to track downtime or line bottlenecks, and analyze likely causes and fixes.
“It’s real time,” says Grove. “You can see what happened a few minutes ago, this morning, or yesterday.”
The browser-based system ties into data generated by PLCs, as well as specific data input received when events like machine downtime prompt operators to check off simple choices on touch screens. Grove says this improves response time to potential problems—such as a nonconformance at a quality check—because the alerting and management screens immediately call attention to those problems.
“We don’t want to wait to decide if our quality side should put something on hold,” says Grove. “We want to know now so we can limit product coming off the line that doesn’t conform to spec.”

A real-time performance management system from CDC Software allows Berner Foods to track events such as downtime or line bottlenecks, and analyze likely causes and fixes. Paper-based efforts at continuous improvement and plant performance were plagued by data latency.

The system also supports continuous-improvement efforts over slightly longer time horizons, such as trying to minimize downtime events on certain lines or work centers. Grove says analysis of data from CDC Factory may reveal that downtime is being caused by cans falling over on a conveyer line, after which maintenance might tweak the conveyer speed to solve the problem.
The system, first deployed by Berner Foods in October 2005, went into second-phase deployment in August 2006. Setting up quality-check details or reason buttons for downtime events is done by selecting from pre-built parameters in an administrative module. Such configuration is done by Zach Kneubuehl, operations manager—and a nonprogrammer, says Grove.
According to Kneubuehl, setting up a quality check with the parameter-based utility can be done in just a few minutes. It’s a matter of selecting basic information about the line and assets involved, as well as picking a simple rule, such as how often to perform a moisture check at a cheese-processing operation.
On the plant floor, the browser fields are configured as touch-screen buttons so operators can quickly select reasons for events, or enter some simple notes.
Kneubuehl says that while CDC Factory doesn’t have any graphical business process modeling tools to control workflow, the continuous-improvement modules have some process steps to choose from in setting up projects. As for the aforementioned 20-percent efficiency improvement, Kneubuehl says it was plantwide, but the majority of the improvement came from one line where the system was used to analyze and clear a bottleneck. He says the key is for operators and managers to leverage the data and trends to guide improvement measures.
“The system tells you what’s going on, but it’s up to you to decide what you want to target, and where you want to start making your changes,” Kneubuehl concludes.