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2024
Journal Article
Title
Semantic Integration and Interdisciplinary Collaboration in Production Planning
Title Supplement
A Graph-Based Approach for Enhanced Data Consistency
Abstract
Based on increasing individualization, shorter innovation cycles and integrating services into products complexity in the development of products and production processes increases. In combination with digitalization, this results in an increased need for interdisciplinary work. A high level of data consistency is required to cope with the resulting diverse and complex data structures, leading to the need for a consistent data model that orchestrates information flows. PLM-systems fall short in their ambition of reaching an overarching data management across the product lifecycle. This results in a lot of administrative work in planning instead of value-adding as well as in inconsistencies and incomplete change processes. To improve interdisciplinary collaboration in production planning, goal of this work is to develop a method leading to a comprehensive data model and to show it’s applicability by means of a case study. The steps of the research performed follow the typical circle of action research: diagnosis, planning, action, evaluation, and reflection. The data model resulting of the application of the method uses semantics to make relationships understandable for both humans and machines. This is necessary for downstream automation and the use of artificial intelligence. The three essential steps of the method are, firstly, an as-is modeling of the processes of interest. Then, the process models are used to evaluate the consistency and efficiency of the planning processes. The method is completed by a guideline for setting up the data model. The proposed approach aims to improve efficiency and quality in assembly planning processes, resulting in its importance for industrial companies.
Author(s)
Conference
Conference on Manufacturing Systems 2024
Open Access
Rights
CC BY-NC-ND 4.0: Creative Commons Attribution-NonCommercial-NoDerivatives
Language
English