How to drive value in production processes

Elliott Middleton, director of product management at AVEVA, explains how automating data historians can transform production analytics.

Last Updated: 04 Dec 2020

Throughout the pandemic, manufacturers looking to switch production to new items and improve productivity have become more reliant on data historians providing sensor data analytics.

Previously, only teams physically present in plants had access to operational data in control systems. But with widespread remote working and digital transformation initiatives, offsite engineers now have to access data as well.

Data historians take high-speed sensor readings and record them. Depending on the industry, readings include temperatures, pressure, flow rates and conveyor speeds, taken constantly, millisecond to millisecond then preserved. With the rise of connected devices, collecting and processing this automatically has become affordable and accessible. 

Unlock modernisation

This is especially important in the food and beverage (F&B) industry, due to their fast production lines and multiple products. In the past, smaller F&B manufacturers used a paper-based chart, which may have had as many as five measurements on a chart recorder. In contrast, automated data collection systems collect and store millions of measurements.

Previously, there was limited physical space for chart recorders, meaning that manufacturers had to be selective about what they recorded. Inevitably, they needed something that wasn’t on the paper.

Now, with control systems, IIoT sensors, and edge devices, it is easier to collect and record anything that might be useful for process improvement to troubleshooting. Regulatory reporting is the focus for using historians to store operational data in some industries. Automating the collection and storage of operational data enables businesses to produce the data they need for compliance.

Diagnostics and troubleshooting

But how can you best extract value from that data? In AVEVA’s recent research, nearly three quarters of manufacturers said one of the key values of historian data came from diagnostics and troubleshooting.

Similarly, 43% said it helped identify process improvement opportunities and 56% used it to help reduce energy consumption. 

Automated data collection and analysis reveals patterns and trends that can support and speed up troubleshooting. If operators can discover problems in 30 seconds, instead of in five minutes, then they solve quicker. 

Failing fast

High-speed packaging lines are jammed with packaging material. If a yogurt plant that is producing 10 cartons a second is down for a minute, with 100 small faults a day – that’s 600 yogurt cartons affected. Accurate data is key to downtime tracking, production costing and energy consumption reporting, enabling manufacturers to increase uptime and allocate energy cost to individual production units.

Very often manufacturers don’t know what they don’t know. Accurate data provides fresh insight, spotting opportunities for process improvement. 

More accessible

Detailed operational data has often only been accessible in the control room. That may simplify security but is a challenge if more people benefit from that information. So sites are mirroring the control room so it’s more accessible on network. 

This hybrid approach is ideal for improved and more timely decision making by more people.  Now engineers can access the data from their mobiles and from home. That has proved invaluable in the Covid-19 era. 

In less traditional manufacturing applications, the accurate data is still valuable, but sites lack the needed infrastructure, staff and expertise. In developed economies, health and beauty products are sold in large containers. But in emerging economies, those are too expensive, so products are produced in smaller packaging.

To avoid high distribution costs, local shampoo plants operate from a miniature plant the size of a shipping container. Whereas in North America there might be four large plants, in an emerging economy that would be replaced by 50 shipping container-sized plants. 

Similarly, some water treatment plants operate in a shipping container, to clean water in remote locations, such as mining operations. There is no room for servers or IT engineers to handle data onsite. But the information is just as valuable to small operations and using a fully-managed cloud solution makes it cost-effective even for these small sites.

Bags of cash

A mechanical bag-filling application had several steps. The systems integrator committed to supplying a system that would deliver a rate of filling 2.5 bags per minute. Then they discovered they could fill 3.5 bags. Great. We overachieved, we’re done. 

This particular system integrator recorded the processing steps in the data historian. They ran a report on these steps, discovering the number of milliseconds each operation took on average. This uncovered a wide variation in the time it took to close the bag. They investigated the reasons for the variation and shaved five seconds off the longest time. That increased production by 20%. Each bag was worth $250, so that translated to almost $750k per day of increased production.

Operations leaders looking to the cloud used to consider security to be a major concern. For some time, there was the perception that on-premise data storage was a more secure option than allowing the data to leave the organisation. That has changed. There is an increasing recognition of the high level of security of the cloud itself – and secure, send-only data architectures protect outbound data. Cloud data is now safely behind multilayered security that is hard to match in a small, on-premise collection of servers

A highly automated process is a prerequisite to collecting and getting the best from historian data, providing insight to improve diagnostic troubleshooting and identify improvement opportunities.

As more organisations gain access to sensor data, more job functions can use it. Many small and medium size manufacturers are still getting by with paper-based chart recorders, or perhaps with basic data loggers. Long term, though there is an inexorable trend towards automated data collection, data historians, and cloud-based solutions. Faster reporting and diagnostics drive productivity that provides an unbeatable competitive edge – and profit.

Elliott Middleton is director of product management at AVEVA 

AVEVA Group plc provides innovative industrial software to transform complex industries such as Oil & Gas, Construction, Engineering, Marine, and Utilities. AVEVA’s software solutions and platform enable the design and management of complex industrial assets like power plants, chemical plants, water treatment facilities and food and beverage manufacturers – deploying IIoT, Big Data and Artificial Intelligence to digitally transform industries. 

For further information visit

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