Joint optimization of LORA and spares stocks considering corrective maintenance time

Level of repair analysis（LORA） is an important method of maintenance decision for establishing systems of operation and maintenance in the equipment development period. Currently, the research on equipment of repair level focuses on economic analysis models which are used to optimize costs and rarely considers the maintenance time required by the implementation of the maintenance program. In fact, as to the system requiring high mission complete success, the maintenance time is an important factor which has a great influence on the availability of equipment systems. Considering the relationship between the maintenance time and the spares stocks level, it is obvious that there are contradictions between the maintenance time and the cost. In order to balance these two factors, it is necessary to build an optimization LORA model. To this end, the maintenance time representing performance characteristic is introduced, and on the basis of spares stocks which is traditionally regarded as a decision variable, a decision variable of repair level is added, and a multi-echelon multiindenture（MEMI） optimization LORA model is built which takes the best cost-effectiveness ratio as the criterion, the expected number of backorder（EBO） as the objective function and the cost as the constraint. Besides, the paper designs a convex programming algorithm of multi-variable for the optimization model, provides solutions to the non-convex objective function and methods for improving the efficiency of the algorithm. The method provided in this paper is proved to be credible and effective according to the numerical example and the simulation result.

Mission-oriented dynamic optimization model of carrying spares for warship redundant system

Redundancy is a common structure for warship system,and it is an effective way to improve the reliability of the system.In this paper, warship system is taken as the object of study,based on the system reliability equivalence principle, a spares demand rate calculation method for redundant system is proposed through structure transformation. According to the system analysis method, the general modeling data structure of spares support echelon and system indenture is established, and the mission success probability is taken as the optimization target to build the dynamic optimization model of carrying spares during the process of multi-phase. By introducing the Lagrange multiplier, the spares weight, volume and cost are transformed to the single target of the spares total scale, and the initial Lagrange factors and its dynamic adjustment policy is proposed. In a given example, the main influence factors of the carrying spares project are analyzed, and the study results are in accordance with the reality, which can provide a new approach to mission-oriented carrying spares optimization for the redundant system.

Mission-Oriented Configuration Model of Aircraft Carrying Spares and Dynamic Optimization Policy

Spare parts are critical to scheduled maintenance and fault repair,and can directly affect the readiness and combat capability of equipment.Equipment′s capacity of carrying spares is influenced by its storage space and scales,so it is necessary to consider economic factors,e.g.spares cost,as well as non-economic ones,such as spares volume,mass and scale,when optimizing spares configuration.Aiming at this problem,the optimization model based on multi-constraints for carrying spares is built by METRIC theory and system analysis.Through the introduction of Lagrange factors,the spares cost is transformed to shadow price,and the optimization method for carrying spares and the dynamic adjustment policy of Lagrange factors are proposed.The result of a given example is analyzed,and demonstrates that the proposed model can be optimized with all constraints,and the research can provide a new way for carrying spares optimization.

An Optimal Replacement Policy for a System with Finite Spares

This paper develops a new replacement policy for a system with multiple spare units.An optimal replacement period is determined by maximizing the mean time to failure of the system.We show that there exists a finite and unique optimal replacement period T for units with strictly increasing failure rates. We also proof that the optimal repIacement period for a system with spares is decreasing in k. Furthermore, an algorithm is presented to get the optimal replacement period and a numerical example is given to illustrate the result. with strictly

New Approach to Calculate the Unavailability of Identical Spares in Cold Spare Configuration

Cold spare is the most common configuration amongst the three types of configuration for systems used on board and for power generation systems. A new approach to calculate the unavailability of systems composed of identical spares in cold spare configuration was proposed in this study. Instead of using the spare gate of dynamic fault tree( DFT) and the Markov analysis,AND gate of static fault tree used for calculating the unavailability of cold spare systems was proposed in this paper. By using this approach,unavailability of identical cold spare systems composed of nonrepairable spare components can be calculated exactly and systems composed of both repairable and nonreparable identical spare components can be estimated without building large Markov state diagram.

Study to Cost of Air Spares Support Based on IPSO

Air spares support is general term of using and repairing of aircrafts which is the material foundation of aero technical support, its effectiveness influences operational effectiveness and equipments of aircrafts directly. Based on particle swarm optimization algorithm, a new model is proposed to optimize the distribution of the cost of air spares, it take the funds as resource and the improvement of performance efficiency as objective and deduces the expressions to get the best distribution plan. The results of experiments indicate that this model can make full use of the limited funds and obtain the highest efficiency of air spares support.

Epigenetic combined with transcriptomic analysis of the m6A methylome after spared nerve injury-induced neuropathic pain in mice

Epigenetic changes in the spinal cord play a key role in the initiation and maintenance of nerve injury-induced neuro pathic pain.N6-methyladenosine(m6A)is one of the most abundant internal RNA modifications and plays an essential function in gene regulation in many diseases.However,the global m6A modification status of mRNA in the spinal cord at different stages after neuropathic pain is unknown.In this study,we established a neuropathic pain model in mice by preserving the complete sural nerve and only damaging the common peroneal nerve.High-throughput methylated RNA immunoprecipitation sequencing res ults showed that after spared nerve injury,there were 55 m6A methylated and diffe rentially expressed genes in the spinal cord.Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway results showed that m6A modification triggered inflammatory responses and apoptotic processes in the early stages after spared nerve injury.Over time,the diffe rential gene function at postoperative day 7 was enriched in "positive regulation of neurogenesis" and "positive regulation of neural precursor cell prolife ration." These functions suggested that altered synaptic morphological plasticity was a turning point in neuropathic pain formation and maintenance.Results at postoperative day 14 suggested that the persistence of neuropathic pain might be from lipid metabolic processes,such as "very-low-density lipoprotein particle clearance," "negative regulation of choleste rol transport" and "membrane lipid catabolic process." We detected the expression of m6A enzymes and found elevated mRNA expression of Ythdf2 and Ythdf3 after spared nerve injury modeling.We speculate that m6A reader enzymes also have an important role in neuropathic pain.These results provide a global landscape of mRNA m6A modifications in the spinal cord in the spared nerve injury model at diffe rent stages after injury.

Confidence Level of System Spares OptimizationUsing Fuzzy Theory

To obtain a higher readiness for a complex system, the common method is to store some spares. Confidence level of system spares is an important parameter to control the probability of the spares required. By introducing fuzzy theory, this paper allocates the confidence level of system spares to its subsystems, thus to achieve a rational management of system spares,

A Bound Heuristic Technique for Solving DRAMA Spares Optimizations

This paper studies the solution technique to solve the DRAMA spares allocation optimization problem. DRAMA model is an analytic spare optimization model of a multi-item, multi-location, and two-echelon inventory system. The computation of its system spares availability is much complicated. The objective function and constraint functions of DRAMA model could be written as the separable forms. A new bound heuristic algorithm has been presented by improving the bound heuristic algorithm for solving the reliability redundancy optimization problem (BHA in short). With the results, the proposed algorithm has been found to be more economical and effective than BHA to obtain the solutions of large DRAMA model. The new algorithm could be used to solve reliability redundancy optimization problems with the separable forms.

Dynamic Prediction Method for Valuable Spare Parts Demand in Weaponry Equipment Based on Data Perception

Missile is an important weapon system of the army.The spare parts of missile equipment are significant effect on military operations.In order to improve the mission completion rate of missile equipment in wartime,this paper introduces data sensing method to forecast the demand of valuable spare parts of missile equipment dynamically.Firstly,the information related to valuable spare parts of missile equipment was obtained by data sensing,and the sample size was determined by Bernoulli uniform sampling probability.Secondly,according to the data quality of multi-source and multi-modal,the data requirement for dynamic demand prediction of valuable spare parts of missile equipment was obtained.Finally,according to the characteristics of the spare parts,the life of the spare parts was predicted,realizing the dynamic prediction of the demand for valuable spare parts of missile equipment.The results show that the demand of valuable spare parts of missile equipment can be predicted dynamically by using this method,the accuracy is higher than 95%,and the real-time performance is more excellent.

显微镜下保留睾丸的睾丸良性肿瘤切除术临床疗效分析(附16例报道)

目的:探讨显微外科手术技术应用于保留睾丸的睾丸良性肿瘤切除术的安全性及临床疗效。方法:回顾性分析2020年10月至2023年2月青岛大学附属医院男科收治的16例睾丸肿瘤患者的病例资料。患者中位年龄23岁,睾丸肿瘤均为单侧,左侧7例,右侧9例,睾丸肿瘤最长径1.0~3.5 cm(中位数1.85 cm)。患者均在术前完善阴囊彩超(CDFI)、磁共振(MRI)、精液、血清睾酮、甲胎蛋白(AFP)、人绒毛膜促性腺激素(hCG)、乳酸脱氢酶(LDH)检查。16例患者均行显微镜下保留睾丸的睾丸肿瘤切除术(TSMS),术中运用显微外科技术,精准辨别睾丸内肿瘤与正常睾丸组织的边界,距离肿瘤边界约2 mm完整切除肿瘤及少部分邻近正常睾丸组织,使用显微双极电凝镊给予精确止血,最大限度保留正常睾丸组织。将完整切除的睾丸内肿瘤及邻近正常睾丸组织进行快速冰冻病理检查。术后定期复查CDFI、MRI、精液、血清睾酮等项目。结果:16例患者术前血清睾酮、AFP、hCG、LDH及精液检查指标均在正常参考值范围内。所有16例患者的术中快速冰冻病理依据2022年最新版WHO泌尿及男性生殖系统肿瘤分类标准,均诊断为睾丸良性肿瘤,并顺利完成TSMS治疗。16例患者术后康复顺利,术后1个月复查CDFI提示睾丸剩余组织血供良好,所有患者随访14~40个月,随访期内定期复查CDFI和MRI均未见睾丸内肿瘤残留、复发或转移征象,血清睾酮、AFP、hCG、LDH及精液检查较术前无显著变化,2例育龄期患者的配偶分别于术后16、18个月实现自然受孕。结论:睾丸内良性肿瘤可以通过CDFI、MRI检查进行术前鉴别诊断,最终定性诊断仍需组织病理检查。TSMS运用显微外科手术技术,可以在完整切除睾丸内肿瘤的前提下最大限度保留正常睾丸组织,从而有效保存男性生育力。TSMS疗效良好、安全性高,特别适用于有保留生育力需求的患者。

子宫内膜不典型增生/早期子宫内膜癌患者保留生育功能治疗后IVF-ET妊娠结局及复发因素分析

目的分析子宫内膜不典型增生/早期子宫内膜癌(AH/EEC)患者保留生育功能治疗后接受体外受精-胚胎移植(IVF-ET)治疗的临床特点和预后,分析影响助孕妊娠结局和疾病复发的主要因素。方法回顾性分析2012年2月至2022年2月在北京协和医院接受AH/EEC生育保留治疗后进行IVF-ET治疗的78例患者的临床资料。总结分析纳入患者的临床特征、IVF-ET相关指标、妊娠结局和复发情况,以单因素和多因素分析临床妊娠率、活产率以及疾病复发的影响因素。结果78例患者中51例(65.38%)为AH患者,27例(34.62%)为EEC患者;开始IVF-ET周期的平均年龄为(34.17±3.70)岁。共有74例患者至少接受了1次移植,每移植周期的临床妊娠率和活产率分别为36.31%(65/179)和18.99%(34/179),累积妊娠率为72.97%(54/74)。多因素分析提示子宫内膜病变初次发病年龄是活产率的独立影响因素[OR=0.8794,95%CI(0.785,0.983),P=0.02]。纳入患者IVF-ET期间子宫内膜病变的总复发率为6.41%(5/78),多因素分析提示子宫内膜病变的病理类型和IVF-ET前复发史是疾病复发的危险因素(P<0.05)。结论AH/EEC患者保留生育功能治疗后的辅助生殖结局相对满意,在肿瘤治疗过程中,进行病变评估时应尽量保护内膜,减少损伤;在肿瘤治疗结束后,应尽快进行助孕治疗,以最大程度降低复发率。

针刀疏筋解结术对类风湿关节炎家兔滑膜炎症的影响及作用机制研究

目的观察针刀疏筋解结术对类风湿关节炎(RA)模型家兔膝关节滑膜组织NF-κB/Bcl-2通路活性及肿瘤坏死因子-α(TNF-α)、白细胞介素(IL)-1β、IL-6、Bax、caspase-3表达的影响,探讨其抑制RA滑膜炎症的作用机制。方法24只新西兰白兔随机分为正常组、模型组、药物组和针刀组,每组6只,除正常组外,其余组采用卵蛋白+弗氏完全佐剂膝关节腔注射复制RA模型,分别予相应干预,连续18 d。测定家兔膝关节痛阈、膝关节周径,超声观察关节腔积液、滑膜厚度及内部血流信号,HE染色观察膝关节滑膜组织形态,TUNEL染色观察滑膜组织成纤维样滑膜细胞(FLS)凋亡情况,免疫组化检测滑膜组织TNF-α、IL-1β、IL-6表达,RT-PCR检测滑膜组织核因子(NF)-κBp65、Bcl-2mRNA表达,Westernblot检测滑膜组织NF-κBp65、p-NF-κBp65、Bcl-2、Bax、caspase-3蛋白表达。结果与正常组比较,模型组家兔膝关节痛阈降低、膝关节周径增加,超声评分和滑膜组织病理评分增加;滑膜组织FLS凋亡率降低,TNF-α、IL-1β、IL-6表达升高,NF-κBp65、Bcl-2 mRNA和蛋白及p-NF-κBp65蛋白表达升高,Bax、caspase-3蛋白表达降低,差异均有统计学意义(P<0.05)。与模型组比较,药物组和针刀组家兔膝关节痛阈增加、膝关节周径减小,超声评分和滑膜组织病理评分减少;滑膜组织FLS凋亡率升高,TNF-α、IL-1β、IL-6表达降低,NF-κBp65、Bcl-2m RNA和蛋白及p-NF-κBp65蛋白表达降低,Bax、caspase-3蛋白表达升高,差异均有统计学意义(P<0.05)。结论针刀疏筋解结术可能通过降低滑膜组织NF-κB/Bcl-2通路活性,促进FLS凋亡,减少TNF-α、IL-1β、IL-6产生,抑制RA滑膜炎症,减轻膝关节肿胀、提升痛阈。

逆行松解神经血管束且保留Retzius间隙机器人辅助腹腔镜根治性前列腺切除术的技术要点(“大家泌尿网”观看手术视频)

保留耻骨后间隙的前列腺癌根治术(RS-RARP)可以显著提高术后即刻尿控且不增加切缘阳性率。然而该术式学习曲线长,目前能掌握的学者不到10%,尚未推广。基于对前列腺解剖结构及手术方式的认识,本中心对RS-RARP进行优化。我们首创了完全后入路逆行松解神经血管束的RARP,最大限度保留神经血管束,简化手术操作,仅使用一根缝线即可完成尿道吻合,无需使用Hem-o-lok,减少相关并发症。我们在本中心常规开展该术式,通过多维度分析认为这是一种“肿瘤控制可、尿控保护好、性功能恢复快、并发症少、可操作性强”的手术方式。本文详细介绍该术式的关键步骤及操作体会。

基于主成分分析-BP神经网络的风电备件需求预测

风电机组具有结构复杂,运维困难,且长期处于恶劣的工作环境的特点。风电备件的需求预测有助于为风电场配备最合适的备件数,以确保风电场的平稳、高效运行。构建主成分分析-反向传播(principal component analysis-back propagation,PCA-BP)模型,针对受多因素影响的复杂备件,先利用PCA将影响风电备件的要素进行筛选,再利用BP神经网络算法,得到最为精确的预测结果。比较自回归积分滑动平均(autoregressive integrated moving average,ARIMA)模型、BP神经网络预测和PCA-BP神经网络预测的结果。结果表明:PCA能显著降低神经网络预测误差,预测的精度为93.94%,高于BP神经网络预测的88.39%和ARIMA模型的85.31%,所以PCA-BP神经网络模型的预测精度准确且有可靠结果,能够适用于风机备件的需求预测。

基于改进Croston方法的多需求模式零备件预测

维修备件管理是提高产线可靠性、实现降本增效的关键。针对具备间歇性与随机性特征的维修备件需求预测问题,提出了基于改进Croston方法的备件需求预测模型。依据Syntetos准则基于间断性与波动性特征将备件需求划分为4类。针对含有波动性特征的需求,基于Croston方法主要思想将备件需求预测分解为需求发生状态预测和需求量预测两类问题,设计了集合经验模态分解(ensemble empirical mode decomposition,EEMD)-长短期记忆网络集成(long short-term memory,LSTM)预测模型。EEMD方法将剧烈波动序列分解为若干相对平稳的分量,进而采用LSTM方法对各分量进行预测。针对含有间断性特征的需求,引入信号处理技术中的信号调制技术,将需求发生状态0-1二值序列进行连续化处理。所提方法解决了备件需求波动性强、间断性大的难题,已应用于湖北中烟武汉卷烟厂,证明了方法的优越性与可行性。

基于质量问题统计数据的某型车辆备件配置研究

基于交付用户使用后的某型特种车辆质量问题统计数据,对发生的质量问题进行了分类和分析,梳理出车辆易损件备件清单。最后对该产品备件配置存在的问题进行了探讨并提出了建议,以期对其他产品备件配置提供一定的借鉴。

基于飞机状态的备件动态规划技术

伴随民航业的竞争日趋激烈,航空公司迫切需要控制成本以提升效益。民机备件既是直接影响飞行安全的关键因素,备件成本又在航空公司可控成本中占比最高。因此,在保证飞行安全的前提下做好备件规划,对航空公司有至关重要的意义。根据民机备件的安全级别、故障修复时限等对备件分级设置保障率水平,采用符合备件故障特性的马尔可夫生灭过程,建立满足给定保障率水平的备件量计算模型,并在此基础上建立以保障成本最低为目标函数,满足保障率水平为约束函数的备件量动态规划模型。基于飞机状态分析历史故障数据、季节性、日利用率、机队规模对备件保障的影响,在所建模型中将故障率季节性差异、日利用率和飞机停场损失淡旺季差异进行评估以减小计算结果与实际需求的偏差。以H航空公司ERJ-190机型显示组件为例,对所建模型进行应用验证,计算结果与H航空公司运营实际相吻合,证明所建模型可为航空公司备件规划提供技术方法支持。

具有低度恶性潜能的多房囊性肾肿瘤的临床病理特征及预后

目的:分析具有低度恶性潜能的多房囊性肾肿瘤(multilocular cystic renal neoplasm of low malignant potential,MCRNLMP)患者的临床病理特征与预后,对比接受不同手术方式的具有低度恶性潜能的多房囊性肾肿瘤患者的临床病理特征。方法:回顾性收集2010年1月至2023年9月北京大学第三医院收治的行根治性肾切除术或者保留肾单位手术且术后病理明确为具有低度恶性潜能的多房囊性肾肿瘤患者的临床资料,获取其基本临床特征、术后病理结果及预后。根据手术方式将患者分为根治性肾切除术组及保留肾单位手术组,并比较两组患者的临床病理特征差异。结果:共纳入35例患者,诊断时的中位年龄为53.0(39.0~62.0)岁,其中23例为男性(65.7%),12例为女性(34.3%)。9例患者接受了根治性肾切除术(25.7%),26例患者接受了保留肾单位手术(74.3%)。35例患者的临床T分期均未超过T2a期。中位手术时间145.0 min,中位估计术中出血量20.0 mL。术后中位住院天数6.0 d。术后病理结果均未提示肾窦侵犯、肉瘤样变、肾上腺侵犯及淋巴结侵犯。将患者根据手术方式分为保留肾单位手术组和根治性肾切除术组,并对两组的临床病理特征进行对比,差异均无统计学意义。除1例患者失访外,其余患者均获随访,随访时间8~111个月,中位随访时间70.5个月,仅1例患者因非肿瘤原因死亡,其余患者均无肿瘤转移或复发。结论:具有低度恶性潜能的多房囊性肾肿瘤患者的预后较好;对于具有低度恶性潜能的多房囊性肾肿瘤,接受保留肾单位手术和根治性肾切除术的患者临床病理学特征差异无统计学意义。

数据与知识双驱动的备件需求模糊预测模型

针对知识驱动型需求预测模型所需的专家知识稀缺、数据驱动型需求预测模型可解释性不足的问题,提出了数据与知识双驱动的备件需求模糊预测模型。该模型基于模糊聚类算法将数值型数据聚类为结构简单、可解释性强的规则库,运用模糊逻辑将领域专家知识表示为Mamdani型规则库。在此基础上,引入了一种新型智能计算理论——模糊网络理论对两类规则库进行合并运算,形成初始预测模型。采用遗传算法优化模型规则库的模糊集参数来提高模型预测准确性。通过与模糊聚类算法进行对比,提出的模型在可解释性以及准确性指标上均具有优势。