The benefits of agility in fish processing

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With a rapidly growing global population, increasing levels of urbanization and an increasingly health-conscious middle class, today’s seafood processors have an unparalleled opportunity to benefit from revolutionizing their industry. Agility is one of keys to realizing those benefits.

Our new series of guides delves into the trends that are changing the fish processing industry and serves as a roadmap to smarter food processing. The first in the series explores how fish processors can leverage agility through Industry 4.0 technology to become more efficient, improve production and increase output. 

Agility in action

Operating a smart factory enables the processor to adopt more sustainable, efficient business models, with lower labor requirements, which in turn helps to advance productivity, agility and speed to market. 

By focusing on data, connectivity and smart equipment, fish processors can increase levels of automation, and focus on making marginal gains that lead to financial advantages and a better return on investment (ROI).

Key benefits of agile factories 

Using the latest technology to be more agile helps fish processors boost productivity through optimization and automation, and enables real-time data management and greater business continuity through advanced maintenance and monitoring.

Agile companies can more easily adapt processes to suit changes in market conditions and customer needs. The greater the level of agility, the easier it is to adopt new technologies that continuously improve processing results.

The sum of this adds up to higher quality products and greater ROI. But how can you achieve these results?

The eGuide looks at how achieving a high level of agility is only possible through intelligent connectivity of equipment and data, which leads to increased efficiency and quality control, and improved demand forecasting, inventory management, customer service and supplier interaction. In other words, through smarter processing, which also contributes to reducing waste material, product defects and equipment downtime.

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Greater productivity 

Using automated processing lines, for example, contributes significantly towards minimizing defects and increasing yield, as well as improving the flow and enhancing the tracking of raw materials. Such control mechanisms provide smart factory operators with better visibility into their production processes. 

Optimization also allows processors to achieve maximum value from raw material across the board, such as through more accurate and consistent portion control, cutting, weighing and packing. Performance bottlenecks can be identified and predicted more easily too, which reduces downtime and minimizes waste.

Reliable data control 

Data control is another pillar of agility that the eGuide examines. Customers value dependable suppliers that can fill complex orders at short notice. However, this can be very difficult to achieve if you aren’t already able to create, gather, interpret and utilize data. 

By collecting and aggregating enormous volumes of data from interconnected machinery, fish processors can inform production performance and machinery maintenance, and identify output patterns in real time. Such agility enables smart factories to optimize productivity. 

This agile approach aims towards self-configuring equipment and material flows, with production schedules adjusting to changes in the desired end product and delivery schedule. The level of automation also means the production manager can see the impact of such changes in real time, which helps to streamline production and consequently attain higher yields.

Connectivity and the ability to use data is why the smart factory is so named. The integration of data from operations and business systems, along with data collected from suppliers and customers, will provide an increasingly holistic view of supply chain processes for smart factories in the coming years. The key benefit of this will be greater overall efficiency along their entire value chain.

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