If you have been reading about systems engineering and the latest trends in the industry, you have no doubt come across the terms “PLM” and “digital thread.” These two phrases are overloaded terms and have slightly different meanings depending on your experience and your personal perspective in system development, production and manufacturing, and product lifecycle support. This article provides a discussion of these terms, providing historical background, how the terms are used today, and how they affect systems engineering.
Let’s start with the PLM acronym. PLM can mean either Product Line Management or Product Lifecycle Management. Product Line Management has its origin in the late 80s and early 90s. PLM was used at that time to describe the practice and individuals involved in managing a product line that had any number of variants and parts sourced from different origins that could be used in producing a final product. The focus of product line management occurred well after a product was designed and the first article assembled. The focus was on the enormous problem of managing parts and variants of the produced system. At first, this was accomplished with spreadsheets and databases. As computing technology matured in the 1990s, the practice matured and the ability to handle large amounts of data effectively increased.
In today’s context, PLM refers to Product Lifecycle Management, which has a meaning much grander than early usage. CIMdata, a leader in PLM education, research and strategic management consulting, defines PLM as a “strategic business approach that applies a consistent set of business solutions in support of creation, management, dissemination, and use of product definition information across the extended enterprise.”
The term Product Data Management (PDM) is used in today’s technical lexicon to refer to the management of the data alone and is a replacement for the earlier PLM term. The term Product Lifecycle Management (PLM) today takes on a larger meaning.
The current use of PLM carries with it the inclusion of system design information developed in the concept and development stages from ISO/IEC/IEEE 15288:2015. PLM also includes the information used in the production, utilization/support, and retirement stages of the lifecycle.
Commercial companies see tremendous value in extending the PDM solution to enable collaboration across business functions. A few areas where this can impact the business enterprise are: downstream data can have an impact on production facility construction, product cost is driven by individual part selection and sourcing, and long-lived product performance can have an impact on future design and manufacturing practices.
Effective PDM requires traceability from initial design (the kind of information we think of as system engineers residing in the MBSE solution) all the way through “As Built,” “As Delivered,” and “As Serviced” versions of the system.
This is where the term “digital engineering” becomes important. Digital engineering is generally thought of as an integrated digital approach that uses authoritative sources of system data and models as a continuum across disciplines to support lifecycle activities from concept through disposal. And, to accomplish this, we think in terms of a digital thread. However, the term “digital thread” can have two meanings.
Digital thread in the manufacturing environment refers to the ability to translate 2-D CAD drawings digitally (i.e. without human interpretation) to program CNC (computer numerical control) manufacturing machines and the control of manufacturing by computer-controlled manufacturing lines.
Taken in the larger context of product lifecycle management, a digital thread requires much more than the manufacturing information. A digital thread in the context of the lifecycle requires us to maintain design information together with manufacturing, logistics, maintenance and supportability, part number, variant and several other pieces of information.
With information connecting “end-to-end,” from initial design all the way through the lifecycle to disposal, we have the information needed to meet the enterprise goals to: identify the organizational value stream; increase business operational efficiency; improve current product performance; and incorporate lessons learned in future product development.
At this point, there two important points for us to recognize as systems engineers.
First, the practice of PLM includes the information we create in the concept and development stages. This is the area we focus on as systems engineers and involves developing the requirement, functional, physical, and verification architectures of a system. These are the domains we commonly consider in model-based system engineering (MBSE).
Second, the definition of PLM forces us to acknowledge our obligation to support the system (or product) in the production stage, through utilization and support, and finally in system retirement. As mentioned earlier, PLM uses information and data beyond system manufacture to influence how we design and build next version or generation systems.
Fundamentally, the system engineering discipline needs to think beyond MBSE and develop methods to connect to and support PLM and thereby the operation of the entire business enterprise in which we reside. PLM essentially defines the enterprise value stream. We need literally to connect to the greater PLM data and integrate with PLM information where it makes sense to do so.
In a related post, learn how a Vitech intern helped to improve product line management in Improving How Lawn Mowers are Made at John Deere.