IoT enables a complete PLM implementation and digital transformation.
There are many different conceptions of the Internet of Things (IoT), and varied viewpoints about how to use it. But these are finally coalescing into an understanding of the IoT as an ever-growing collection of digital connections among and between physical “things.”
In this article, “things” is broadly defined as anything in the physical world, provided it has embedded electronics and digital connectivity. A big part of the challenge of using the IoT is that it is an ever-growing collection of connections. Sooner or later, every object and all its data will go through the IoT-connected world—even things that don’t yet exist.
This points to the power of digital connectivity (regardless of scale or scope) and underlines:
- Why the IoT is the biggest challenge, and biggest opportunity, for true closed-loop end-to-end product lifecycle management (PLM), and
- Why only an appropriate PLM approach can open the IoT’s complete value.
This article, focusing on IoT, is part of a series (that can be read in any order) on the 12 biggest trends and enablers that are essential to every organization’s successful, effective and complete PLM implementation and digital transformation. In previous articles, I have referred to these trends as, what CIMdata calls, the Critical Dozen.
What is the IoT and Its Connection to PLM
To my surprise, getting a handle on the IoT, explaining what it is and defining its connection to PLM, proved to be one of the toughest challenges when coming up with the Critical Dozen. So, although this article will focus on the “why” and “how” of the IoT and PLM, it’s worth revisiting what exactly the IoT is.
I am convinced that PLM will make a big difference to those who develop solutions for the IoT, and to everyone whose job requires finding and using the connectivity and data the IoT provides.
Getting to that point of understanding has not been a smooth journey for most. Extracting any quantifiable value from the IoT has often been mystifying. Fortunately, for a few clever digital entrepreneurs and even some of the analysts and consultants who work with them, the value of the IoT has begun to emerge. And this value is growing as innovations in IoT comprehension, tools and strategies move into everyday use.
At long last, the realization has taken hold that the IoT is not some vast, impenetrable accumulation of ones and zeroes; instead, it is a resource whose capabilities, extent and riches we are now able to grasp.
For many years, most IoT users and solution providers thought providing some form of digital access was sufficient, i.e., connecting a physical device to the Internet. “IoT access” by itself is now seen as an empty promise. IoT access has proved useful only in limited ways without add-on tools to facilitate the understanding and comprehension of the data collected.
A common “access” use was tracing connections between physical objects and reformatting them for use by product developers and field-service techs. But even this fell short of what was most needed: tools to leverage IoT data to help guide and generate better performance of any assets for which IoT users were responsible.
Part of the problem is that each industry, or industry group, and their analysts approached the IoT from different starting points. Though the IoT’s connections and data are widely used, that use and value are constrained by each group’s viewpoints. This is obvious when we look at the wide variety of needs and goals of the biggest IoT users, including manufacturing, automotive, aerospace and defense, logistics and fleet management, retailing, medical care and public utilities.
Individuals from each of these groups have told me about what their sector is looking for from the IoT, and every answer differs greatly. It’s no surprise that there are so many different, and even contradictory, views of the IoT.
The foregoing helps explain why so many PLM users have struggled with the IoT. Hard data such as dollar projections of sales (in the trillions) and IoT market values (also in the trillions), as well as tallies of connected devices (in the billions), vary too widely to inspire much confidence that they have the credibility needed for baselines in business plans. Yes, all analysts predict double-digit annual growth, but so what? Growth how and in what? There has been little to no consensus.
The Benefits of Connecting Your Product Lifecycle with IoT
At this point, it is time to stop trying to define the IoT and focus on how best to use it. For me, that means understanding data coming back from the field (as a primary example of useful IoT connections) and feeding that data into informational flows of our “things.” These are the products, systems and physical assets, all with their own embedded applications, from our enterprise plus those of our suppliers and customers.
PLM is now coming into widespread use, tying factory equipment to products in the field and tying production equipment and its resulting products—throughout their entire lifecycles—back to their original design/operational intents. This works best when we represent “things” with PLM’s digital twins and feed them with PLM’s digital threads (i.e., webs) and their end-to-end connectivity. In summary:
- Digital twins make IoT data/information comprehensible and usable, by keeping them up-to-date and accurate.
- Digital threads/webs and their end-to-end connectivity provide the technological backbone of all data/information coming in from the field; this is why PLM’s digital threads/web mesh so effectively with the IoT.
- Joining PLM to IoT can drive end-to-end collaboration by directly connecting product development to both manufacturing and the products’ users.
Immediate ways that product developers and users benefit when PLM and the IoT come together include identifying how products in the field are actually being used (which often differs from design intent) and pinpointing functionality that is rarely or never used. Identifying a product’s unused capabilities can accelerate the refinement and production of profitable modifications, upgrades and new versions and trigger the development of innovative follow-on and next-generation products.
In addition to these potential benefits, IoT connectivity enhances many elements of the enterprise’s PLM solution. In a webinar entitled “CIMdata’s Critical Dozen: The Top 12 Trends & Enablers for Digital Transformation,” I also covered benefits like how:
- Robust architectural concepts and detailed-design feedback from actual usage, manufacturing capabilities, maintenance and repair.
- Testing, which includes test-bench and performance monitoring for prototypes, subsystems and components, plus monitoring proving grounds and test labs and optimizing their performance and management.
- In manufacturing, visibility and feedback on defects and the effectiveness of supplier quality control plus early warnings of problems in OEM and supplier operations and in supply chain logistics.
- After-sales service feedback on diagnostics and repair of defects in the field, along with success/failure alerts, product health monitoring and maintenance scheduling.
More generally, IoT connectivity offers all sorts of data from “edge” sensors, devices, equipment, IT systems and even smartphone SIM cards. All these continually feed information into decision-making and planning processes that help reveal insights, enable root-cause analyses and define strategies for control, among many other applications.
How to Use IoT with PLM: The Challenges
Lest anyone thinks working with the IoT is straightforward and easily delegated to clever new hires, I offer a word of caution. The data/information flowing into, out of and through the IoT’s countless connections changes constantly. Content, configurations, origins, destinations and the connections are continuously new.
This is why I consistently urge at the very outset to carefully define what your business unit, enterprise, agency or organization needs from the IoT. Secondly, I suggest organizations engage expert technical help before anyone writes a single line of new IoT-oriented code.
Why? Because what we are actually doing when we approach any “thing” in the IoT is finding the appropriate connection and attaching it to a loop accessible by users and the digital twin.
This should immediately bring security to mind, which we must take seriously. In the wake of the COVID-19 disruptions and the stay-safe/work-from-home paradigm, enterprise security has been greatly extended—and consequently, sharply enhanced. The huge jump in the number of IoT-connected end points is attractive to hackers; expect push-back and blockage of any approach to the IoT’s connectivity loops that has not been carefully thought through.
Resolving security issues in the IoT (or anywhere else) means establishing new levels of trust and verifying good intentions. Once that is done, IoT users and project managers can look forward to gains in capabilities. These gains will include deeper comprehension of engineering data/information, more effective collaboration throughout the organization and stronger ties to suppliers and customers.
Going deeper into the IoT raises challenges that are now confronting IoT solution developers. These have been spelled out concisely in a recent McKinsey & Co. report titled, “IOT value set to accelerate through 2030: Where and how to capture it,” and include:
- Recognizing that effectively using the IoT requires transforming the organization’s operating models for information—extensive change management—not just learning to use a new technology.
- The persistence of proprietary operating systems in the IoT that interoperate poorly, if at all.
- Implementation and deployment in the IoT can lead to hefty hidden costs, difficulties and time sinks for software customization, recoding, hardware retrofits and secure connectivity.
- Vexatious privacy concerns following the adoption of laws on data protection and privacy; for example, the California Consumer Privacy Act and the European Union’s General Data Protection Regulation (GDPR).
- Cybersecurity, as mentioned above.
Readers familiar with my articles will recognize these as key issues in many aspects of digital transformation.
These well-known challenges are why I say that successful IoT-enabled strategies must have a strong PLM foundation. This foundation allows PLM to act as the cross-functional process and data backbone, a necessary requirement for the success of any IoT-enabled strategy and its organization-spanning functionality.
And as I regularly point out, all organizations run on data. This will not change.
In conclusion, the IoT is all sorts of countless “things” that exist in terms of establishing and maintaining their connections to each other and the enterprise with all its extensions. This points to a promising future and significant benefits for PLM users and developers of next-gen IoT solutions. I have also endeavored to show why the IoT is the biggest challenge facing PLM, as well as PLM’s biggest opportunity—thus far, anyway. These specifics help underscore why only PLM can open the complete value still trapped in the IoT’s connectivity, and what that connectivity and the IoT can do for PLM implementations.
