PC-JUL22-PG56-57.1_Layout 1 26/07/2022 11:41 Page 57
FOOD & BEVERAGE
The upgrade, performed without installing new
machinery, has enabled the Mantuan brand to produce over 800,000 cartons from the line per month
each individual station in order to determine which one was negatively impacting the overall efficiency of production. The decision was therefore made to install continuous monitoring tools — in this case, a series of smart sensors based on protocols native to the IoT world — to analyse the system 24 hours a day, collect data from each individual station and study it in real time using the MQTT protocol. Analysis of the data revealed one key issue in
particular: a major bottleneck at the second station — the filling machine. Targeted improvements were therefore made at task level, without affecting subsequent stations. "The challenge with implementing these types of measures is to avoid causing jams or creating choke points at stations downstream," explained Andrea Stefani, OMRON Automation Product Engineer. "When there are so many processing stages and machines from different suppliers, as in the case of Cleca's ready-to-use broth line, there's a tendency to overlook the bigger picture and examine each individual process rather than the line as a whole. However, the i-BELT philosophy is about having a comprehensive overview and holistic approach to managing the line, in the same way as a
conductor might lead an orchestra." The analysis conducted
by OMRON in accordance with the i-BELT framework enabled staff at Cleca to gradually improve the filling machine's performance, eventually achieving an 8% increase in productivity. As a result, the company is now able to take around 2 cartons of ready-made broth off the line every second, totaling more than 800,000 each month. "The involvement of OMRON and the team
working on i-BELT was crucial to establishing communication between the system's existing components and all of the devices used to collect data," said Franceschini. "By using this approach, we've managed to make our line incredibly granular, dividing it into separate blocks to analyse them individually and correlate them with subsequent blocks. We could almost say the dynamics of a line like ours aren't too dissimilar to those that govern a queue of traffic: When traffic stops and starts unexpectedly rather than flowing steadily,
FLOW OPTIMIZATION SECOND TO NONE
congestion occurs, which cascades down and slows the process downstream.” "OMRON was particularly motivated by
the prospect of an entirely new challenge, for the European market at least," concluded Cavallanti. "This is the first time we've seen a shift toward what we like to call tomorrow's automation. For us, automation in the future will encourage more and more companies to add value to the intangible part of a project, i.e. the data, in order to achieve the more tangible part: the outcome."
OMRON
https://industrial.omron.co.uk
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