Home / Current Issue / Paper 1705123
Automating Change Management Processes for Improved Efficiency in PLM Systems
Subject area: Science,Engineering and Technology · Area of research: PLM Systems
Abstract
Automation in change management processes plays a pivotal role in enhancing the efficiency of Product Lifecycle Management (PLM) systems. With the increasing complexity of product development, manual change management often leads to delays, errors, and communication gaps. Automated workflows streamline change requests, impact analysis, approvals, and implementation processes, ensuring faster decision-making and reducing human errors. By integrating automation with PLM systems, organizations can improve collaboration among stakeholders, maintain version control, and ensure that changes align with compliance requirements. The use of technologies such as Artificial Intelligence (AI) and Robotic Process Automation (RPA) enables predictive insights, automates repetitive tasks, and optimizes resource allocation. Automation also minimizes bottlenecks by providing real-time status updates and notifications, helping teams respond proactively to changes. Additionally, it ensures traceability and transparency throughout the change lifecycle, which is critical for audit readiness and compliance. This abstract highlights how automating change management fosters continuous improvement in PLM systems by reducing turnaround times, improving accuracy, and enhancing operational efficiency. It explores how automated change tracking and documentation reduce risks associated with product development and how seamless integration with ERP and supply chain systems ensures end-to-end visibility. Ultimately, automated change management contributes to better product quality, faster time-to-market, and improved customer satisfaction. The research aims to demonstrate how organizations can leverage automation to achieve agility, mitigate risks, and sustain innovation in an ever-evolving market landscape.
Keywords
Change management automation, Product Lifecycle Management (PLM), workflow optimization, AI in PLM, Robotic Process Automation (RPA), version control, compliance tracking, process efficiency, real-time collaboration, predictive insights, time-to-market improvement, operational agility, risk mitigation.
How to cite this paper
@article{1705123,
author = {Rafa Abdul, Aravind Ayyagari, Krishna Kishor Tirupati, Prof. (Dr) Sandeep Kumar, Prof. (Dr) MSR Prasad; Prof. (Dr) Sangeet Vashishtha},
title = {Automating Change Management Processes for Improved Efficiency in PLM Systems},
journal = {Iconic Research And Engineering Journals},
year = {2023},
volume = {7},
number = {3},
pages = {517-545},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1705123.pdf},
abstract = {Automation in change management processes plays a pivotal role in enhancing the efficiency of Product Lifecycle Management (PLM) systems. With the increasing complexity of product development, manual change management often leads to delays, errors, and communication gaps. Automated workflows streamline change requests, impact analysis, approvals, and implementation processes, ensuring faster decision-making and reducing human errors. By integrating automation with PLM systems, organizations can improve collaboration among stakeholders, maintain version control, and ensure that changes align with compliance requirements.
The use of technologies such as Artificial Intelligence (AI) and Robotic Process Automation (RPA) enables predictive insights, automates repetitive tasks, and optimizes resource allocation. Automation also minimizes bottlenecks by providing real-time status updates and notifications, helping teams respond proactively to changes. Additionally, it ensures traceability and transparency throughout the change lifecycle, which is critical for audit readiness and compliance.
This abstract highlights how automating change management fosters continuous improvement in PLM systems by reducing turnaround times, improving accuracy, and enhancing operational efficiency. It explores how automated change tracking and documentation reduce risks associated with product development and how seamless integration with ERP and supply chain systems ensures end-to-end visibility. Ultimately, automated change management contributes to better product quality, faster time-to-market, and improved customer satisfaction. The research aims to demonstrate how organizations can leverage automation to achieve agility, mitigate risks, and sustain innovation in an ever-evolving market landscape.},
keywords = {Change management automation, Product Lifecycle Management (PLM), workflow optimization, AI in PLM, Robotic Process Automation (RPA), version control, compliance tracking, process efficiency, real-time collaboration, predictive insights, time-to-market improvement, operational agility, risk mitigation.},
month = {September},
}