Controlling variability to make the unpredictable, predictable.

Unpredictable variables throughout the manufacturing life cycle can cause a huge drain on productivity and waste. Understanding the impact of these changes helps food and drink manufacturers decide on the best intervention - before it’s too late. Today's automation and digitalisation helps to control and predict design and production variables, and advanced Internet of Things takes this to a new level by tracking and visualising variability in real time - no matter where it occurs throughout he value chain. Machines can then self-adapt so that production lines and manufacturing operation systems can be reactive to the conditions they are faced with. 

Find out how technology helps manage variability in food production

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Podcast: Could technology be the key to managing variability?

In this podcast by Food Matters, we look at the challenges facing the food and drink industry when trying to manage variability, what pinch points affect businesses and how these can be resolved through tech. In conversation with Speedibake, Raynor Foods, Polestar Interactive and Digital Catapult. 

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Predicting variables in raw materials

Precise information around source of goods and raw material make-up is needed to be able to give consumers insight into the provenance of the food they buy and to understand and predict behaviour of raw materials as they move through the factory. The Achilles heel for many companies is coping with the interaction between the chemistry, biology and physics, causing unpredictable variability across the supply chain from farm to fork. For manufacturers to respond to this, it is vital they have detailed data on the life of the product from its raw material form through to final manufactured product. 

 Food and drink products are made to specification. For example, as a sandwich manufacturer that supplies into airlines, we make products that meets weight requirements. If raw materials are variable in weight this can stop our production lines or mean the final product doesn’t pass quality acceptance.” 
Tom Hollands, Raynor Foods 
Hear more from Tom Hollands at Raynor Foods in this podcast

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How can transparency throughout the value chain be achieved? 

With the prevalence of internet access, cloud computing, and the decreasing cost of the Internet of Things (IoT), it is now possible to generate, manage, and communicate data effectively. In combination, blockchain and the Internet of Things have the ability to understand and visualise the root cause, and then adapt production accordingly.

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Predicting product behaviour and production readiness   

The digital twin

The digital twin is the precise virtual model of a product or a production plant. It allows operators to predict behaviour, optimisie performance, and implement insights from previous design and production experience.


Predictable scale up of new recipes is vital. Before it goes into production it can simulate various mixes of its proposed product or percentage of ingredients to know the result. This can optimise the quality, and manufacturers can look at the details of the packaging and how it will reach its customers from boxing, transportation to the time it reaches the point of sale.



Predicting variables in the environment 

Even when the product itself is predictable, it can be hard to predict the environmental conditions that the product is exposed to. Its inevitable factories fluctuate in temperature and humidity, but when it causes an entire batch to be ruined, this seemingly minor variable can be a huge problem. The variability can be controlled wth totally integrated automation so that product behaviour throughout the factory is as expected. 


How can these variables be monitored and controlled?

With TIA Portal, these variables can be monitored and controlled. Different stages of production may require specific temperatures. For instance, for bread yeast to ferment and the dough to be ready for baking, warm conditions are needed. The baking and finished product has other climatic requirements that give it the desired longevity and freshness when it reaches the customer.  

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bread baking

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Keith Thornhill, Head of Food and Beverage, talks about how control of the environment and other variables can contribute to increased food productivity and agility.

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Calibrating machinery and processes to respond to variables

Calibrating machines in a way that enables SKU flexibility and efficient product changeover is a big part of making sure variability in orders doesn't cost downtime. Further upstream it's also helpful if machines can self adapt to align to the variability in output of a farm. 


How can you use Virtual Commissioning to ensure a machine or line can respond to variability?

If the machine is in operation and requires optimising or modernising to deal with variability, it is possible to keep downtime to a minimum and virtually commission a machine in the TIA Portal.  Virtual Commissioning sofware validates the sequence of operation at the design stage using the machine’s digital twin with the real PLC code to ensure it is correct. Most plants and machines now use CAM (computer aided manufacturing) which, with the help of the digital twin, can create CAM profiles and import them directly into the PLC code. It also simulates errors in the machine so that operators can learn to handle real faults.  

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