What are examples of Edge analytics in manufacturing?

Edge analytics is a vital component of manufacturing’s 4.0 landscape with many viable, unique use cases. If you have Edge data, you need Edge analytics. It’s no longer enough to collect data: you must find diverse use cases and examples for Edge analytics across your manufacturing organization. 

Let’s explore some key Edge analytics examples within the manufacturing ecosystem by looking at use cases in CPG, Paper and Packaging, and Beverage production. 

Edge analytics in manufacturing example:

Consumer Packaged Goods (CPG) manufacturer

Consumer Packaged Goods (CPG) are usually produced at rapid paces with high volumes. These products include toiletries, packaged food items, makeup, and household products.   

When you mass-produce a product, every second of lost production adds up—both in terms of impact and cost. Closing down the line to address a problem or a lingering defect impacts everyone in your supply chain. Your trucks are waiting outside with no product, your customers are unhappy, you’ll miss hitting your quality KPI, and teams have to spend time isolating what went wrong, and possibly working overtime to cover the gap in output.  

Imagine you work for a diaper manufacturer that produces 800-1,000 diapers per minute. Right now, your company relies on daily sample reports from your Laboratory Information Management System (LIMs).

By only performing quality checks twice a day, you and your colleagues are often late in recognizing quality defects. Some of these checks may even pass a lab sample test but miss other defects in the batch. Working reactively to defects is costing you both time and money. With lower output rates, you need to produce additional products to compensate for the lost ones. 

Any data latency has the potential to dramatically impact your production costs. Edge analytics applications move manufacturers away from “after the fact” and into the present moment (and in some cases, even into the future state!). These easy-to-use applications automate your condition and quality monitoring and alert eams about any problems in real-time. 

For example, Braincube’s Counter App automatically monitors and displays real-time production rates and defect rates. In addition to tracking production quotas in real-time, this level of insight allows teams to pivot if conditions change unexpectedly. 

In the case of our diaper manufacturer, the shop floor teams can easily see when defect rates start increasing. Teams can start investigating the source of these defects quicker than if they simply waited for the next quality check. By automating your quality control and displaying it in a visually-appealing dashboard, teams are freed up to complete other, more complex tasks. 

Alerting applications enable you to take things one step further than simply monitoring live dashboards. Rather than watch for an increase in defect rates, you and your team can receive alerts when defects, vibrations, fill rates, or other metrics hit a specified threshold. This allows you to stay focused on other tasks knowing that you’ll be notified if the line needs attention. 

Edge analytics in manufacturing example:

Paper and packaging manufacturer

Demand for tissue, paper, and packaging products is at an all-time high: paper manufacturing lines are running nonstop. However, as a commodity industry, paper manufacturers don’t have cushy margins to lean on when something goes wrong. Every misstep costs valuable time and money. 

Staying on top of demand and minimizing downtime is crucial. Data needs to be leveraged in live time to maximize product output and hit margin targets. Edge analytics enables teams to gain meaningful insights from the data coming in directly off the line with little to no delay. 

Relying too heavily on data flows can make manufacturers bullish. Most of us have been let down in some way by failed promises of digital transformation. But what if there was an augmented way to alert data teams when something is wrong with incoming data? 

Braincube’s Oscilloscope App makes it possible to verify that your production data is being collected correctly. The app also identifies any abnormal data behavior, ensuring that your data flows are performing as expected. This is especially important in mass-production environments like paper and packaging manufacturing, where reliable Edge data plays a critical role. 

Another way to help teams perform more efficiently is to leverage tools like Braincube’s Transformation Toolbox. This toolset helps boost Edge analytics efforts by gathering and aggregating data signals together with automatic computations like the minimum, maximum, average, etc. These rapid data transformations accelerate discoveries and help teams stay on top of changing conditions, without tedious, manual, or multi-system calculations. 

In short, teams can ensure that production is on track to meet or exceed quotas during production runs, not afterward (when it’s too late to make adjustments). 

Edge analytics in manufacturing example:

Beer and non-alcoholic beverage manufacturer

Similar to paper and CPG producers, beverage companies have slim margins. They’re focused on maximizing uptime, rapid line changeover, and OEE, all while minimizing downtime.

Let’s say you’re working for a high-volume beer manufacturer. In beverage manufacturing, efficiency and speed are vital components. Typical KPIs may include maximizing flow rate (the rate that bottles or cans are filled) or consistent fill levels (e.g., not over-filling or under-filling bottles and cans, which adds unnecessary cost and quality concerns). 

These filling processes occur rapidly. A high-volume beverage production line can fill over 2,000 cans per minute! It’s easy to imagine the domino effect when something goes wrong. If one bottle breaks, production could stop for hours while teams work to clean up the mess, perform a root cause analysis for what went wrong, and resolve the issue. 

Braincube’s Snapshot App captures data from a set period of time after an event like a defect or machine outage. This allows you to extract value from data when it’s the most timely or relevant. The data is captured so you can analyze it deeper when warranted, such as when a major outage occurs.

Getting ideal usage and performance from expensive equipment can be accelerated with Braincube’s Machine Status app. The app generates automated reports of the average time for each status by day, week, month, or year. These reports make it easier to build predictive maintenance strategies and work towards less unexpected downtime in the future. 

Since beverages are consumed by customers, quality is imperative in the beverage industry. Beverage products must go beyond being safe for consumption: they must meet consumers’ taste expectations time and time again.

Edge analytics tools enable you and your teams to stay on top of possible quality issues, a critical concern for food and beverage manufacturers. This is especially true in the case of Braincube’s Alerts application.

With the Alerts App, you can set alerts that instantly notify specific teams or employees when key indicators begin dropping in performance. These alerts can range from out-of-spec vibrations to unexpected quality scores. Alerts help teams get the information they need during production so that they can be as focused, agile, and efficient as possible.

Conclusion

Leading manufacturers know that winning in today’s environment doesn’t mean collecting the largest amount of data: it’s about utilizing the right data. With Edge analytics technologies, teams can get the right information, at the right time, to make the right decisions for current production challenges.

Edge analytics tools are valuable across a wide range of manufacturing industries. However, if you’re thinking about bringing these tools into your organization, look for opportunities where speed and efficiency intersect. This is where Edge analytics technologies, tools, and applications can make the biggest impact on your organization.