Abstract

<p>The aim of this research is to apply machine learning techniques to the reconfiguration of automated manufacturing system, the <br>objective is to provide a model for fast decision making in automation processes in the manufacturing industry, to use the dataset <br>in product reconfiguration to predict a product, to design an intelligent model that could provide an easy and faster <br>reconfiguration of products in a manufacturing industry. The motivation towards this work is caused by the high rate of delay<br>in the production processes caused by the disturbance, taking proper corrective actions to complete the production orders on <br>time and to minimize the impact of the disturbances. Humans can break down during product production leading to reduction <br>and delay in product production, there is need for an intelligent model that does not require human effort, the model would be <br>able to take decision, automate processes and facilitate production processes. The data which is on the production of semiconductors in an industry will be analyzed with R and R-Studio platform sourced from UCI machine learning repository. The <br>methodology adopted in this project was SEMMA which stands for Sample Explore Modify Model Access which focuses on the <br>main modeling tasks in the project without venturing into the business understanding and deployment according to oreilly.com. <br>The expected result after the experiment is to develop an intelligent model for the reconfiguration of product in a manufacturing <br>company and also facilitate production and decision making in the company using the dataset on the production of semiconductor as a use case.</p>