Brew Better Beer: How the IoT Can Improve Sustainability and OPEX

According to Statista, the beer segment worldwide is projected to grow by 5.44% (2023-2027) resulting in a market volume of US$753.4bn in 2027.

While this may mean plenty of growth opportunities for brewers, it also means that efficient production is key to financial success and embracing modern technology is a must to stay competitive.

So how do breweries become even more efficient and improve quality consistency? How can brewers hold themselves accountable surrounding company sustainability initiatives?

Let’s dive deeper into these challenges and how the IoT may play a critical role in helping solve them.

Brewer’s Challenges with Quality Control

In the beer world, or for any beverage producer really – quality equates to consistency. Brewers know that if temperature settings are off on one of their filtration machines, a bad batch of beer might be produced. And if this issue isn’t corrected quickly, there will be many more bad batches and a whole production day wasted. For example, a single one-hour stop can equate to USD $10-15 thousand dollars lost for mid-size breweries.

Some of the root causes to performance control challenges are:

• Lack of visibility into machine performance metrics that impact quality.
• Operators may run equipment differently, creating variances in flow rate and temperature data collected.

Brewer’s Challenges with Sustainability Initiatives

According to a 2020 Euromonitor Lifestyles Survey, more than a quarter of those surveyed said they boycott brands that do not align with their ethical values. This means communicating sustainability strategies is starting to play an increasingly important role in a business’ success.

Some of the root causes to unsuccessful sustainability initiatives for breweries are:

• Currently leveraging materials and technologies that may be potentially harmful to the environment.
• Inability to obtain accurate total water consumption and energy usage metrics, or if the information is collected, there is potential nuances in data.
• Expertise is required to analyze for trends and determine which sustainability initiatives to pursue and which changes will provide maximum impact.

(To learn more about beer production sustainability challenges and solutions, you can read our posts here and here.)

Brewer’s Challenges with Process Inefficiencies

Brewmasters rely on data collection and analysis to help them identify process improvements, however, the data-collection process can be a manual one, which presents several problems.

Some of the root causes for the inability to implement process improvements:

• There is no guarantee of accurate or consistent data collection performed by humans.
• Resources (person or equipment) are required to monitor data.

Or the process can be digitized (using the IoT), but poorly done so, which creates the following problems:

• Data can be stored in multiple locations or with multiple employees.
• Massive amounts of data can create analysis paralysis (meaning reviewers become so overwhelmed with information that they cannot dissect it to make strategic business decisions).
• Expertise is required to analyze for trends and determine optimal settings.

The bullets above mean that a brew master may struggle to identify issues with the line or machinery, thus taking much longer to solve for problems.

Smarter Beer Production with the IoT

Here is where the Internet of Things (IoT) and smart machines come into play. IoT refers to a network of devices and sensors that capture and communicate data with one another. The sensors collect data that can be routed into a single place for review.

Through the collection of this data, brewers can identify key problems with their beer filtration process – not only for one specific machine, but potentially for multiple machines at sites across the globe. In addition, brewers can improve product quality and even feel confident in implementing sustainability initiatives that drive impact.

Benefits of Smarter Beer Production: Quality Control

Oxygen level and haze can impact a beer’s flavor, so continuous monitoring of relevant quality parameters enables brewers to match consumers' quality demands.

With the filtration machine connected to the cloud, you can see in real-time if the oxygen levels are out of specification and if you use smarter machines, the machine will adjust process parameters to meet the quality specification. Now the beer batch is guaranteed to taste good, and your beer’s quality can remain consistent batch after batch.

Leveraging the IoT on your filtration machine ensures that you collect the right quality parameters (i.e.: oxygen and haze) to ensure that they are met.

Benefits of Smarter Beer Production: Sustainability Initiatives

Brewing uses a significant amount of water. According to the University of Vermont, it takes three to seven barrels of water to create just one barrel of beer.

Beyond improving quality, the IoT can support sustainability initiatives for your brewery through the tracking of volumes of water used by your machine, helping you identify where you may be able to use less water (a non-renewable resource.) For example, Pall has seen smart filtration machines reduce water usages from three to seven barrels down to five barrels or less.

Beer production also requires a decent amount of energy; according to a study by the Brewer’s Association, it takes 50-60 Kwh (or 50,000 watts) to produce one barrel of beer. Leveraging membrane filtration for microbiological stabilization compared to thermal installations is the first step to achieve sustainability, as flash pasteurizers consume up to 80% more energy on the thermal and electric side compared to beer final filtration with membranes.

Pair a membrane filtration system with the IoT and you can identify even more areas to optimize machine performance, further reducing energy usage during production.

Leveraging the IoT on your filtration machine ensures that you collect and track the sustainability related metrics (i.e.: water and energy usage) so you can continually reduce consumption.

Benefits of Smarter Beer Production: Improved Efficiency

Identifying problems through IoT data collection enables corrective actions to be taken quickly, ensuring a more effective outcome.

This enables process visibility that can help detect problems, expedite emergency service calls and better predict requirements for routine maintenance on your filtration machine.

Imagine the following scenario:

Let’s say you are a brewer that has fully automated production and the capacity with two lines x 600 hl per hour. It is a three-shift operation with four brands being produced daily. You operate your entire brewery from the central control room; the distance between the filter room to the control room is an eight-minute walk.

You’re sitting in your control room when you notice that your filter lines show different specific throughput results. The performance of the filter lines varies from not noticeable to significant differences in filter capacities. Selective investigations and analyzes based on the data and process curves did not reveal any root causes of the variances in performance.

Due to the physical distance between the central control room and the filter systems, it is next to impossible to watch the machine work in real-time while you also review the performance data.

In addition, two different platforms are used to review process control data, which makes direct comparison even more difficult. Since the differences make a significant financial impact to your lines, you decide to assign a qualified employee to analyze the data and process over a longer period to determine root cause of the line performance issue.

In this hypothetical example, it takes you approximately 18-months, a full-time process engineer, around USD $200 thousand dollars and the creation of an on-site SCADA (supervisory control and data acquisition)* to do the following:

• Adapt the existing SCADA data programming in order to better manage, compare and analyze the data.
• Analyze the relevant process data including peripheral influencing variables.
• Adjust cleaning effectiveness to a comparable level for the installed lines, based on the analysis of the cleaning times, detergent consumption and cleaning processes.
• Adapt the upstream process steps (fermentation/storage cellar) for smoothing out the solid loads to the centrifuges.
• Optimize the centrifuge efficiency to achieve a more constant solids content at the respective filter inlet.
• Improve control and handling of the filter inserts to optimize inventory management.
• Identify a cost-reduction of 15-20 % depending on beer type and volume.

But by using an IoT connected filtration system, the relevant data for a process check and optimization are individually configured, the evaluation is carried out directly at a workstation and the effectiveness of adjustments is tracked promptly – meaning the full optimization program to solve this same problem would not take as long to solve or cost near as much.

And if you leverage a Pall Beer IoT solution, you have access to our SLS team who can help you analyze the data and provide consultative feedback to improve your machine optimizations and implement further process improvements.

IoT and Filtration Machines Optimal Solution for Brewers

Leveraging technology to gather insights on the production line enables brewers’ greater control over the manufacturing process.

By using digital technologies such as the IoT to monitor their filtration and stabilization machines, brewers gain a much deeper insight into production processes.

Of course, the key is to have an IoT solution that tracks and provides the right data, enabling brewers to make adjustments in real-time to improve quality and sustainability initiatives and increase operational efficiencies, thus impacting their bottom-line.

To learn more about how Pall can help you enable the IoT on your filtration machine, contact us.

 (*Cost and time surrounding a full-scale optimization program to solve the production/process problem may vary based on size of brewery, total number of lines, types of data collection used, etc.)