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Any food factory can be smart!

08 August 2021

Dan Rossek argues that the benefits of digitalisation can be enjoyed by any food manufacturer, irrespective of company size or existing legacy equipment. 



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While the view conjured up by thoughts of a smart factory is often one of a pristine green field site with the latest technologies in place, the reality for many food producers is very different, where often ageing, legacy equipment and unconnected lines are more often the norm, along with a wide variety of technologies and differing levels of capability.

Many food manufacturing sites consist of a disparate range of legacy machines that perform their function well and in many cases, efficiently, but do not offer any digitalisation capability. 
 
In a 2013 report, The All-Party Parliamentary Manufacturing Group suggested that this was a result of the British culture of taking pride in making things last as long as possible, contrary to the culture of some other countries that take pride in having the latest equipment.
 
The challenge this creates is that when these legacy lines were commissioned, the benefits of collecting data at line level or integrating it with the IT level wasn't understood, and many systems were designed with basic logic functions, using simple analogue I/O.
  
In addition, the food and beverage sector, can find it hard to justify the investment in technology, where short-term contracts make long-term investment a risk. Most manufacturers are also reluctant to disrupt a machine or line if it is working well.
 
The most straightforward solution to achieve a smart factory is to retrofit a new control system architecture and place the automation technologies onto it while maintaining a machine’s mechanical structure. Unfortunately, many factories are not able to pause a line for the time needed to undertake a such retrofit.
 
For this reason, an incremental approach may be more suitable; looking at explicit parts of a machine and establishing what can be achieved with individual improvements.
 
Defining objectives 
The starting point of any digitalisation journey is to define a clear set of objectives. Generally, the desire to develop digitalisation capabilities will be triggered by challenges or opportunities which have already been identified. For example, is the business operating over its capacity? Are production issues causing missed deadlines? Are parts not being delivered on time? Are there quality issues?
 
Having a clear, prioritised list of objectives is key to understanding what needs to be solved before trying to solve it. This will often involve identifying where the greatest return on investment (ROI) can be made, as this is where the quickest digitalisation wins can be found. 

Next, it is important to analyse the legacy platform by undertaking a technology assessment of plant and capital equipment to establish a baseline of what can already be achieved. In simple terms, this means looking at whether there is any intelligence within the equipment and its wider systems, whether it is connected, and whether it has IT/OT capabilities which can escalate data into the IT domain. For example, many manufacturers will already have their equipment connected to an ERP system which provides some degree of connected infrastructure.
 
This stage should identify the types of machines, automation architecture and capabilities that are present to provide a holistic view of the status of the plant. Many SMEs have relatively simple sites, so this need not be an overly complex process.
 
A technology assessment may identify that the field level data needed to understand any identified challenges may not be available within the existing systems. Typically, manufacturers with legacy equipment do not have the necessary intelligence within their lines. They may know basic information about how many items are produced, but generally, there is no deterministic information such as how productive the line is, how long it is idle or stops for, or how long one part of the machine is waiting for another to finish its process. Deterministic information makes it possible to build a level of intelligence that can tell them what to change, or what needs to be added to a machine. And the answer may be simple. 
 
If the baseline analysis identifies insufficient system capability to run the required sensors and capture the data they produce, then a secondary data collection layer – using technologies such as Omron’s Sysmac Automation Platform and field level deterministic sensors – can be added. This can work independently to the machine and not interfere with it in any way. 
 
Depending on the machine’s scale, this data collection layer could be a system controller with fieldbus communication that allows I/O to be deployed remotely. Alternatively, a central PLC could be used to collect information. The installation will be relatively straightforward, requiring a modest investment, because it is not actually controlling anything on the machine; it is simply collecting data.
  
The results from the baseline assessment – in terms of scale and investment required to get a facility modernised – could be overwhelming. But remember that an entire site does not need to be tackled in one project. It is far more practical to compartmentalise and prioritise the elements which will give the greatest return, in terms of productivity and efficiency.
 
In addition, there are several schemes and organisations to help businesses on their journey towards a smart factory. These include the High Value Manufacturing Catapult Centres, which are industry-biased and provide innovation support to businesses. Technology vendors and their integration partners can also provide valuable support.

De-risking
Capital investment in digitalisation can be de-risked by building in flexibility and agility to enable the solution to adapt to future changes within the business. Modern automation systems have this capability built in, and if they are intelligently employed, users can be sure that they will be able to fulfil future requirements. 
 
Organisations such as Omron are developing different methods of de-risking projects and improving the accessibility of technology, with servitisation approach or alternative financial models. From this perspective, the customer is charged for equipment based on an outcome or performance-based metric, or via a financial leasing solution, as an alternative to a one-off capital investment. This changes the investment decision dynamic from capital costs to operating costs and either solution can offer manufacturers a financial or operation benefit.

Conclusion
With the right approach, all food manufacturing operations – regardless of the age of the equipment in use – can benefit from developing a digital capability, providing the right steps are taken. Namely, to identify the business challenges; define the technology baseline; prioritise the areas for improvement; then engage with a technology vendor, systems integrator or support initiative and create a compelling business case.

Dan Rossek is regional marketing manager at Omron.


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