English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

—Right PLM components selection and investments increase business advantages. This paper develops a PLM components monitoring framework to assess and guide PLM implementation in small and middle enterprises (SMEs). The framework builds upon PLM maturity models and decision-making methodology. PLM maturity model has the capability to analyze PLM functionalities and evaluate PLM components. A proposed PLM components maturity assessment (PCMA) model can obtain general maturity levels of PLM components based on key performance indicators. Investment decisions should be made from the relatively weaker PLM components based on the results of PCMA. One developed method of the fuzzy analytical hierarchy process (Fuzzy AHP) is applied to extract the premier improvement component needed. The results of a first empirical assessment in a swimming industry are presented, which could be used as benchmark data for the other Small and Medium sized Enterprises (SMEs) to develop their own PLM components monitoring framework to increase the success of their PLM implementation.

A PLM components monitoring framework for SMEs based on a PLM maturity model and FAHP methodology