We’ve all heard the buzzwords: digital transformation, product lifecycle, product data, PLM, PDM, systems engineering, models-based engineering and so on. It can be confusing, trying to figure out which technology or trend will have the biggest impact on the business. It’s also easy to imagine you’re missing out on a new, hot trend. But before we worry about whether we’re ahead of the curve or behind it, let’s be clear exactly what we’re talking about.
Product Lifecycle Management (PLM) as a term has been around since the 1950s—it is not a new concept, but recently, more organizations are looking at this process as a place for improvement. A product lifecycle is simply the stages a product goes through from the initial concept to end of life—whether that’s a complex manufactured product like a rocket or a simpler product such as a house or a winter coat.
Product lifecycle management is the set of processes and/or procedures used to manage all of the product’s information throughout the lifecycle—from inception and planning; to design, engineering, and manufacture; to service and disposal.
At Adaptive, we have defined the product lifecycle to start with the digital design process and continues into the physical side of manufacturing for prototyping, testing, first article inspection, and quality control.
But what about product data management (PDM)? Where does that fit?
As the words imply, PDM involves managing the information about a product, from models and drawings to bills of materials (BOMs) and more. But PDM shouldn’t be equated with PLM. PDM is about the data involved in managing all the data around the development of a product – product specifications, version control and more. PLM calls on the data in PDM to manage the entire digital design process.
Systems engineering is also sometimes confused with PLM, but that focuses on how to design and manage systems (which almost always include products). It’s the overall organization and oversight of a system, as well as the people and processes that ensure all aspects of a system are considered and integrated into a whole. PLM, which focuses on everything about the product, can sometimes help automate design processes related to systems engineering. But generally speaking, systems engineering has a broader scope, as it also includes the coordination of teams, logistics, and other responsibilities outside of the product stream.
Models-based Systems Engineering
Within systems engineering is the concept of models-based system engineering (MBSE). MBSE establishes a “model” to analyze and document key aspects of the systems engineering life cycle which includes system requirements, analysis, design, and validation and verification activities. Similar to a PLM, it is intended to improve communications within engineering teams and other stakeholders, it provides early identification of requirements issues, improves specification of allocated requirements to hardware and software resulting in fewer errors during integration and testing and provides requirements traceability, reduces project risks and lowers costs, and more.
The idea behind digital transformation is to establish a process for organizations to track the entire cross-functional cycle of product development capturing and integrating key data points to establish traceability and manage how a product is conceived, created, tested, and brought to market. In essence, the data trail creates a “digital thread” that captures the evolution of that product. Of course, this doesn’t happen all at once and needs to be taken in discrete steps that build success upon success. In some cases a digital thread will extend beyond the walls into the supply chain, this is the ultimate nirvana. However, many organizations are not quite ready for that just yet and it is more talk than anything. However, the concept of establishing a digital thread goes hand in hand with PLM and systems engineering strategies. The transformation part happens when there is a more collaborative approach in an organization when everyone is working off the same data and making better business decisions. We will be writing more on this topic later.
As you can see, product development covers a broad spectrum in an enterprise as it tends to touch many functional departments as work gets completed across an organization. In some cases a business problem on the surface may not “appear” to be a PLM issue, but in many cases due to collaboration needs, managing product changes, and tracking all documentation it quickly becomes something a PLM strategy can affect.
Stay tuned for our next post where we will dive a little deeper into Understanding PLM Fundamentals…