A Hybrid Quality Control Strategy for Consumption Data on Petroleum, Oil and Lubricants by Oil Equipment

Abstract

Petroleum, oil and lubricants (POL) is critical to the functioning of oil equipment. It is very important to maintain the quality of POL consumption data of oil equipment. High-quality POL consumption data provide reliable datasets for computing the annual POL supply quota of oil equipment and improving the energy efficiency of such equipment. Based on the data analysis platform SPSS, this paper designs a hybrid quality control strategy called SEIB-K for POL consumption data of oil equipment, which couples the expectation-maximization algorithm with multiple imputations (EI), box plot (B), and kappa coefficient (K). The SEIB-K can systematically analyze the quality of actual POL consumption data, identify the missing items, abnormal items and contradictory items. Example analysis shows that our strategy could significantly improve the quality of POL consumption data. The research results provide a technical support for accurately determining the annual POL supply quota of oil equipment.