Improve Production Efficiency and Predict Machine Tool Status using Markov Chain and Hidden Markov Model

Industrial intelligence is the most popular issue in the industry. Building models based on the different conditions of each algorithm can significantly increase production efficiency and reduce costs. On the other hand, Prevention of machine downtime is the most important part of industrial intelligence as well. This study believes that reducing downtime can improve efficiency and reduce costs. So we simulate this situation and predict base on different unit time by means of Markov chain as well as Hidden Markov Model. The Markov chain can show which idle reason may cause the machine to malfunction. In addition, Hidden Markov models can help managers arrange personnel and prevent potential failures based on past status sequences. Therefore, This study concludes the accuracy upper 86 percent, so the research can help the managers to make decision and improve production efficiency.