Can The Growth Of IIoT Withstand The Challenges of PLM?

Can The Growth Of IIoT Withstand The Challenges of PLM?

Sensors Insights by Alan Mindlin

The IoT may have the power to transform the industrial sector as we know it, but could challenges posed by PLM put a stop to the much needed influence of connected technologies? 

The surge in the internet of things (IoT) technology, market and use cases continues to take many industries by storm. For the industrial market in particular, IoT is bringing with it major waves of change. From augmented reality and data sharing to cloud computing and big data, new innovations are transforming the way manufacturers manage their products and assets.

In fact, it’s been estimated that growth of the global IoT market in product lifecycle and asset management will see a compound annual growth rate of almost 20 percent until 2021. However, there may be some major challenges standing in the way of industrial IoT (IIoT) reaching its full potential.


Free Newsletter

Like this article? Subscribe to FierceSensors!

The sensors industry is constantly changing as innovation runs the market’s trends. FierceSensors subscribers rely on our suite of newsletters as their must-read source for the latest news, developments and analysis impacting their world. Register today to get sensors news and updates delivered right to your inbox.

The Road to PLM

With product development comes the task of managing and securing massive amounts of data. To help alleviate the pain points of managing the product design process, manufacturers began adopting product data management (PDM) technologies in the mid-1990s. Over time, PDM adapted to the rise of the “customerization” age, which involved industrial players outsourcing their manufacturing needs at an increasing rate.

To keep up with demand and allow for increased collaboration, PDM gave way to collaborative product commerce (CPC), a subset of PDM that enabled companies to use the internet and technology to work with suppliers and customers on a global scale. However, as web-based technology became more commonplace and the differentiation of CPC more difficult, the industrial market was in need of a new process to bring increased business value to enterprises and their partners. 

Product lifecycle management (PLM) was created to do all this and more. With the power of PLM, manufacturers can improve the efficiency of each phase of the product lifecycle by incorporating strategy, planning, management and execution.

The key is bringing together product information and business analysis to deliver the types of insights that will optimize the product lifecycle. The software solution is built on a foundation of consolidated data-sharing systems and increased communication, helping to streamline processes, build out strategic sourcing and improve integrations throughout the value chain.


IoT’s Lasting Impact

The future of the industrial sector is shining bright — and much of that has to do with the ongoing impacts brought about by the increased usage of IoT. The introduction of advanced capabilities, such as real-time data collection and predictive analysis, is taking the IIoT market to new heights. With increased access to IoT-fueled technologies and innovations, industrial efficiencies are on the rise.

From knowing the risk of maintenance issues before they happen to leveraging data to maintain safety compliance, the insights garnered from IIoT are helping manufacturers make more informed and strategic business decisions. Not only does the IoT promise to deliver increased efficiencies, but it also enables industrial stakeholders to aggregate data from all connected devices and eliminate data silos. However, the benefits of IoT may hit a wall due to some of the challenges posed by PLM.


Knocking Down PLM Roadblocks

While the potential for IoT solutions is significant, many enterprises find that reaping the rewards is easier said than done. Unfortunately, there are aspects of PLM that stand to significantly hinder the progress IoT can make within the industrial sector.

To fully realize the potential of IoT and leverage product data efficiently, manufactures must understand the challenges brought about by PLM and take the necessary steps to address them sooner rather than later.

Figure 1


PLM Challenge 1 — Unlocking Data

In many cases, data is only as valuable as the ways in which it is used to drive effective and necessary change. But taking the first step toward using data in the right way requires having access to it in the first place. For many manufacturers, variable device data is often confined within the engineering process by PLM. The longer data is stuck within the PLM infrastructure, the longer it will take to find increased value from the information collected about products and services.

It’s only when this data is unlocked that manufacturers will be able to experience its true potential. With the power of more data-driven decisions, manufacturers can take preventative measures when it comes to the maintenance and improvement of their assets.

For example, with access to a turbine’s usage rate and repair history, executives will have the necessary information to help predict when issues may arise or how to increase equipment efficiency. The data aggregated and shared within IIoT ecosystems can positively impact all phases of the product lifecycle, but only when manufacturers address the accessibility of data across their existing systems.


PLM Challenge 2 — Data Sharing

Access to data is important, but so is the ability to share it downstream and across the value chain. The PLM infrastructure, however, makes this next to impossible for many manufacturers. While enterprises often turn to the use of a single spreadsheet to distribute data when needed, the solution is both temporary and risky. Plus, the growth and evolution of IIoT will soon advance beyond the ability for giant spreadsheets of data to effectively store and share product information. The dismantling of information in this way poses serious threats to a company, especially if the spreadsheet is not managed and secured in a consistent way.

Without a holistic view of their own data, enterprises may be unaware of the valuable in sharing portions of the information they collect with upstream vendors or suppliers. But manufacturers aren’t the only ones with valuable data to share. End customers may also possess data that can help to improve PLM planning and drive operational efficiency.   

Enterprises must consider how to effectively solve for the issues of data ownership and security. Addressing the challenges of data sharing starts with ensuring the interoperability of different systems and improving the communication channels between all machines and sensors.

The IIoT is quickly opening up a whole new world to manufacturers. However, making the most of this opportunity requires taking a proactive approach to solving for PLM challenges. Supporting increased connectivity across all touchpoints within an IIoT ecosystem will help manufacturers gain increased transparency, efficiency and optimization throughout the entire product lifecycle. 


About the author

Alan Mindlin is the technical manager at Morey, focusing on new business development and new customer acquisition. He does so by leading strong product design teams, creating state-of-the-art solutions and using Morey's best-in-class manufacturing facility.

Alan has nearly 40 years of engineering expertise, having worked with Bell Laboratories in the U.S., Europe, and Japan, and as a consultant to startups and new businesses. He has a bachelor’s degree in electrical engineering and a master’s degree in marketing and operations from Washington University in St. Louis, as well as a master’s degree in electrical engineering from Purdue University.

Suggested Articles

Critics are concerned about a false sense of public health safety when temperature scanning is used in hospitals and other settings

Machine learning challenge will look for vocal communication between elephants and other behaviors

Iowa State University researchers are working with NSF grant