In the past 12 months, the food industry has been forced to re-evaluate and re-assess its operational priorities. For years, many manufacturers focussed on flexible production to enable diverse product lines and mass customisation, in line with shifting consumer demands. In 2020, this was forced to change, and production efficiency and operational adaptability became the focus. Once more, automation and digital technologies came to the forefront of food manufacturing priorities.

Digitalisation is a word that has been banded around a lot in industrial markets for the past few years, serving as a catch-all phrase encompassing everything that generates, records and communicates data. Unfortunately, as with most amorphous phrases, this leads to confusion among managers about how to introduce these technologies, which causes costly errors in implementation, such as overlapping data collection systems or introduction of technologies that do not serve a strategic purpose.

For food manufacturers at the beginning of their digitalisation journey, the first step is to define an agreed and important goal, which the company can reverse engineer a solution from. Whether looking to deliver on a continuous improvement object that has been identified as part of a formal process, or just illustrating the value of an engineering team unleashed with time to think, it’s key to let the desired improvement dictate what kind of digitalisation will be needed.

For example, if material costs are too high and the agreed goal is to reduce them, a digitalisation project should establish systems that identify the factors influencing this. Understanding the root causes for yield problems could require a combination of machine data, ambient condition data, quality or lab data and information about material quality provided by suppliers. Thinking through where data is readily available, versus where it’s trapped in paper, spreadsheets or isolated automation, will ensure the plan can deliver on the purpose.

Planning at the outset of investing in digitalisation, but some food manufacturers may will have undoubtedly already rushed into digitalisation in years past. For businesses with some digital or automation technologies in place, one of the most valuable things to do is review the lay of the existing digital landscape. The easiest approach to doing this is to apply the ‘three Rs’ to your existing data: reduce systems overlap, reuse data and recycle data.

Reducing data collection system overlap not only makes it easier for managers to identify the source of a specific data set, it also streamlines costs. Why have a downtime system collecting machine event data, a yield analysis system collecting overlapping data and a work in progress tracking system that is separate to both of those? Having three systems collecting fundamentally the same data means duplicated configuration and deployment costs, as well as possible conflict over which one holds the ‘truth’.

An effective data and digitalisation strategy should also aim to use collected data in various calculations to produce several insights. For example, the downtime event data collected for OEE calculations may be part of what’s needed to solve a quality problem. The energy and water data collected for sustainability reporting may hold the key to real savings opportunities. Wherever there is a connection to a data source, managers should think of ways to make sure that a data point only needs to be collected once in order to be used many times.

Finally, offline analysis tools and some of the new analytics packages on the market could mean that old data offers recurring value as a firm chases finer and finer points of improvement. So, it’s important to set up a data management approach and data management platforms that can give you the option of making repeated use of data.

Digitalisation projects can lead to more innovative and effective ways of working for food manufacturers, but they rely on careful planning and strategic implementation. By giving full consideration to the goals to be reached or how data is used within a site, food businesses can ensure their systems are always effectively aligned with their goals.

There are two types of food plant managers. There is the innovator, who is looking for new ways to achieve goals and improve systems, and the cost-conscious individual, who is looking for leaner and cost-effective solutions. Depending on your goal and the category you fall into, your systems and software should be specified and procured with that objective in mind.

Aligning your systems with your goals and aims for the business is the first step in this process. Being honest and realistic with these aims is vital, as without a clear view of what you want to achieve in your food plant, there is going to be disappointment, costly mistakes and confusion along the way.

There is no one-size-fits-all approach to industrial automation, so systems will vary depending on the automation profile of the business. But what systems will benefit each type of food plant manager?

The Innovator

When thinking about innovation, one of the key components is data. With data comes the opportunity to view where improvements, changes and adaptations can be made. Data sources such as control systems and sensors are at the heart of the plant, and will grant access to the information that will change the game altogether.

Implementing these systems is relatively simple but, of course, you must have the necessary equipment to collect and record this data. To start with, you should at least have a SCADA system in place, connected to show an overview of system performance.

To facilitate greater innovation, you can look at installing an MES system, which gives more access and accountability to the humans in control of the systems. From a plant-wide overview through to granular production activity, the system collects data from sensors and industrial control systems and displays it in a ready to view state.

Insight is the key to innovation and that is what these systems offer. So, if you’re looking to change the world of food plants, there’s some food for thought to get you started.

The cost-conscious

When cost is top of the agenda, the systems and software you will look to are different to that of the innovator.

Instead of the wild and wonderful additions of new technologies, the key here is making the most of what is already on site. Optimising asset performance is relatively easy if you look towards an Internet of Things connected platform, such as GE Digital’s Predix platform. This kind of system can predict problems and outages before they occur and connect the factory to the wider logistics chain.

This software uses machine learning to detect normal behaviour and data sets. Automation can detect issues far quicker than a human worker, and can cross reference historical data to see if it is a recurring issue. Employing this kind of intelligence facilitates predictive maintenance to prevent future issues.

Considering your business goals is crucial when looking to improve systems and infrastructure. With so many different solutions to achieve different goals, it is impossible to think that there is one solution that could be rolled out across multiple plants.

Currently, many food and beverage companies solely rely on manual paper checks for their traceability procedures. Data is collected manually by the workers, which is then collated. The files are then collected and stored in offices, which must be sorted through in the event of a regulatory inspection or a recall.

Manually collecting vital information like this can have an impact on the accuracy of the information and the speed at which it can be collected. However, European companies in the food and beverage industry are bound to laws that mean their traceability procedures must be extremely tight to avoid any prosecution or fines.

All countries in the EU are bound by the General Food Law of 2002 to ensure that food safety is maintained for all European consumers. The law defines traceability as the ability to trace and follow food, feed and ingredients through all stages of production, processing and distribution.

When food or feed is found to be unsafe, companies are under obligation to withdraw or recall the product. They must also notify the national authorities who can then monitor where the product may have spread to and whether further action should be taken. Otherwise, a contaminated feed could have wide reaching consequences across the European food supply chain.

To comply with this regulation, companies must have traceability systems in place that allow them to identify where their products have come from and where they are going to. They must do this quickly to reduce the spread of contaminated product and the amount of product recalled, affecting the supply chain.

It is almost inevitable that at some point in the food chain, mistakes will be made, and contaminated products may enter production. However, to minimise the disruption to their business, food manufacturers can invest in automated traceability systems. Then, if a contaminated product is found, the batches that it has been in contact with are traceable.

To create an effective web of traceability records, data should be collected from the three different stages of food production. Manufacturers can use PLCs and HMIs to collect the data. Emerson Automation’s PACSystems range of control systems are easily integrated into existing systems, meaning that the benefits of improved traceability are not outweighed by a huge cost to integrate the new products.

In the first stage, all raw materials should be easily identified by the batch and date code, meaning they are tracked as soon as they come into the factory. Then, as the raw material is processed, manufacturers should note the number of units produced and the amount of any waste product. Finally, the third stage, where the product is sent to customers, is one of the easiest to keep traceability records of, as most businesses keep detailed records of orders and their recipients.

By feeding the data collected along the production line into a MES system, the plant manager can view all of this traceability information at a glance. In the event of a recall, the plant manager can then share this information with the relevant authorities quickly, without having to track down missing data, minimising the disruption to the plant.

Not only does improving traceability systems help the manufacturer in the unfortunate event of a recall, it also helps the businesses’ transparency. Novotek has previously worked with a Dutch milk producer where GE Digital’s Historian application allowed the company to improve its transparency to its customers. As the brand promoted itself in organic retailer stores, proving the origin of the milk was important to the success of the brand, meaning the producer had to invest in an improved traceability system. Food scandals don’t look likely to disappear anytime soon, but by investing in better control systems to improve traceability, food manufacturers can reduce the effect of the scandals on their business. Just as professional gardeners wouldn’t weed their gardens with inadequate tools, food manufacturers must not rely on out-dated manual collection methods. By carrying out traceability procedures using connected, automated systems, food manufacturers can protect themselves as much as possible against scandals.