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Throughout the past few years, there has been notable research effort directed towards developing automated knowledge acquisition (KA) in order to automate knowledge acquisition in Supply Chain Management (SCM) applications. Several methods utilized for the automation of supply chain management involved Intelligent Agent (IA) and Case-Based Reasoning (CBR). This paper used both approaches to bring about automated knowledge acquisition in order to assist decision-making in SCM applications. With the arrival of a new case, prior cases are retrieved from the database and the potential solutions are laid down. After the completion of acquisition, case and solution outcome are analyzed and evaluated according to function similarity. Finally, after evaluating the new case along with the problem details and the chosen solution, the case is retained in the database for issues that will arise in future applications.