How manufacturers can capture the knowledge of experienced workers

Digital presents new opportunities to capture knowledge more effectively

Digital presents a massive opportunity for manufacturers to capture experienced workers’ knowledge, and to use that knowledge in conjunction with all the variable process conditions. This knowledge asset can be used to create more granular standards that enable less-experienced workers to effectively deal with the myriad changes a typical manufacturing process can experience.

With the proliferation of internet of things (IoT) sensors across the shop floor, manufacturers now have access to increasingly rich data on process, equipment conditions and performance they never had before. With that data fed into a Microsoft Azure-based platform, manufacturers can identify an event that happened at a point in time and record how experienced workers responded. In other words, it’s now possible to document in Azure that when certain measurable conditions existed, these experts recognized what was happening and reacted in a specific way because they’ve seen the same conditions thousands of times before and know what adjustments they needed to make.  

When a manufacturer builds models that combine this shop floor data with the intuition of knowledge workers, it can generate truly powerful insights that are specific to the manufacturer’s own dynamic environment. That prediction and those data points can then be built into the company’s standards. Workers with less experience and intuition can use this information to understand what they should do when the data tells them they’re encountering the same situations.

The same approach benefits maintenance activities. Let’s say a manufacturer has a piece of rotating equipment that loses its set point and begins vibrating. If the equipment doesn’t have sensors that generate performance data, a maintenance worker would have to take the equipment offline and try to figure out what was wrong and fix it. A highly experienced person who’s very familiar with the equipment might be able to do that in an hour. A less-experienced worker might take three or four hours — and may end up replacing non-defective parts in a trial-and-error effort to eliminate the vibration. A standard based on the experienced worker’s approach — how he diagnosed and fixed the problem — accompanied by a video of how to do it would help less-experienced workers benefit from that knowledge (and, thus, significantly reduce the equipment’s downtime). Augmented reality glasses such as the Microsoft HoloLens could further help the worker with the maintenance procedure, ensuring compliance with standards and taking more time out of the process.  

Now imagine the equipment is fitted with a variety of sensors that measure temperature, torque, resistance, voltage, pressure and other performance aspects. The data those sensors generate can enable workers to zero in on the exact cause of the vibration — for example, a pump nearing failure. Then, using a mobile device to access the Azure-housed standard and video for repairing the pump that’s based on an experienced worker’s knowledge, any maintenance person can quickly and effectively fix the pump. That’s a far better approach than a worker having to spend time poring over a paper-based manual with the pump’s bill of materials and schematic trying to figure out what to do. 

Think back to the HVAC inspectors mentioned earlier. That manufacturer ultimately used digital capabilities to codify the capabilities of the maintenance workers’ finely tuned ears. By applying sensors across the equipment to measure such things as decibel levels, vibration and sound waves, the company was able to translate the hum workers listened for, into objective data that less-experienced workers could use to diagnose the equipment’s condition. 

The process for capturing experts’ knowledge

Capturing experienced workers’ knowledge and insights so everyone can benefit seems like an obvious and intuitive thing to do. So why doesn’t every manufacturer do it? The reason is — it’s not that easy. Many manufacturing processes are highly dynamic, with myriad combinations of variables that are difficult to account for, and experienced workers do things instinctively on the fly. Getting these workers to sit down and document everything they do in every possible scenario in a written standard is unrealistic — especially when that takes them off the floor, where they’re the most valuable.

Manufacturers that lack operational excellence discipline especially struggle with this. They’re far more likely to experience variations in process performance because they tend to only capture experienced workers’ leading practices in an ad hoc way, almost by accident. These companies could benefit from multimedia platforms, housed in Azure, that can help workers quickly and easily turn their knowledge and experience into instructional content of all kind — including video, audio, written documents, webcam images, screen captures and hyperlinks. So, instead of spending hours writing about, for example, how to repair a piece of equipment, an expert can record a video of the process with his smartphone in actual time and upload it to the platform — where it’s available for other workers to access via their laptops or mobile devices wherever and whenever they need it. 

“Microsoft cloud-based business intelligence tools can allow employees to view and manage data in a visual and intuitive manner, and in real time — enabling them to make more evidence-based and timely decisions at all levels of production, operations and sales,” notes Neal Meldrum, Business Strategy Manager at Microsoft. Similarly, cloud analytics tools can reduce the time and expense of analyzing large amounts of product data, and thereby help reduce production costs.”

Using these and other such tools can get less-disciplined manufacturers on a path to a more formal and systematic approach to capturing “tribal knowledge” that’s embedded in highly advanced operational excellence programs, such as the one developed and curated over 20 years by Procter & Gamble (P&G). The foundation of operational excellence at P&G is the company’s Integrated Work System (IWS), which has played a critical role in the company’s culture and world-class performance for decades. IWS is based on the philosophy of striving for zero loss and 100% employee ownership, and it’s used in all P&G plants around the world to drive continuous improvements in throughput, quality, productivity and cost reduction. It’s also a key component of the EY Smart Factory solution, which is based on leading Microsoft technologies.