Creating the “Things” in the Internet of Things: Part 2 – Realizing the Potential of IoT




In Part 1 of this blog series, we focused on how the Internet of Things is helping PLM expand into the operational phase of a product’s lifecycle – allowing PLM to reach the complete product lifecycle and “close the loop” by providing information from products’ operational and service phases to engineering, quality, and other stakeholders. In Part 2, we will explore how PLM can help product development companies realize the potential of IoT technology. 

The benefits of deploying Internet of Things technology are numerous: data gleaned from it can be used to minimize or prevent product failures, optimize production processes and product use, and dramatically reduce service and operating costs of products – just to name a few. So with all these benefits, why aren’t more product development companies leveraging data from smart, connected products? The problem isn’t sensors: they are growing cheaper and more ubiquitous every day. And it isn’t data storage: digital storage size increases at a stunning pace even as it too plummets in price. In fact, these two factors together mean that companies can literally collect more data than they can use. And, without the means to translate this data into actionable intelligence, they frequently do. 

Designing and leveraging smart, connected products relies on product lifecycle management – PLM – technology. Uncovering meaning from a sea of IoT data is a process of identifying variability between real-world results and their expected values, analyzing the outliers, and communicating them to stakeholders who can investigate why they occurred and take action to prevent them from happening again. But knowing what constitutes as an “expected” value for any given product is a complex problem because product development itself is so complex. And PLM is in the business of managing these complexities. PLM manages both the variability within a product, as a range of teams from across the product lifecycle introduce highly governed changes to see a product through to its completion, and the variability across products, as different configurations of a product are released to manufacturing. PLM creates and manages the final, unique baseline definition of each product’s configuration as it was released to market,  capturing its design intent from  expected operating conditions, user behavior, performance results, quality predictions, and service planning. Knowing a product’s expected performance is the first step in identifying and analyzing its outliers -- making data from PLM central to understanding the data collected from IoT.

But PLM does even more. Each product definition managed in PLM houses a range of associated data – part information, documentation, software versions, and powerful CAD visualizations – that, if tapped, can be leveraged to inform and enhance IoT technologies and apps themselves. Robust connections between a product’s complete digital definition in PLM and its physical counterpart or “twin” operating in the field would enable PLM to serve up valuable product data to downstream IoT technologies and apps. This connection would communicate information about predicted product performance – including expected quality, reliability, and usage KPIs for each product configuration, for example – to assist in the analysis of IoT data. And, it would drive valuable information from product development – including CAD visualizations, service plans, predicted failure rates, software configurations, and more – into IoT technologies and apps, including service technologies and AR /VR experiences, to ensure their accuracy and relevance. 

Finally, this connection between PLM and the product it creates is just as vital because of its ability to communicate IoT data back into engineering and other stakeholders that leverage PLM. PLM already controls the flow of product data throughout an organization. Extending its reach into the operational phase of the product’s lifecycle extends its value by leveraging the workflow and communication strengths of PLM to deliver essential intelligence from IoT data back to the stakeholders already involved in the product’s lifecycle, development through service. 

But must PLM as we know it change to accommodate an IoT age? To develop smart, connected products, PLM technologies must be equipped to bring ECAD, systems engineering, and software development data and processes into its purview. And to better manage smart, connected products throughout their complete lifecycle, including the operational phase, PLM technology must be closely integrated with IoT platform technologies and big data analytics that connect to and process data returning from sensored products. Finally, to leverage data coming back from IoT, PLM needs the ability to consume sensor data, resulting analyses, and interpretations as well as connect that data with product development stakeholders who can use it to improve current and next-generation products: closing the loop on the work they do. 

To learn more about how PTC PLM solutions are already realizing the value of integrated IoT technology, view the Windchill 11 Telecast