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Supervising the production process of equipment and ensuring its normal operation is an important responsibility of user supervision representatives, and also an important basis for guaranteeing the performance of equipment. Due to the numerous uncertainties in the production process, it is often difficult for supervision representatives to make accurate and objective quality assessment of it. In order to improve the precision of the quality assessment of the equipment production process and strengthen the quality supervision of the production process, firstly, the quality assessment indexes are constructed by objectively analyzing the problematic scenarios and problematic factors, and the two dimensions of the self-inspection conformity of the contracting unit and the inspection satisfaction of the supervisory representative are taken as the basic variables for assessing the indexes according to the definition of the quality supervision of the production process. Decision laboratory method and entropy weight method are used to determine the subjective and objective weights of the indicators respectively, and the concept of distance function is introduced to finalize the combined weights of indicators at all levels. The cloud eigenvalue is obtained through expert judgment calculation to establish a two-dimensional cloud model, the two-dimensional cloud map is drawn to determine the quality level initially, and the proximity is calculated to determine the results accurately. A certain military diesel engine assembly process is analyzed as an example, which meets the requirements of comprehensive and objective assessment of the quality of diesel engine assembly process and verifies the effectiveness and feasibility of the proposed method.