Abstract
Abstract—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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
