Model-Based Definition: The Death of the Drawing

Lionel Grealou CAx, PLM Leave a Comment

Image credit: Verisurf Software

Rapid changes in technologies and IT solutions provide opportunities for increased adaptability and flexibility in terms of enabling or sustaining competitive advantage. Manufacturers, OEMs and Tier 1-2 suppliers spend millions of dollars in implementing and maintaining their Product Life-cycle Management (PLM) ecosystem; they need to identify the appropriate adoption, change and continuous improvement strategies to control their PLM return-on-investment (ROI).

Recently, CIMdata brought the concept of ‘PLM platformization‘ to illustrate and explain how PLM is to address complexity and proactively adapt to (or lead against?) the constant change in the external environment. This supports the idea that PLM is becoming broader and deeper than ever in scope, with its boundaries reaching out to ERP, MES and other enterprise domains across the entire Product Realization (above and beyond the traditional world of Engineering where PDM has been – and still is – predominant).

Some argue that ‘full PLM‘ has not been done before as most organization refer to it as ‘PDM‘ as most PLM discussions in the traditional industries (automotive, aerospace and defense) are around CAD and BoM. Actually, as introduced in a previous post, ‘the reluctant engineer‘, most manufacturing organization already ‘does PLM‘ – even if it is done on the back of an envelop, if they don’t formally use PLM tools, or perhaps simply don’t call it PLM.

Others already leverage PLM tools and technologies in a more or less effective and efficient manner. The concept of ‘platformization of PLM‘ is to bring structure and essential core competencies to the product realization process in 15 key points (in no particular order):

  1. Covering the entire product realization life-cycle.
  2. Reaching across all business functions or silos (holistic implementation and adoption), not just engineering and manufacturing.
  3. Focusing on business ROI, not just resource efficiency; but, looking into the business case for growth and business expansion.
  4. Providing data access to all business functions – as relevant (security, on the cloud, from a mobile device, etc.)
  5. Becoming an open platform for collaboration, data sharing and knowledge optimization – enabling value co-creation.
  6. Providing a simple platform to deal with complexity (making sense of big data, complex and changing requirements, regulation constraints, etc.)
  7. Supporting the circular economy, data reuse, learning, etc.
  8. Introducing new support and maintenance models (beyond the traditional IT models as PLM is not just an IT platform, but a business ‘operating model‘).
  9. Providing plug and play‘ capacity and capability.
  10. Leveraging social collaboration, information and knowledge exchange.
  11. Being agile – enhancing the New Product Introduction (NPI) process.
  12. Managing IP, creativity and innovation (based on knowledge and information management).
  13. Leveraging and adopting new technologies – in a timely manner, within their S-curve of adoption and their life-cycle, in a controlled environment (in terms of customization).
  14. Defining, adopting and making available the relevant (selected) standards.
  15. Going beyond the scope of PDM into other functions, technical and non-technical domains – where most business benefits can be realized from PLM (e.g. material life-cycle management, weight management, cost management, etc.)

Some (OEMs but also large Tier 1) manufacturers are contributing to pushing the boundaries of PLM toward global integration or multiple PLM platforms using integration standards. Managing the cost of ownership includes managing cross-PLM platform integration and PLM-ERP / PLM-MES integration, rather than ‘simply‘ looking after single PLM platform customization…

What are your thoughts?


Reference:


This post was originally published on LinkedIn on 30 October 2015.