The food and beverage manufacturing industry is one of narrow margins, high demand and strict regulatory requirements. As such, it’s easy to understand why many manufacturers are turning to higher levels of automation and digital technologies to meet an ever-growing and ever-changing demand from consumers. And as interest around Industry 4.0 and the Industrial Internet of Things (IIoT) has grown, more senior managers at food businesses are considering digitally transforming operations. 

However, the trouble with concepts such as Industry 4.0 is that they are ambiguous. IIoT, for example, includes everything from automatic process control and improved data collection to advanced data analysis and virtual reality (VR) supported maintenance. There are lots of potential benefits offered by this cornucopia of technologies, but they are often too conceptual for most food manufacturers to truly grasp.  

Instead, we must look at the technologies that can offer tangible value to manufacturers. For many, control systems and process automation are the prime areas for development. In fact, a report published by the Food and Drink Federation found that manufacturing process automation was the second biggest focus area for innovation by food manufacturers, with 73 per cent of manufacturers investing in this area. 

Automation is of particular interest for food manufacturers as it offers a meaningful way to achieve the benefits promised by the IIoT. For example, a fourth-generation HMI/SCADA software can oversee and control certain connected processes. As part of a larger networked automation platform — for example, GE Digital’s Predix — this software could contribute to the effective deployment of a smart predictive maintenance program. 

With such a program, food manufacturers can minimise downtime by having a system in place to monitor equipment health and automate certain maintenance tasks in a proactive, predictive manner. However, this can only happen if a manufacturer has suitable quantities of relevant operational data. This comes back to food plant managers ensuring they take the right first steps in their automation journey. 

The first steps 

For food manufacturers making their first moves into modern automation systems, the first step should always be to identify why managers want to automate. This involves developing what we refer to as a technology adoption profile. 

There are two main profiles: the innovator, who wants to experiment and find new ways of operating and developing better products, and the “price-sensitive purchaser”, who has the main aim of reducing downtime, minimising operating expense and maximising margins by making operations as efficient as possible. This profile influences the types of technology that you should invest in as a first step into process improvement. 

Once a manager determines what they want to achieve, the first port of call should be to ensure a system is in place that can collect and store an effective amount of data from machines, sensors and systems. This is where Historian software proves invaluable.  

For food businesses, Historian software ticks the right boxes for traceability and for process management and improvement, because it stores accurate operation and production data. This data should form the basis of any effective automation strategy, as plant managers can easily identify the key areas that require optimisation or improvement. 

Crucially, Historian systems don’t require substantial changes to an existing system configuration; they simply slot into existing technology infrastructure, connecting easily to a wide range of data collection and reporting tools. Some best-in-class Historian systems, such as GE Digital’s Historian, make integration even easier via fast software installation and integration. 

Historically, the challenge here has been one of price. Currently, Historian software is typically built around a model where manufacturers pay upfront for an amount of tags, irrespective of whether they are actively analysed or even used at all. The result is that medium to large size enterprises are paying high costs for 10,000 tags, when they might only need and use 400. Meanwhile, smaller companies are being priced out. 

To tackle this, Novotek has teamed up with GE Digital to provide Enterprise Historian software using a subscription-based model, making the system affordable to food manufacturers of all sizes. With this model, users can store data is several tags but only pay for the tags that they analyse, which reduces the barrier to entry for digitalisation and allows managers to retroactively analyse collected data. 

This model helps food manufacturers in remaining competitive. Not only does the insight provided by the Historian software allow for greater analysis and improvement of processes, but plant managers can attain this without paying over the odds. From here, food manufacturers can determine how their automation journey progresses — whether it’s down the route of innovation or improved overall equipment effectiveness. 

Industrial processes generate thousands of terabytes of data every day, most of which can be calculated and analysed to offer insights on how to improve or optimise operations. More users that are experienced with data collection and analysis often eventually encounter the problem of system scalability: as more data is generated, the idea of using the cloud to store and process data might seem appealing.

It is this challenge that leads operators to mentally pit local data parsing and aggregation in Historian systems against storage and analysis in the cloud. The belief is that the large storage sizes boasted by cloud providers, alongside the appealing concept of off-site data processing without the computational requirements, is better suited for higher volumes of data produced by the evolving edge. The process could therefore be logically streamlined to connect edge devices and systems in such a way that they communicate data directly to the cloud, where it can be stored, processed into usable KPIs and accessed by staff.

Because directly connecting edge systems to the cloud means that raw data is pushed directly to the cloud without significant pre-processing, it means that hundreds of messages are sent every hour. It doesn’t appear to be a problem at first — until the finance department receives the monthly invoice.

Processing raw data in cloud systems is also relatively expensive. Most database technology for time series data in cloud is not optimised for read and write functionality. This means that overall performance suffers as a consequence, with seemingly the only way to alleviate these issues being to increase the capacity of the cloud service.

Both of these issues make the use of Historian systems apparent. This is not to say cloud is bad. It is good for scalability and freeing up local resources from data storage. But as with all things, it must be deployed and set up intelligently.

If Historian systems can aggregate edge data and perform simple calculations to refine that information, it reduces the volume of data sent to the cloud. It still provides engineers on the factory floor the option of viewing granular data, while letting managers and executives access the refined data via the cloud — reducing the cloud collection and processing burden.

50 years ago, the thought that a plant manager could stay home and be able to have meaningful oversight of operations, while collaborating with other remote colleagues on the details, was unbelievable. If COVID-19 had struck at that time, most factories would have simply closed entirely.

Today, instead, with the right industrial IT solutions, plant management — along with team supervisors, quality leaders, engineers and continuous improvement managers — can work as a team as if they were together, regardless of where they are. A combination of developments in IT and OT have come together to make this possible.

There are now ways to securely deliver existing automation software applications such as SCADA via the web. Likewise, plant data repositories, or Historian software, have had the speed and power of their collection and storage capabilities supplemented with modern, web-based tools for exploring data. This includes ways to quickly add context and description to otherwise technical data points, so there can now be one source of raw truth that is accessible from anywhere, comprehensible by anyone.

Full-fledged production tracking systems or MESs have similarly had rich web-based front ends built, so that the detailed flow of events and activities can be tapped into from anywhere, regardless of how those systems may have had to be tied to on-site automation and sensors

The driving force behind the evolution of plant tech, though, was to enable greater productivity. With information from core operations readily at hand, alongside information from the broader enterprise, leading firms began to accelerate their continuous improvement efforts, undertake deeper collaboration with suppliers and other industrial partners and develop better insights into how to refine products and processes. The fact that their modern systems lent themselves to remote work and collaboration would come to be seen as a bonus aspect to these capabilities.

Despite the ready availability of modern plant IT and automation, and the numerous documented cases of manufacturers realising the benefits of modern systems, many factories remain wedded to paper, spreadsheets and ad-hoc/as-able machine data analysis efforts (often based on manual extraction and collation of data from individual assets).  The implications of this go beyond it being comparatively inconvenient to deal with remote working.

Firms that have incorporated more modern plant solutions already enjoy significant advantages in their cost of production, their operational flexibility and their predictability in relation to meeting demand. The question is whether such current advantages will be further entrenched, or whether we will see a surge of investment from others to take on these capabilities. There is also a question of whether the firms catching up will look to go beyond simply sustaining their operations and towards fine-tuning or even re-shaping them.

Lessons from leading organisations

The next wave of technology adopters can benefit from observing how organisational structures and behaviours have been changed as modernisation has unfolded. New tech has certainly changed the way line-side operators stage, execute and manage production. However, the freer flow of data to different stakeholders has also seen improvement in surrounding business processes such as supply chain coordination and product design.

One of the cultural changes common in leading firms is broad recognition that detailed operational data supports the work of many stakeholders traditionally seen as removed from the production process. This has prompted the formation of cross-functional teams responsible for ongoing learning about the continuing evolution of automation and software.

Tasked with spotting developments that could yield outsize impact, not just sustain incremental gains in capability, cross-functional teams embody the recognition that technology is not only a critical tool to enable existing strategies, but potentially the key to new ones. That behavioural change also means that tech adoption is no longer intimidating or mysterious. With IT, operations, product design, engineering and quality leaders learning together, each group’s perspective and knowledge becomes part of a common understanding of how to understand the next technology wave in the context of the firm’s challenges and opportunities.

If the COVID outbreak showed how rapidly our steady work routines and supply networks can be disrupted, this is the time to see how technology can provide UK plc with increased resilience and a renewed operational vigour. It’s vital that manufacturers adopt the tools that support better insight and collaboration for the impact they can have on productivity, flexibility and even innovation. Modern plant systems should be seen as critical to success all the time, not just as a convenience during a pandemic.

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.