“Changing consumer tastes are driving the food and beverage industry transformation,” says Maryanne Steidinger, Director, Industry Solutions Marketing, Schneider Electric. Manufacturers have to re-assess the current way of doing business and ensure they are agile enough to respond to changes, she suggests.

Schneider Electric is a Founding Partner of the marcus evans Food & Beverage Manufacturing Summit 2016, taking place in Chicago, Illinois, November 10-11.

What transformation is the food and beverage manufacturing, packaging and labeling industry undergoing today?

There is an expectation of perfect production. Manufacturers cannot use poor quality materials or have people getting sick because of their products. When you have the complexity of manufacturing products, making food, packaging and distributing it with the complexity of the various licensing, regulatory and labeling guidelines, and be able to do it perfectly, every day, is a huge amount of pressure. The system cannot let you down. You have to invest in safeguards and ensure the quality is maintained, otherwise you can go out of business.

There are also new methods, reformulations to remove artificial color, flavors and ingredients, and different methods of delivering products to meet consumers’ needs for “food on the go.” Gluten-free products were almost unheard of a decade ago, but now manufacturers have to produce gluten-free versions of their products and have a manufacturing process that works with that.  

What changes to the way manufacturers source, make and deliver products do these changes require?

It makes manufacturers re-assess their current way of doing business. Can they be more agile by putting in systems that give them supply chain visibility? Can they add manufacturing intelligence to understand better cause and effect to reduce quality errors? Does tracking the performance of raw materials give them better process control or yields? It is all about being more responsive to these changing tastes, implementing systems to make them more agile, more compliant, and more productive.

How can Schneider Electric help manufacturers transform their business?

Our role is to deliver visibility to production processes, to make sure they are done as planned and consistent across the plant, and able to change as often as needed. We help improve sustainability, efficiency and traceability of operations; 49 percent of food and beverage CFOs see a significant link between sustainability and financial performance. We understand the need for agility, responsiveness and standardization in manufacturing, and offer solutions to enable batch management, formulation, packaging and operations optimization.

What intelligence on line performance do they need to unlock hidden capacity in production lines? How can data help them make wiser decisions?

Implementing a packaging line performance application will help a manufacturer gauge how effective and accurate their packaging process is, and how it can contribute to the profitability of the organization by improving first pass yields, reducing quality breaches, and increasing line throughput. One event that most processors ignore is a ‘micro-stop.’ This is an event where the line essentially ‘hiccups,’ not stopping production but reducing throughput. There are applications using Overall Equipment Effectiveness (OEE) that measure throughput, quality and equipment uptime to provide a metric (percentage OEE) that can be used to determine how effective the packaging process is. OEE of 100 percent would be perfect performance, and this measure can be used, in real-time, to tweak production for maximum performance and capacity.

What advice can you offer on making it right the first time?

That is what it comes down to. Any time a manufacturer has to throw away a full batch, it will hurt its efficiency. The equipment they use is an important part of ensuring that everything is made right the first time. Smart manufacturing, predictive analytics and predictive maintenance will all help. There are software programs to collect data on how a machine is performing, compare it with historical data and provide insights on when unplanned downtime might occur.