Consumer expectations of confectionery manufacturers are changing rapidly, with personalization, customization and individualization emerging as some of the most important buzzwords of recent years.
Coupled with the wellness movement and the diversification of the global food chain, there is increasing pressure on manufacturers to downsize products while maintaining high quality and safety standards. To meet these new demands, the use of automation, digitalization and artificial intelligence (AI) in food production has in many cases gone from being a necessity to a requirement.
More and more manufacturers are using automation equipment, such as robots, in combination with technologies that include vision systems or artificial intelligence (AI) to further increase productivity and efficiency. The idea of artificial intelligence in manufacturing is not a new one, and many manufacturers are already using it today. By essentially mimicking human activity with computer software, added to the Internet of Things (IoT), these devices can analyze data, make decisions, and act on that data without human intervention.
Turning data into actionable information
Operating in an asset-intensive industry means confectionery manufacturers have to meet quality, regulatory and cost requirements, not to mention the growing focus on sustainability and waste reduction. Therefore, ensuring that equipment operates at the highest level of productivity and efficiency is vital.
Advanced analytics platforms, such as ABB’s recently released Ability Genix, can provide this link in the chain by contextualizing operational (OT), information technology (IT), and engineering technology (ET) data to provide actionable insights that enable better decision-making. For example, operators can see how equipment and systems are performing against various asset performance metrics such as quality, cost, and safety. Quality managers can then predict batch cycle quality deviations and decide whether to stop the process and fine-tune it.
Another important element is the system’s scalability, which can be realized through a flexible, modular approach. For example, it can be applied to optimize a single asset or value driver, but can then be easily expanded as needed. So when looking for data analytics software and services, it’s important to look for a provider that can work with your production line’s unique circumstances to offer benefits no matter where you are in your digitalization journey.