Throughput is one of the key performance indicators for manufacturing systems, and its improvement remains an interesting topic in both industrial and academic field. One way to achieve improvement is reducing downtime of unreliable machines. Along this direction, it is natural to pose questions about the optimal allocation of improvement effort to a set of machines and failure modes. This paper develops mixed integer linear programming models to improve system throughput by reducing downtime in the case of multistage serial lines. The models take samples of processing time, uptime and downtime as input, generated from random distributions or collected from real system. To improve computational efficiency while guaranteeing the exact optimality of the solution, algorithms based on Benders Decomposition and discrete event relationships of serial lines are proposed. Numerical cases show that the solution approach can significantly improve efficiency. The proposed modeling and algorithm is applied to throughput improvement of various systems, including a long line and a multi-failure system, and also to the downtime bottleneck detection problem. Comparison with state-of-the-art approaches shows the effectiveness of the approach. Supplementary materials are available for this article. Go to the publisher's online edition of IISE Transaction.

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With the recent development of the electrical vehicle (EV) industry, the study of manufacturing systems producing key components in this sector is becoming increasingly important. Multi-loop closed manufacturing systems (MCMS), whose operation and control are rarely studied in the literature, are widely used in the EV industry. This work provides innovative guidelines for MCMS operation also valid in a general context and not necessarily limited to the EV field. The main focus is on a specific topic of MCMS operation, namely the near flatness phenomenon. The near flatness indicates how system throughput is influenced by its population, i.e. the number of items circulating in the MCMS, especially in high-throughput conditions. The study of near flatness aims at enhancing MCMS flexibility in terms of population control and handling while guaranteeing high system throughput. In this work, a new indicator quantitatively describing the near flatness is provided. Numerical studies are conducted to analyze the effect of machine efficiency in isolation, mean times to repair, and buffer capacities on the near flatness. Experiments are also carried out on a real case of MCMS in the EV field. Based on the experimental results, practical specifications to improve MCMS design and management are provided.

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The hydraulic manifold block is designed by using virtual design method to provide the designer with a complete, image geometric model. Design process is simulated by using the method of physical modeling. Designers can directly see the results of design, the relationship between the observation holes and the assembly result on the virtual model. It reduces the labor of designers and increases the reliability of the calibration process. The programming method is carried out. Taking Visual Basic as the integrated development environment, the database as well as the macro recording and decompilation technology is used for the secondary development of Solid Works, in order to realize three-dimensional parametric design of the hydraulic manifold block.