Data underlying product lifecycle management (PLM) implementation remains problematic, engineers said at the recent CIMdata PLM Road Map conference. Presenters outlining their organizations’ plans and goals offered grim pictures of the data difficulties confronting them with PLM and nearly every other information management solution. Poor data quality in PLM and most every other piece of information technology (IT) is a stumbling block for digital transformation and Industry 4.0 – producing anything complex and connected (smart). It was no mystery why so many enterprise solution implementations and IT projects fall short.
Extracting reliable information from the data mess would greatly benefit organizational decision-making, speakers noted, as well as opportunity seeking, risk reduction, workforce reskilling, and uncovering problems. Fixing how data is handled and mishandled will take years and require a rethink of information life cycles in engineering, manufacturing, and the field.
Assurances that legacy product specifications and contract requirement data will remain available and accessible often prove untrue. While PLM generally handles new data well, the mess may still get worse.
Conference attendees noted problems with verification and validation, ownership conflicts, format incompatibilities, languages (digital and spoken), file fragmentation, missing data, vendor upgrade disruptions, circular references to previous versions of documents, cybersecurity questions, slow development of industry standards, and blockchains – all amid exploding data volumes from the Internet of Things (IoT).Printed circuit board
Bruce Mayer, manager of engineering application technology and strategy in Northrop Grumman’s Mission Systems sector, spoke on integrating smart documents (see sidebar, p. 35) in PLM and the digital thread. Implemented with PLM as part of model-based enterprise (MBE), smart documents can inform users about their contents. The problem is what Mayer calls “the document quagmire – large amounts of information, stacks and folders of specifications, information extraneous to task at hand, large amounts of cross referencing, and verifying the latest version.”
With work instructions for a printed circuit wiring board, for example, fabrication requirements and parts list run to 24 pages that reference 40 more documents. The board is supposed to be simple and rigid, yet specifications totaled 37 unique documents of client and industry standards.Corporate culture
Part of the information problem is cultural and organizational, such as whether users and managers are proactive or reactive, how they collaborate, and which information they share or keep.
Managing data means knowing where information is and that it is reliable – ensuring access amid rising physical and cyber security challenges, staffing skills, tech disruptions, and budgets.
Some digital technology has made managing information worse. With varying levels of frustration, customers send new types of data, demanding it be considered while offering no help in managing it.
The closed-door, experts-only approach to defining and engineering products is no longer good enough. CIMdata’s recent PLM Status and Trends Survey revealed that many companies appear to be stuck on PLM as product data management, and perhaps only CAD data management. Neither comes close to end-to-end management of information, product, and process life cycles.
Three common problems with implementations include trying to do too much too soon, failing to formulate and communicate a long-term vision, and promising benefits that are too broad and sweeping that they ignore frustrating details. Disruptors are opportunities, and PLM is a strategic approach, not just a business-unit tool.