Improving root cause analysis through the integration of PLM systems with cross supply chain maintenance data

Abstract

A B S T R A C TThe purpose of this paper is to demonstrate a system architecture for integrating Product Lifecycle Management (PLM) systems with cross supply chain maintenance information to support root-cause analysis. By integrating product-data from PLM systems with warranty claims, vehicle diagnostics and technical publications, engineers were able to improve the root-cause analysis and close the information gaps. Data collection was achieved via in-depth semi-structured interviews and workshops with experts from the automotive sector. Unified Modelling Language (UML) diagrams were used to design the system architecture proposed. A user scenario is also presented to demonstrate the functionality of the system.

Improving Supply Chain Human-Machine Systems by the Analysis of Departmental-Level User Characteristics

“…The contribution of Madenas et al (2016) is to demonstrate a system architecture for integrating product lifecycle management (PLM) systems with cross-supply chain maintenance information to support root cause analysis. By integrating product data from PLM systems with warranty claims, vehicle diagnostics, and technical publications, engineers were able to improve the root cause analysis and close the information gaps (Madenas et al, 2016). The contribution of Behnake and Janssen ( 2020) is to identify boundary conditions for sharing assurance information to improve traceability.…”

“…Based on an extensive content analysis of academic and trade literature, including websites and documents of vendors and users of the technologies, Musa et al (2014) capture, analyze, compare, and contrast the design choices, essence, results, and current and potential future impacts of some recent developments. The contribution of Madenas et al (2016) is to demonstrate a system architecture for integrating product lifecycle management (PLM) systems with cross-supply chain maintenance information to support root cause analysis. By integrating product data from PLM systems with warranty claims, vehicle diagnostics, and technical publications, engineers were able to improve the root cause analysis and close the information gaps (Madenas et al, 2016).…”

Adoption of product lifecycle management in new product development: a case study of automotive organisation

“…Reusing, modifying, translating product data generated through CAD/CAM/CAE platforms by using neutral formats such as STEP/XML has already been explored and would be beneficial for practitioners seeking application of this (Chiang and Trappey, 2007; Nosenzo et al , 2014). Integration of PLM with other enterprise-level systems is also important to consider since there are multiple applications in an organization working towards overall organizational benefit (Ming et al , 2008, Demoly et al , 2013, Wiesner et al , 2015; Lv et al , 2016; Madenas et al , 2016; Sodhro et al , 2018). The integration efforts extended to requirement management have also been expanded to identify with existing RM techniques (Daniels et al , 2013; Violante et al , 2008) and provided a PLM based approach for the same purpose is established through PLM, leading to the inclusion of this domain within PLM (Violante and Vezzetti, 2014; Papinniemi et al ., 2014).…”

“…It is also important to understand that the complete spectrum of manufacturing could not be completed without involving the activities at the supplier ends. Thus, the involvement of suppliers has been investigated in a PLM integrated system (Madenas et al , 2016). The next phase, which is addressed by PLM research, is an important domain of product service-related activities.…”

A structured approach to defect data management for improving DFM implementation in aerospace manufacturing

“…For example, Goh [14] emphasised the importance of feeding back manufacturing knowledge to improve the design and engineering capability in the aerospace industry, yet the work envisaged an organisational strategy toward improving the knowledge feedback cycle with less emphasis on how organising and structuring data can further enable a higher impact of such strategies. Madenas et al [15] recognised the benefits of analysing data held at the supplier's knowledge base, and the way to identify and integrate it within PLM systems for the purpose of root cause identification. Chaime [16] recognised the effects of defects on quality management from made (in-house) and supplied parts.…”