Influencing Factors of Machine Utilization Based on Industrial Internet of Things
The influencing factors of machine utilization in manufacturing companies have attracted more and more attention from scholars and practitioners. Based on the literature of intelligent manufacturing and industrial Internet of Things, this study monitors the accurate time of machine downtime by installing data acquisition modules on 11 gear hobbing machines in the same series, so as to reduce the influence of human factors. Synchronize the data to the computer host of the company’s management information system, so as to improve the real-time performance of production information. Taking the number of downtime caused by various main reasons as the independent variables and the machine utilization as the dependent variable, this study establishes a regression model, and uses multiple regression analysis to explore the relationship between the number of downtime and the machine utilization. The model was tested on 1120 sets of data collected continuously for 121 days. The survey results show that lack of manpower, personnel rest, machine setting and development of new products are the main reasons that affect the machine utilization, and reveal the influence of the various main factors on the machine utilization.