The benefits of Product Lifecycle Management (PLM) have been noted for improving business, creating collaboration, and reducing energy and time by making transcendent decisions through the process of product life cycle. This work aims to propose a PLM Components Maturity Assessment (PCMA) model to gain comprehensive maturity results and reduce the complexity in obtaining maturity scores. According to PLM functionalities, we divide PLM into fifteen components. PLM components can be cataloged into five main fields: ‘TechnoWare’, ‘InforWare’, ‘FunctionWare’, ‘OrgaWare’, and ‘SustainWare’ (TIFOS Framework). With PCMA model we analyzed PLM components and proposed mature content of each dimension, obtaining specific key performance indicators for each dimension. This work has been also useful to solve decision-making issues based on AHP methodology, such as: selecting the optimal PLM components in TIFOS Framework, obtaining the components ranking weight, getting components maturity score, and comparing it with the actual situation to give constructive business suggestions. These business suggestions include strengths and weakness of PLM components and conducting selection of PLM components. Experimental studies have been conducted to verify maturity scores for each component and to achieve component-ranking weights
PLM Components Selection Based on a Maturity Assessment and AHP Methodology
Savino M;
2013-01-01
Abstract
The benefits of Product Lifecycle Management (PLM) have been noted for improving business, creating collaboration, and reducing energy and time by making transcendent decisions through the process of product life cycle. This work aims to propose a PLM Components Maturity Assessment (PCMA) model to gain comprehensive maturity results and reduce the complexity in obtaining maturity scores. According to PLM functionalities, we divide PLM into fifteen components. PLM components can be cataloged into five main fields: ‘TechnoWare’, ‘InforWare’, ‘FunctionWare’, ‘OrgaWare’, and ‘SustainWare’ (TIFOS Framework). With PCMA model we analyzed PLM components and proposed mature content of each dimension, obtaining specific key performance indicators for each dimension. This work has been also useful to solve decision-making issues based on AHP methodology, such as: selecting the optimal PLM components in TIFOS Framework, obtaining the components ranking weight, getting components maturity score, and comparing it with the actual situation to give constructive business suggestions. These business suggestions include strengths and weakness of PLM components and conducting selection of PLM components. Experimental studies have been conducted to verify maturity scores for each component and to achieve component-ranking weightsFile | Dimensione | Formato | |
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