4 elements of an effective smart manufacturing platform - Embedded.com

4 elements of an effective smart manufacturing platform

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The manufacturing industry, in particular, sees cloud computing as an opportunity to implement revolutionary solutions that usher in the rise of the smart factory.

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As we progress through the fourth industrial revolution and the internet of things, we continue to uncover ways to boost the potential of manufacturing practices through technology. Factories that have chosen to take the leap attribute 20% of productivity gains to smart manufacturing practices.

A prevalent feature among emerging solutions is shifting from on-premise software to utilizing the cloud. While the concept is straightforward, there are many different ways to harness the capabilities of the internet. Here are four elements of an effective, cloud-based manufacturing platform.

#1 Data Integration

Arguably the highlight of tapping into the cloud is the unprecedented level of interconnectedness between machines and their users. In our daily activities, we’re already experiencing the internet acting as a conduit for commands and responses between various devices. Imagine how the same level of integration can be applied to a larger scale in an industrial manufacturing setting.

Gathering data for an entire facility requires additional infrastructures to be in place. Obtaining large amounts of information starts with having the proper instrumentation to capture measurements, such as sensors and transmitters.

Of course, having the measuring tools is just the first of many successive steps. Actionable insights will only be possible with a platform that allows the integration of data from various sources and structures it in a form that lends itself to analysis.

An effective platform for smart manufacturing can handle big data, along with the complexities of varying levels of data quality. For instance, a typical facility will have multiple assets with different standards for measuring performance. While utilizing the cloud helps in gathering the data, an effective program will also have to consider the ability to manage and organize all the nuances of each type of data from varying types of equipment.

#2 Analytics and Visualizations

Assuming that a comprehensive dataset is available, an effective platform requires equally rigorous analytical power to make sense of the data. Using technologies such as machine learning and artificial intelligence (AI) allows analysis beyond merely reporting historical patterns. Instead, these tools pave the way for a more forward-looking approach to maintenance and manufacturing.

For example, platforms that specialize in maintenance aim to increase equipment reliability through reduced disruptions. By leveraging the real-time condition-monitoring information from machines, it is possible to schedule maintenance activities even before any noticeable deterioration. At the same time, because of the sound basis for identifying the need for servicing, these platforms ensure that resources are going into tasks that add value. Predecessors of these advanced tools generally rely on a usage- or schedule-based approach that tends to trigger maintenance activities even when unnecessary.

While intricate analytical processes happen in the background, a practical feature of a good program includes clear and concise dashboards. These tools serve the purpose of giving management an overall health check of the state of the plant. They are also invaluable for the frontline workers in quickly identifying where pending actions must be taken.

#3 Adaptability and Scalability

In truly becoming a smart factory, productivity solutions need to go further than a proof of concept. In other words, the tools and programs that usher improved ways of working need to be adaptable and scalable to the current operation of the plant.

One of the benefits of subscribing to a cloud-based service is the simplified process of acquiring additional processing and storage capacity. Conventional on-premise software tends to be more rigid in responding to such changes in demand.

For existing products, the extent of the service that a cloud-based program offers is also more easily customizable. Say, for instance, a manufacturing plant wants to start piloting a new predictive maintenance strategy for a specific group of machines. With cloud-based software, the manufacturing plant is able to manage data patterns in a more focused manner. If the facility decides to expand the strategy to more assets, an effective platform should allow the facility to do so easily. Expanding the range of services to accommodate new equipment as required will be a part of the continuous improvement to which a platform should adapt.

#4 Ease of Use

A common misconception about using cloud-computing systems is that users need to be experts in the working technology. This idea gets easily misunderstood as workers having to unlearn all their conventional wisdom and completely replace it with coding skills or building algorithms. The reality is not so scary.

Many smart manufacturing platforms on the market have been really good at offering a wide range of options for the user, some of which don’t require technical expertise. Some programs utilize a low-coding environment that requires significantly less training. Other platforms support no-code functionality that can be used by non-technical teams.

Upskilling workers to learn more about the technical side of the software is always an option. When incorporating new technologies which require unconventional skillsets, new roles will naturally emerge that require new ways of working. The good news is that various options are available regardless of the route a company prefers.

Conclusion

The cloud is an invaluable innovation that has limitless applications. The manufacturing industry, in particular, sees cloud computing as an opportunity to implement revolutionary solutions that usher in the rise of the smart factory. While utilizing the cloud is remarkable in itself, the specific ways that providers offer their solutions can significantly impact the success of implementation.


Eric Whitley is Director of Smart Manufacturing at L2L where he helps clients learn and implement L2L’s pragmatic and simple approach to corporate digital transformation. In addition to the many publications and articles Eric has written on various manufacturing topics, you may know him from his efforts leading the Total Productive Maintenance effort at Autoliv ASP or from his involvement in the Management Certification programs at The Ohio State University, where he served as an adjunct faculty member. Eric lives with his wife of 35 years in Northern Utah. When Eric is not working, he can usually be found on the water with a fishing rod in his hands.

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