Connected Technology Solutions spoke to Paul Haimes, VP Europe technical sales at PTC about the evolving role that PLM has in the digital transformation

How has the role of Product Lifecycle Management (PLM) evolved to help organisations cope with the increasingly complex engineering challenges of developing new products?

The main reason that PLM has had to quickly evolve from the old product data management days is to better reflect the needs of a globalised economy where the design anywhere, build anywhere approach is growing fast.

It was not an instant fix, but over time PLM was able to solve the issue. What it did not do at the time, however, was address the lifecycle of the product once it had left the manufacturer.

Industry 4.0, industrial Internet of Things (IIoT) and digital transformation gives us the ability to link together the three pillars of the product lifecycle – engineering/design and evolution, manufacture (the connected smart factory), and the concept of the connected product when it is out in customer use.

Blended with IIoT technology, PLM now manages the full lifecycle and does, as advertised, the cradle-to-grave process – or the cradle-to-cradle process we think of as part of the circular economy.

That is how PLM has evolved, and it will continue to develop in this direction to help organisations not just cope with the increasing complexity, but also to refine their product offerings and offer different ways to market. This could be the product as a service, or power by the hour – all of that is enabled by the idea of the three pillars of connected engineering, connected manufacture, and connected product.

 What are its key attributes and benefits in the modern, digitally connected enterprise?

When we consider the role of PLM in a digitally connected enterprise, we must consider it both in terms of the digital thread and several digital strands of information which make up the thread. It plays a significantly role in both… I will explain.

The digital thread within any company is made up of multiple threads of information – one of these is the product lifecycle ‘strand’, which includes connected manufacture and connected product.  You also have other business systems, such as MES, supply chain management, ERP – all of those also have a strand of data that forms part of the digital thread.

PLM’s ability to cover those three core building blocks of the digital thread, but also its ability to intertwine with those other digital strands, is fundamental. I see its key attributes being the ability to cover the full lifecycle, but to also integrate with other technologies.

To a certain extent, IIoT platforms, such as ThingWorx, can act as an integration capability, which makes that integration more possible. Software, like ThingWorx Flow, acts as a technology that pushes information to these other business systems with an event-based action.

These are the sort of things we see as key benefits to the connected vision that PTC offers.

 How does it interact with other software platforms such as CAD, ERP, MES, as well as IIoT platforms like ThingWorx?

A decade ago, we were talking about the integration bus layer or, in other words, how do we provide connectivity between these systems.

As we move forward, things are going to be a little more straightforward and, rather than building big heavy bridges, there is the potential to put up more lightweight integration structures, that are nonetheless valuable but easier to set up.

Restful services for example, as a mechanism to communicate between business systems, allows that integration to be built. Our technologies, like ThingWorx, are pushing the flow of codeless or low-code integrations.  We see a lot of interest in these types of technologies from the market and IIoT is partly responsible for making it possible.

 How does modern PLM software support the digital thread?

As I mentioned earlier, PLM is seen as the digital backbone. When we talk about a model-based enterprise and model-based definition, we are describing the ability for us to capture product or component specific information so that it is carried to downstream processes – whether that is product manufacturing information (PMI), quality information, supplier data or material data – all of which is valuable to stakeholders throughout the product lifecycle.

We also see that product information can extend far further than we first imagined. If we think about the role of PLM in the circular economy, what we see here is an ability to capture and carry information about how this component or part can be repurposed for a second or even third life.  Similarly, information on how the product can be remanufactured and what the recyclability options are for different materials is valuable for the downstream economy.

As we move from a cradle-to-grave approach from a cradle-to-cradle model, data on the reverse logistics of a product, and how a subassembly or individual parts will be given a new life, is likely to become a much sought-after commodity.

And as manufacturers transition from the traditional approach of selling their products towards offering their product as a service, where the customer is effectively leasing the product, the need for the digital backbone of information is even more critical. In these new business models, manufacturers rely on their ability to differentiate themselves with improved equipment uptime, less servicing and more accurate billing.  The connected product is a foundation capability for this to take place and relies on the seamless flow of digital information within the digital thread. In this, we see IIoT as a component of PLM which is fundamental for these types of use-cases.

 How can it help companies become more customer-centric?

The connected product is one of the best insights a company can have into how their product is being used by the customer. In my opinion, this is the richest form of information about what the customer requires, or more importantly, what it does not require.

I think manufacturers are often guilty of bringing an increasing amount of functionality and capability into their product in the belief that it is what the consumer wants. However, this is not necessarily reflected in their usage patterns.

Every piece of additional functionality must be designed, tested, maintained, costed, and replaced as a service item and, eventually, retired. Many of the features that you believe your customer wants could be eliminated and significant cost taken out of the design and manufacturing process.

When it comes to being more customer centric, we are seeing an increasing amount of Augmented Reality (AR) being used to make customer interaction easier. This starts in sales and marketing, where AR is being used to assist in the visualisation of the product – companies making everything from cars to luxury yachts rely on AR to illustrate how, in real time, their configured product will look to the customer.

The important thing here is your PLM environment understands the product configuration options and can then provide this information to the downstream processes.  If delivered correctly and with the right understanding, a company can become instantly more customer-centric using PLM to power the new AR technologies.

 How does it support and interact with AR tools? What are the benefits here?

Again, AR as a technology must be relevant to the task at hand – if you are not providing your AR user with a product specific experience that relates exactly to the product itself, then your strategy is going to struggle.

A parallel to draw here is the traditional instruction manual that is 300-pages thick, in all different languages, and with various models and configurations covering five or six products.

When you finally get to read the section, you are interested in, it reads: “If you have Model A this is relevant, if you have B or C this is relevant and, if you have D or E, you need to read this piece.” As a consumer, who on earth has the time to do all of this?

Customers and consumers expect a more tailored approach today – AR has the potential to offer experiences that are specific to the product in front of them, but it is PLM that is powering the capability.

 With sustainability and circularity climbing the agenda of manufacturing companies, how can it impact a product’s carbon footprint and end-of-life considerations?

Much of the carbon debt of a product is built up during the design phase. That is when decisions are taken by engineers about the materials they use and, often by association, the manufacturing processes that are going to be required.

Much like we do with cost or weight rollup, seen commonly in PLM systems today, the ability for us to manage carbon debt is going to be critical in helping engineers make more informed decisions about the materials they can use.

For example, what material substitutes are available with similar performance, but a lower carbon footprint? There are several dedicated websites that offer that service, showcasing alternatives that may provide a similar level of performance, but are less harmful to the environment.

There is still a lot of work required before we have a universally accepted understanding of what the carbon debt is for a particular process/material.  This will be different for each material supplier, and likely to be different depending on the country of origin.

For example, if you are procuring different types of steel, we should know how this steel was generated. If it was made in an electric arc furnace, this typically generates less carbon than a traditional basic oxygen furnace, so it is ultimately a better option.

The digital thread of information cannot just be around manufacturing tolerances and the quality of processes. As we have seen, it also needs to include much richer sources of information which feed a broader range of use-cases – such as the carbon product footprint. We are going to continue to see the expansion of PLM as the backbone of information within manufacturing industries – enabling the evolution of the digital thread.

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