Optimization of dynamic sequential test strategy for equipment health management

Testing is the premise and foundation of realizing equipment health management （EHM）. To address the problem that the static periodic test strategy may cause deficient test or excessive test, a dynamic sequential test strategy （DSTS） for EHM is presented. Considering the situation that equipment health state is not completely observable in reality, a DSTS optimization method based on partially observable semi-Markov decision pro- cess （POSMDP） is proposed. Firstly, an equipment health state degradation model is constructed by Markov process, and the control limit maintenance policy is also introduced. Secondly, POSMDP is formulated in great detail. And then, POSMDP is converted to completely observable belief semi-Markov decision process （BSMDP） through belief state. The optimal equation and the corresponding optimal DSTS, which minimize the long-run ex- pected average cost per unit time, are obtained with BSMDP. The results of application in complex equipment show that the proposed DSTS is feasible and effective.

Sequential multidisciplinary minimally invasive therapeutic strategy for heart failure caused by four diseases: A case report

BACKGROUND The coexistence with patent ductus arteriosus(PDA),mitral valve prolapse(MVP),atrial fibrillation(AF)and hyperthyroidism is extremely rare and complex.The optimal therapeutic strategy is difficult to develop.CASE SUMMARY A 27-year-old female with PDA,MVP,AF and hyperthyroidism presented with severe dyspnea.Given that a one-stage operation for PDA,MVP and AF is high risk,we preferred a sequential multidisciplinary minimally invasive therapeutic strategy.First,PDA transcatheter closure was performed.Hyperthyroidism and heart failure were simultaneously controlled via medical treatment.Video-assisted thoracoscopic mitral valve repair and left atrial appendage occlusion were performed when heart failure was controlled.Under this therapeutic strategy,the patient’s sinus rhythm was restored and maintained.Two years after the treatment,the symptoms of heart failure were relieved,and the enlarged heart was reversed.CONCLUSION Sequential multidisciplinary therapeutic strategies,which take advantage of both internal medicine and surgical approaches,might be reasonable for this type of disease.

Revenue-sharing contract to coordinate independent participants within the supply chain

To improve the performance of the supply chain with one supplier and multiple retailers under deterministic price-sensitive customer demand, an optimal strategy is proposed based on knowledge discovery. First the decentralized system in which the supplier and the retailers are independent, profit-maximizing participants with the supplier acting as a Stackelberg game leader is studied. Numerical examples illustrate the importance of the coordination. The conventional quantity discount mechanism needs to be modified to coordinate the supply chain, so a revenue-sharing contract is proposed to coordinate such supply chain. Lastly, a special decision under certain demand rates is studied. The pricing and replenishment policies can be decided sequentially, which yields much less loss comparing with optimal decision when the demand rates are sufficiently large.

Design and Analysis of Computer Experiments - An Application to a Complex Industrial Component

Since the formal introduction of computer experiments back in 1989, substantial work has been done to make these experiments as efficient and effective as possible. As a consequence, more and more industrial studies are performed. In this direction, sequential strategies have been introduced with the aim of reducing the experimental effort while keeping the required accuracy of the meta-model. The strategies consist in building a fairly accurate meta-model based on a low number of experimental points, and then adding new points in an iterative way according to some strategy like improving the accuracy of meta-model itself or finding the optimal design point in the design space. In this work, a hybrid of these two strategies is used, with the aim to achieve both meta-model accuracy and optimum design solution while keeping low the experimental effort. The proposed methodology is applied to an industrial case study. The pragmatism of such hybrid strategy, together with simplicity of implementation promotes the generalization of this approach to other industrial experiments.

Multidisciplinary co-design optimization of structural and control parameters for bucket wheel reclaimer

Bucket wheel reclaimer(BWR)is an extremely complex engineering machine that involves multiple disciplines,such as structure,dynamics,and electromechanics.The conventional design strategy,namely,sequential strategy,is structural design followed by control optimization.However,the global optimal solution is difficult to achieve because of the discoordination of structural and control parameters.The co-design strategy is explored to address the aforementioned problem by combining the structural and control system design based on simultaneous dynamic optimization approach.The radial basis function model is applied for the planning of the rotation speed considering the relationships of subsystems to minimize the energy consumption per volume.Co-design strategy is implemented to resolve the optimization problem,and numerical results are compared with those of sequential strategy.The dynamic response of the BWR is also analyzed with different optimization strategies to evaluate the advantages of the strategies.Results indicate that co-design strategy not only can reduce the energy consumption of the BWR but also can achieve a smaller vibration amplitude than the sequential strategy.