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.

System optimization-oriented spare parts dynamic configuration model for multi-echelon multi-indenture system

In order to optimize the spares configuration project at different stages during the life cycle, the factor of time is considered to relax the assumption of the spares steady demand in multi-echelon technique for recoverable item control (METRIC) theory. According to the method of systems analysis, the dynamic palm theorem is introduced to establish the prediction model of the spares demand rate, and its main influence factors are analyzed, based on which, the spares support effectiveness evaluation index system is studied, and the system optimization-oriented spares dynamic configuration method for multi-echelon multi-indenture system is proposed. Through the analysis of the optimization algorithm, the layered marginal algorithm is designed to improve the model calculation efficiency. In a given example, the multi-stage spares configuration project during its life cycle is gotten, the research result conforms to the actual status, and it can provide a new way for the spares dynamic optimization.

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.

Joint optimization of maintenance inspection and spare provisioning for aircraft deteriorating parts

With the wide application of condition based maintenance(CBM) in aircraft maintenance practice, the joint optimization of maintenance and inventory management, which can take full advantage of CBM and reduce the aircraft operational cost, is receiving increasing attention. In order to optimize the inspection interval, maintenance decision and spare provisioning together for aircraft deteriorating parts, firstly, a joint inventory management strategy is presented, then, a joint optimization of maintenance inspection and spare provisioning for aircraft parts subject to the Wiener degradation process is proposed based on the strategy.Secondly, a combination of the genetic algorithm(GA) and the Monte Carol method is developed to minimize the total cost rate.Finally, a case study is conducted and the proposed joint optimization model is compared with the existing optimization model and the airline real case. The results demonstrate that the proposed model is more beneficial and effective. In addition, the sensitivity analysis of the proposed model shows that the lead time has higher influence on the optimal results than the urgent order cost and the corrective maintenance cost, which is consistent with the actual situation of aircraft maintenance practices and inventory management.

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. Equipmentrs 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.

Location and allocation problem for spare parts depots on integrated logistics support

In equipment integrated logistics support(ILS), the supply capability of spare parts is a significant factor. There are lots of depots in the traditional support system, which makes too many redundant spare parts and causes high cost of support. Meanwhile,the inconsistency among depots makes it difficult to manage spare parts. With the development of information technology and transportation, the supply network has become more efficient. In order to further improve the efficiency of supply-support work and the availability of the equipment system, building a system of one centralized depot with multiple depots becomes an appropriate way.In this case, location selection of the depots including centralized depots and multiple depots becomes a top priority in the support system. This paper will focus on the location selection problem of centralized depots considering ILS factors. Unlike the common location selection problem, depots in ILS require a higher service level. Therefore, it becomes desperately necessary to take the high requirement of the mission into account while determining location of depots. Based on this, we raise an optimal depot location model. First, the expected transportation cost is calculated.Next, factors in ILS such as response time, availability and fill rate are analyzed for evaluating positions of open depots. Then, an optimization model of depot location is developed with the minimum expected cost of transportation as objective and ILS factors as constraints. Finally, a numerical case is studied to prove the validity of the model by using the genetic algorithm. Results show that depot location obtained by this model can guarantee the effectiveness and capability of ILS well.

Calcineurin inhibitor sparing strategies in renal transplantation, part one: Late sparing strategies

Kidney transplantation improves quality of life and reduces the risk of mortality. A majority of the success of kidney transplantation is attributable to the calcineurin inhibitors(CNIs), cyclosporine and tacrolimus, and their ability to reduce acute rejection rates. However, longterm graft survival rates have not improved over time, and although controversial, evidence does suggest a role of chronic CNI toxicity in this failure to improve outcomes. Consequently, there is interest in reducing or removing CNIs from immunosuppressive regimens in an attempt to improve outcomes. Several strategies exist to spare calcineurin inhibitors, including use of agents such as mycophenolate mofetil(MMF), mycophenolate sodium(MPS), sirolimus, everolimus or belatacept to facilitate late calcineurin inhibitor withdrawal, beyond 6 mo post-transplant; or using these agents to plan early withdrawal within 6 mo; or to avoid the CNIs all together using CNI-free regimens. Although numerous reviews have been written on this topic, practice varies significantly between centers. This review organizes thedata based on patient characteristics(i.e., the baseline immunosuppressive regimen) as a means to aid the practicing clinician in caring for their patients, by matching up their situation with the relevant literature. The current review, the first in a series of two, examines the potential of immunosuppressive agents to facilitate late CNI withdrawal beyond 6 mo post-transplant, and has demonstrated that the strongest evidence resides with MMF/MPS. MMF or MPS can be successfully introduced/maintained to facilitate late CNI withdrawal and improve renal function in the setting of graft deterioration, albeit with an increased risk of acute rejection and infection. Additional benefits may include improved blood pressure, lipid profile and serum glucose.Sirolimus has less data directly comparing CNI withdrawal to an active CNI-containing regimen, but modest improvement in short-term renal function is possible, with an increased risk of proteinuria, especially in the setting of baseline renal dysfunction and/or proteinuria. Renal outcomes may be improved when sirolimus is used in combination with MMF. Although data with everolimus is less robust, results appear similar to those observed with sirolimus.

Retroperitoneal laparoscopic partial resection of the renal pelvis for urothelial carcinoma:A case report

BACKGROUND The standard treatment of transitional cell carcinoma of the upper urinary tract consists of radical nephroureterectomy with bladder cuff removal,which can be performed either in open or laparoscopy or robot-assisted laparoscopy.Treatment of chronic renal insufficiency patients with upper urothelial tumor is in a dilemma.Urologists weigh and consider the balance between tumor control and effective renal function preservation.European Association of Urology guidelines recommend that select patients may benefit from endoscopic treatment,but laparoscopic treatment is rarely reported.CASE SUMMARY In this case report,we describe a case of 79-year-old female diagnosed with urothelial carcinoma of the renal pelvis and adrenal adenoma with chronic renal insufficiency.The patient was treated with retroperitoneal laparoscopic partial resection of the renal pelvis and adrenal adenoma resection simultaneously.CONCLUSION Retroperitoneal laparoscopic partial resection of the renal pelvis is an effective surgical procedure for the treatment of urothelial carcinoma of the renal pelvis.

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

Selective partial salivary glands sparing during intensity-modulated radiation therapy for nasopharyngeal carcinoma

Objective This study evaluated the dosimetric consequences of selective partial salivary gland sparing during intensity-modulated radiotherapy(IMRT) for patients with nasopharyngeal carcinoma(NPC).Methods Ten patients with NPC were enrolled in the study.Two IMRT plans were produced for each patient:conventional(control) and partial salivary glands-sparing(treatment),with dose constraints to the entire parotid glands or partial salivary glands(including the parotid and submandibular glands,delineated with the adjacent distance of at least 0.5 cm between the glands and PTV,the planning target volume) in planning,respectively.Dosimetric parameters were compared between the two plans,including the V_(110%),V_(100%),V_(95%)(the volume covered by more than 110%,100%,or 95% of the prescribed dose),Dmin(the minimum dose) of PTV,homogeneity index(HI),conformity index(CI),and the mean dose and percentage of the volume receiving 30 Gy or more(V_(30)) for the parotid glands and submandibular glands.Results Treatment plans had significantly lower mean doses and V_(30) to both the entire parotid glands and partial parotid glands than those in control plans.The mean doses to the partial submandibular glands were also significantly lower in treatment plans than in control plans.The PTV coverage was comparable between the two plans,as indicated by V_(100%),V_(95%),Dmin,CI,and HI.The doses to critical structures,including brainstem and spinal cord,were slightly but not significantly higher in treatment plans than in control plans.Conclusion A selective partial salivary gland-sparing approach reduces the doses to parotid and submandibular glands during IMRT,which may decrease the risk of post-radiation xerostomia while not compromising target dose coverage in patients with NPC.

Spare Parts Demand Forecasting:a Review

Spare parts are very common in industry and military fields, and the investigations of spare parts demand forecasting methods have draws much attention in recent years. However,to the best of our knowledge,only few papers reviewed the forecasting papers systematically. This paper is an attempt to provide a novel and comprehensive view to summarize these methods. A new framework was proposed to classify the demand forecasting methods into four categories,including empirical methods,methods based on historical data,analytical methods and simulation methods. Some typical literatures related to each category were reviewed.Moreover, a general spare parts forecasting procedure was summarized and some evaluation criteria were presented. Finally,characteristics of different forecasting methods and some avenues for further research were illustrated. This work provides the managers with a systematical idea about the spare parts demand forecasting and it can be used in practical applications.

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.

Forecasting Spare Parts Demand Using Statistical Analysis

Spare parts are very essential in most industrial companies. They are characterized by their large number and their high impact on the companies’ operations whenever needed. Therefore companies tend to analyze their spare parts demand and try to estimate their future consumption. Nevertheless, they face difficulties in figuring out an optimal forecasting method that deals with the lumpy and intermittent demand of spare parts. In this paper, we performed a comparison between five forecasting methods based on three statistical tools;Mean squared error (MSE), mean absolute deviation (MAD) and mean error (ME), where the results showed close performance for all the methods associated with their optimal parameters and the frequency of the spare part demand. Therefore, we proposed to compare all the methods based on the tracking signal with the objective of minimizing the average number of out of controls. This approach was tested in a comparative study at a local paper mill company. Our findings showed that the application of the tracking signal approach helps companies to better select the optimal forecasting method and reduce forecast errors.

Inventory Management of a Plant Spare Parts Supply Chain

In spare parts industries, firms are dealing with a situation which is more and more uncertain due to the supply chain structure and variable demands. This paper presents a Bayesian approach to forecast demand and subsequently determine the appropriate parameter S of an （ S - 1 ; S） inventory system for controlling plant spare parts. We apply the Bayesian approach in an innovative way to specify the initial prior distributions of the failure rates, using the initial estimates and the failure history of similar items. According to the proposed method, a lower base stock than the one currently used is sufficient to achieve the desired service level.

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.

Purchase-oriented Classification Model of the Spare Parts of Agricultural Machinery

Based on the classification of spare parts and the research results of the demand of spare parts,a three-dimensional classification model of spare parts of agricultural machinery is established,which includes the application axis sorted by technical characteristics,the cost axis classified by ABC method,and the demand axis classified by the demand of the spare parts of agricultural machinery.These dimension axes represent different factors,and the application of factors in purchase is analyzed.Guiding value of each dimension axis is summarized in the field of the spare parts purchase;and corresponding strategy instruction is put forward.Integrated application of these strategies by model makes the purchase have more realistic operational meaning.Application field of the three-dimensional model of spare parts is discussed;and the direction for further research is pointed out.

Prioritizing Maintenance Spare Parts Based on Supportability Analysis and Neural Network

In order to facilitate spare parts management,an integrated approach of BP neural network and supportability analysis(SA)was proposed to evaluate the criticality of spare parts as well as to prioritize spare parts.Influential factors of prioritizing spare parts were detailedly analyzed.Framework of the integrated method was established.The modelling process based on BP neural network was presented.As the input of the neural network,the values of influential factors were determined by supportability analysis data.Based on the presented method,spare parts could be automatically prioritized after supportability analysis for a new system.A case study results showed that the new method was applicable and effective.

Transumbilical laparoendoscopic single-site surgery(LESS) partial nephrectomy:a median follow-up of 2 years

Objective:Nephron-sparing surgery(NSS) for small renal masses offers a similar functional and oncological outcome to that of radical surgery.Laparoendoscopic single-site surgery(LESS) emerges as an advanced alternative for reduced invasiveness and improves cosmesis;LESS is developing quickly and its indications have been expanded,but still in its infancy.The aim of this paper is to report our preliminary experience in transumbilical LESS partial nephrectomy(LESS-PN),so as to assess its utility, safety and efficacy.Methods:From August 2009 to October 2010,3 patients underwent transumbilical LESS-PN via a novel multi-channel TriPort by a single experienced urologist in our institution.Patient demographics,perioperative and follow-up data were prospectively collected and analyzed.Results:All the three procedures were successfully completed.A 5-mm ancillary trocar was utilized in all 3 cases.The mean operative duration was 226.3(210-254 min) with an estimated blood loss of 56.7 ml (20-100 ml).Mean warm ischemia time was 35.7 min(19-48 min).One patient was transfused due to postoperative bleeding. The recovery was uneventful and mean length of postoperative stay was 13 days(12-14 days).At the latest follow-up,all patients remained symptom-free and had normal renal function without evidence of recurrence,and they were delighted for a hidden transumbilical scar.Conclusion:Transumbilical LESS-PN is a feasible and safe procedure albeit extremely technically challenging.Surgical outcomes at a median follow-up of 2 years are promising,while currently it should be reserved for highly selected patients with favorable tumor anatomy and performed by a very experienced laparoscopic surgeon.

Ship spare parts demand forecast based on RBF neural network

Due to the fact that in ship maintena n ce process,the method of determining the number of spare parts is not scientific and the actual operation is complicated,this paper analyzes four major facto rs affecting the number of ship spare parts,including number of main planned op eration s,total times of disassembling in maintenance,accumulated working time and mea n t ime between failures.It also establishes a spare parts demand forecast model b ased on the affecting factors and radial-basis function(RBF) neural network.F inally,the paper provide s forecast examples and makes a comparison between the examples and back propaga tion(BP) neura l network forecast result.The comparison results s how that the forecast based on RBF neural network is simple and the forecast res ult fits the actual situa tion and fitting effect is better than that based on BP.

Auto Spare Parts Export: At a Crossroad

Chinese car spare parts sup-pliers have arrived at a cross-roads,as the golden age for component export has gone forever,when the production method was simple,costs were low and profits were high.What will be the way out in front of the tremendous export pres-sures?