Last updateMon, 27 May 2024 10am

Smart cocoa processing that hits the productivity sweet spot

Companies in the food and beverage industry are grappling with a number of challenges that can prevent them from thriving in today’s marketplace. However, there are real opportunities for these manufacturers to optimise and improve their operations using data science. Malte Schlüter, Global Director for Food & Beverage and Consumer Packaged Goods (CPG) - Factory Automation at Mitsubishi Electric Europe, explores how during his exclusive videocast interview ‘Food and Beverage industry: Can cocoa be smart?’

Across the food and beverage value chain, businesses are encountering a number of obstacles that are holding back the potential for increased profitability, efficiency, throughput and, ultimately competitiveness. This is driving producers and packaging experts to look for technologies to help optimise product quality, uptime, productivity, costs, resource utilisation and environmental footprint.
These aspects can all be enhanced with the adoption of value-adding solutions based on data-driven digital technologies, according to leading expert Malte Schlüter. For example, it is possible to streamline and improve the results of product and packaging inspections using innovative vision systems that identify anomalies and remove defective or off-spec materials. These combine high-resolution, high-speed cameras, artificial intelligence (AI) image analysis platforms and automated machines, such as industrial robots. An additional benefit of these setups is the ability to continuously improve their detection performance over time, thanks to the data-led refinement of the models used.
The potential gains that companies can achieve will be highlighted by one of Mitsubishi Electric’s latest demonstration units on show at interpack 2023 from 4th-10th May in Düsseldorf, Germany. Attendees will be invited to join the company at Stand A40 in Hall 6 to explore an open, modular and fully integrated quality inspection line for chocolate bars and their packaging.
The solution features a conveyor belt that passes three different stations. Firstly, the products go through an X-ray system that can spot foreign objects and impurities, subsequently, they are taken to a deep learning-based solution that evaluates packaging seal quality. Finally, an articulated six-axis robot picks, lifts, and turns the product around so that it can be weighed and then inspected by a vision system, which is used to perform a final check of the chocolate bars. All in all, this is a fully automated product and packaging quality inspection solution, that can be placed modular and highly flexible at many process steps on every production line.




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