Strategic decision making for production line configuration in Digital Twin

Modular product design for a product family strategy is a dominant mass customization methodology and impacts production line configuration. Common modules shared across product families, generations even the entire product platform, have a different lifecycle, which caused ever-changing market d...

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Bibliographic Details
Main Author: Kim, Yerim
Other Authors: Moon Seung Ki
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/160784
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Institution: Nanyang Technological University
Language: English
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Summary:Modular product design for a product family strategy is a dominant mass customization methodology and impacts production line configuration. Common modules shared across product families, generations even the entire product platform, have a different lifecycle, which caused ever-changing market demands. So, the modules should be differentiated and redesigned based on the product development plan and market demands. Thus, a production line must be also designed to quickly respond to product change requirements while production volume flexibility is secured. Therefore, this research presents a decision-making process to determine strategic production line configuration by integrating the concept of product development and product lifecycle. On the other hand, a framework is proposed to develop a Digital-Twins (DT) driven decision support system for the production line selection the production line configuration and the product lifecycle. DT is a promising product lifecycle management (PLM) enabler that controls, analyses, and processes all product-related data throughout the entire enterprise. To develop the decision-making process for the line configuration, a hybrid multi-attribute decision-making (MADM) method is used to evaluate and compare feasible production line configuration scenarios in terms of production efficiency, economic production, and flexibility. This research shows the effectiveness of DT-driven decision-making in the manufacturing context when adjusting the production plan according to the product lifecycle information associated with a product platform and a modularity strategy.