Enterprise Resource Planning (ERP) consultants play a vital role in customizing systems to meet specific business needs by processing large amounts of data and adapting functionalities. However, the process is resource-intensive, time-consuming, and requires continuous adjustments as business demands evolve. This research introduces a Self-Adaptive ERP Framework that automates customization using enterprise process models and system usage analysis. It leverages Artificial Intelligence (AI) & Natural Language Processing (NLP) for Petri nets to transform business processes into adaptable models, addressing both structural and functional matching. The framework, built using Design Science Research (DSR) and a Systematic Literature Review (SLR), reduces reliance on manual adjustments, improving ERP customization efficiency and accuracy while minimizing the need for consultants.

翻译：企业资源规划（ERP）顾问在处理大量数据和调整系统功能以满足特定业务需求方面发挥着关键作用。然而，该过程资源密集、耗时较长，且需随业务需求变化持续调整。本研究提出一种自适应性ERP框架，通过企业流程模型与系统使用分析实现定制化过程的自动化。该框架利用人工智能（AI）与自然语言处理（NLP）技术，将业务流程转化为基于Petri网的可适配模型，同时解决结构匹配与功能匹配问题。基于设计科学研究（DSR）与系统性文献综述（SLR）构建的该框架，降低了对人工调整的依赖，在提升ERP定制效率与准确性的同时，减少了对顾问资源的需求。