International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 176 - Number 22 |
Year of Publication: 2020 |
Authors: Ali A. Majeed Ali, Osama Abdulhak M. Nasher, Ahmed Sultan Al-Hegami |
10.5120/ijca2020920234 |
Ali A. Majeed Ali, Osama Abdulhak M. Nasher, Ahmed Sultan Al-Hegami . A Framework for Total Quality Management of Diesel Generator Fuel Consumption using Machine Learning and Internet of Things (IoT). International Journal of Computer Applications. 176, 22 ( May 2020), 43-52. DOI=10.5120/ijca2020920234
Decision making on quantity of fuel consumption requirement is playing a very important role in industrial applications, for establishment of the production process which became more complicated and essential especially in Arab countries which have major shortage of fuel availability and price fluctuation and subsequently, Decision Making becomes very hard. Over the years, most of decisions were generated, based on personal experience which may not be effective due to many parameters such as level of experience of decision making and the state of the production system. Developing the ability to predict fuel consumption of Diesel Generator (DG) is extremely beneficial for improvement of generator performance, reducing operation and maintenance cost and avoiding fuel misuse; however, fuel consumption is measured by the amount of fuel used during a specific time period. In this paper, we propose a framework that makes use of IIOT technology to collect data in reliable manner and construct models based on mathematical and machine learning techniques to predict the optimum time and quantity of fuel. The proposed framework is implement and experimented with real datasets. The experimental results are promising.