A new reality for dairy processing

Augmented reality (AR) has a long relationship with the industrial sector. In fact, one of the first applications of the technology was in the navigation of NASA’s X-38 spacecraft. Today, the advancement of AR technology has made it easily accessible to consumers and engineers alike via smartphone apps. Here, Sean Robinson, service leader at food and beverage digitalisation specialist Novotek UK and Ireland, explains how dairy manufacturers can use AR to augment plant maintenance.

In the dairy industry as in many others, margins are everything. Business leaders always want their operations to be as efficient and effective as possible, with the highest possible uptime and the lowest possible operational expenses. This means low product wastage, high energy efficiency and lean processes.

However, dairy manufacturers and processing plants face an additional pressure. Raw dairy produce has a very limited lifespan, so it’s vital that it is treated in a timely fashion to prevent potential risks to public health. Unsurprisingly, regulation is very stringent on factors such as hygiene and the correct temperature for milk to be stored at pre-treatment. Each of these are defined in the UK’s Dairy Products (Hygiene) Regulations 1995.

This is one of the key distinctions between dairy processing and many other industrial segments. Improved process speed and operational efficacy isn’t simply sought after to increase throughput and profitability. It becomes an objective because it directly correlates with the safety of products. If raw milk spends too long at a temperature above 6 degrees Celsius without being properly treated, it becomes at risk of harmful bacteria growing.

Whether a dairy manufacturer is setting out to reduce their product wastage or lower energy usage, one thing remains a constant. No matter how many shiny new machines, automated systems or wirelessly connected widgets a business invests in, maintenance will be the key to getting the most out of hardware investments. In spite of this, it’s often the part of the process that many engineers begrudge, due either to it being time-consuming, labour-intensive or highly complex to maintain certain systems.

Digitalising maintenance

Fortunately, advancements in industrial automation systems over the past decade have gone some way to addressing the challenges conventionally associated with maintenance. As more industrial assets — whether that is the pump in a milk pasteuriser or the SCADA system controlling a packaging line — are able to connect with manufacturing execution systems (MESs) and enterprise resource planning (ERP) systems, dairy plant managers are presented with an increasingly reliable and scalable means of determining maintenance schedules.

This eliminates some of the guesswork from maintenance schedule, which means that plant managers can devise maintenance schedules that are more strategic. For example, a SCADA system might pick up a dwindling performance in a motor. If the SCADA system is connected to an MES, the plant manager can easily access this information remotely and make maintenance of that motor a priority. For perfectly healthy systems, they can be maintained only when their performance data indicates they need it.

The only downside to this is that if a plant contains thousands of connected data sources, it can simply be too much data for a plant manager to reasonably analyse to determine the ideal maintenance schedule. More advanced MESs resolve this problem, a good example being GE Digital’s Predix, which incorporates machine learning artificial intelligence (AI) into the system.

This AI can identify correlations and trends in data sets, allowing it to alert managers when maintenance should be conducted on a system. In effect, the AI learns the indicators of poor equipment health and can facilitate a shift to a predictive maintenance model, reducing unnecessary labour and time usage.

Although this makes life easier for plant managers, it does little to simplify the maintenance process itself for engineers. This is where AR comes in, by using the data within the MES and a purpose-built industrial internet of things (IIoT) platform to reimagine maintenance.

Bringing AR to dairy

A contributing factor to the complexity of maintaining some systems is a matter of design. Engineers need to know the most efficient and easiest way of accessing the components that need attending to, and this is not always an easy task — not least because it requires prior knowledge of the specific parts that are under-performing.

Take a milk pasteuriser for example. If the problem is that the flow rate of milk is lower than it should be, it could be a problem with the centrifugal pump, the valve or even the flowmeter measuring flow. With enough performance data from each of these parts, maintenance engineers can easily know which to inspect. And what better way to access this data than a digital overlay showing real-time performance data of each part?

This becomes possible with an industrial AR application like those available through PTC’s ThingWorx 8 IIoT platform, offered by Novotek UK and Ireland. This platform allows dairy engineers to build apps that are specifically designed for their plant and applications, ensuring that the app is suitable for any set up. Of course, the key to achieving this effectively is to work with an industrial AR expert like Novotek to ensure everything goes smoothly.

With that in place, maintenance technicians and engineers can either use AR headsets or their mobile phones to access the application. Simply by holding their phone up to a pasteuriser, engineers could see real-time performance data and could zoom in deeper to see specific parts. With a virtual representation of the pasteuriser’s centrifugal pump on the screen, engineers can inspect and identify if it is the part causing problems. If it is, the AR app can show the easiest way to access and maintain it.

And if a problem is particularly puzzling and the maintenance engineer isn’t sure how to address it, AR applications make it possible for specialist technicians to remotely view and advise on the issue. This encourages the sharing of specialist knowledge and improves the effectiveness of overall plant maintenance.

The value offered by AR is applicable to almost every connected system in a dairy plant. Let’s say that a dairy plant’s manufacturing execution system highlights that a rotary evaporator, used to standardise the dry matter of milk in the early production stages, requires maintenance. As the evaporator consists of several components, a maintenance engineer could use AR to see a virtual representation of the components in the evaporator and identify which needs attending to.

By using a purpose-built AR application, the engineer can view real time system data from the ThingWorx IIoT platform and see which components are performing inefficiently. In this case, it could be that the evaporator’s compressor requires lubrication. The engineer can then resolve this in the least disruptive way possible, minimising the impact that necessary maintenance has on production. Crucially, this technology maximises uptime and improves overall equipment effectiveness in the most efficient, effective and easy way possible. If a dairy manufacturer is looking to make their operations as lean and efficient as possible, AR seems like the ideal tool to help achieve precisely that.