关键词: 单元化制造系统, 可靠性建模, 决策图, 故障树

Abstract: The manufacturing industry is undergoing rapid development and change in the modern era. As a result of the ongoing advancements in technology and the diversification of consumer demand, an increasing number of businesses are focusing on ways to increase production efficiency and lower costs, and enhance product quality. The cellular manufacturing system has garnered attention in this context because its remarkable flexibility and adaptability enable itself to promptly respond to changes in the market and client customized requirements. The equipment manufacturing business has made an extensive use of the cellular manufacturing system, which is a standard multi-variety and small-batch production organization with the manufacturing cell at its center. The cellular manufacturing system completes the production and processing tasks of equipment through the cooperation among different manufacturing cells, and its manufacturing cells or equipment can be regarded as the components of the cellular manufacturing system, which affects the completion of the system tasks. The cellular manufacturing system divides the factory into different areas, the same area has the same processing function, and different processing cells are placed in each area to perform related processing tasks, that is, the processing cells in the same area can be replaced by each other. As a result, the processing paths of the cellular manufacturing system are diverse, and the uncertain processing paths bring challenges to the reliability evaluation of the cellular manufacturing system. Its manufacturing cells or equipment can be regarded as the components of the cellular manufacturing system, which affects the completion of the system tasks. The cellular manufacturing system completes the production and processing tasks of equipment through the cooperation among different manufacturing cells. The factory is divided into distinct regions by the cellular manufacturing system, and each area has a single processing function. Various processing cells are positioned in each area to carry out related processing duties; in other words, the processing cells in the same area are replaceable. Because of this, the cellular manufacturing system has a variety of processing pathways, and the performance assessment of the system is complicated by the uncertain processing paths.
This study first examines the differences in the processing cell’s equipment deterioration process under various conditions: when equipment is not used for processing parts, its characteristics—which are limited to its life parameters and time—determine the equipment’s degradation process, which can be expressed as a continuous stable failure rate. Processing time, processing accuracy, and other factors influence the degree to which parts machining activities contribute to equipment deterioration during the machining process. The incremental failure rate may be used to characterize the degree of degradation resulting from these factors. So, the processing cell’s reliability function and cumulative failure function are determined, and the mixture failure rate model is developed. Subsequently, the various states that might occur inside the cellular manufacturing system are identified, and a performance assessment framework considering the variety of process routes is proposed to address the issue of the cellular manufacturing system’s complex reliability evaluation. The probability formulae of the system under various states are obtained in this procedure, which models the reliability of a specific processing task using multistate fault trees and multistate binary decision graphs. In order to remove the imbalanced efficiency loss and overproduction between operations, a genetic algorithm is utilized to select the process path that satisfies both the highest reliability of the system and the shortest job completion time. After obtaining the process path through genetic algorithm, the sampling approach is used to determine how the processing cell and equipment reliability vary over time. This allows for the evaluation of the probability of the manufacturing system in various stages. The feasibility of the method is demonstrated by the results of the case analysis, which obtain the probability of the system in various states as well as the dependability of the internal equipment and processing cell.
The analysis of the result of the case confirms that the number of machining equipment, processing time, machining parts and degradation parameters inside the processing cell all have an impact on the reliability of the processing cell. And when there are multiple types of the same parts between pieces of equipment, the failure of one processing cell will cause multiple equipment to be unable to complete production, and the risk of production plan failure can be reduced by analyzing the number of similar parts in different pieces of equipment and making adjustments. Finally, the correctness and effectiveness of the proposed method are verified by comparing the results with those based on simulation analysis. Compared with the learning cost of simulation software, the model evaluation has better practicability and convenience, and can provide support for the production management and real-time decision making of unitized manufacturing.

Key words: cellular manufacturing system, reliability modeling, decision diagram, fault tree