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Unpacking the ‘new normal’ of automation in food manufacturing

Home Manufacturing & Processing Food & Beverage Unpacking the ‘new normal’ of automation in food manufacturing

FOOD and beverage companies can now set the course for a time after COVID-19 using automation to boost competitiveness and productivity. Manufacturers should focus their resources on four market driven perspectives: workforce, product quality, flexibility and sustainability.

That’s according to global automation company, Omron, which believes the current crisis offers a chance to rethink outdated procedures and to use automation with the aim to boost productivity, efficiency and quality.

Robert Brooks, Omron Europe’s Industry Manager for Food and Beverage, said the first aspect to be considered in this respect are the employees. “At the moment, there are millions of people employed in these sectors. This number has an enormous impact on producers in terms of costs, but also primarily in terms of the health and safety of human resources.”

He said the pandemic had led to developments such as social distancing and tighter safety regulations that companies need to adhere to. Automation can help in overcoming this challenge while also improving security and efficiency in the longer term.

“An example is a cobot or mobile robot solution that can relieve employees from challenging and repetitive tasks so they can focus on more value-added and fulfilling roles.”

Product and production quality as well as traceability are further aspects that are increasingly important for both manufacturers and customers alike. Barcode quality is one example that is a key element in many applications, said Alberto Giordani, Product and Project Manager at Omron Solution Partner Alfacod.

He added that regulations from international organisations like ISO or GS1 are widely adopted, but in addition there may be further project specific specifications driven by suppliers and customers. This leads to a need for reliable systems and tools that ensure a bar code is correct and readable. Solutions can be adapted so they can also check pack design aspects and package integrity and completeness.

Brooks said there was a close link between automation and traceability, ultimately protecting the brand reputation of the producer and reducing costs. “Another simple example is a verification solution using vision systems or RFID, linked into the production management software can help to reduce issues connected with false codes or labels. “

Mobile robots and flexible production lines provide companies with valuable support. Daniela Moles, communication expert at Omron Solution Partner LCS Group cited the example of a customer producing coffee pods.

“Our customer receives requests for very different pods, such as normal plastic or reusable, eco-friendly, different colours and different sizes. By implementing a fleet of Omron’s mobile robots that can manage the fluctuating demand across periods of time or two entirely different requests, we were able to help them to achieve a more flexible environment within the plant. Being able to adapt and evolve will become even more relevant and important in the future.”

Automation is also closely connected with sustainability, Brooks said. It can control temperature and pressures, ensuring a product is correctly packaged and reducing waste and scrap. A more detailed example could be one where a producer must consider multiple variables such as packaging thickness, ambient temperature and packaging film speeds.

This approach requires a system to capture data in real-time, analyse it and make decisions. “If we are able to process and read through this data, we have all the guidelines in order to work better, implement sustainable actions to achieve a sustainable future,” said Brooks.

An example of this, he added, is Omron’s Sysmac AI Controller, a smart Artificial Intelligence solution that collects, analyses and uses data on ‘Edge’ devices within a controller to prolong equipment longevity and detects abnormalities to prevent failures. It combines control functions of manufacturing lines and equipment with AI processing at manufacturing sites in real time.

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