Narrow Results

Proof-testing for E/E/PE safety-related systems is known as a periodic inspection and maintenance activity to maintain their designed functional safety in operation. Generally, the proof-testing takes so much cost and time for checking the E/E/PE safety-related systems comprehensively. Therefore, effective proof-testing intervals should be considered based on the rationale for the hazardous risk and maintenance cost. As one of the approaches, there exist methods deriving economic proof-testing intervals minimizing simultaneous the proof-testing cost and the risk at hazardous event occurrence. However, the safety constraint should be needed to consider at the same time since the E/E/PE safety-related systems are required to maintain certain safety level in operation. This paper addresses a mathematical approach for obtaining optimal proof-testing intervals for such practical situations.

Software reliability plays an important role in assuring the quality of a software. To ensure software reliability, the software is tested thoroughly during the testing phase. The time invested in the testing phase or the optimal software release time depends on the level of reliability to be achieved. There are two different concepts related to software reliability, viz., testing reliability and operational reliability. In this paper, we compare both types of software reliabilities to determine the optimal testing time of the software so as to minimize the total expected software maintenance cost. We consider a software has a number of clusters of modules, each having a different number of errors and a different failure rate. A hyperexponential model is employed for analyzing software reliability growth. Parameter estimation using the maximum likelihood estimation technique is also discussed. Numerical illustrations are taken to explore the effect of various parameters on reliability and maintenance cost. It is noticed that the operational reliability concept should be adopted for the software testing time problem.

This paper presents new sequential imperfect preventive maintenance (PM) models incorporating adjustment/improvement factors in hazard rate and effective age. The models are hybrid in the sense that they are combinations of the age reduction PM model and the hazard rate adjustment PM model. It is assumed that PM is imperfect: It not only reduces the effective age but also changes the hazard rate, while the hazard rate increases with the number of PMs. PM is performed in a sequence of intervals. The objective is to determine the optimal PM schedule to minimize the mean cost rate. Numerical examples for a Weibull distribution are given.

Both response time and processing time become recently big problems in the processing time of various online and batch systems. Especially, the access efficiency of the database should be greatly controlled as for the speed of the processing time of accesses to the database. Because records are inserted far from their logical position, the storages of deleted records occupy some diverse spaces in the database. Then, to cover the weak point of the database, we execute the database reorganization at suitable times to achieve a good performance requirement for the application. There are two types purposes of the database reorganization: The purpose of physical reorganization is to optimize the database storage and to improve the database structure. However, as the database has usually access locality, its data structure may deterirate in limited parts of the storage space. Thus, we adop the partial reorganization. This reorganizes only locally structurally deteriorated space in the database, while the structural efficiency can be recovered similarly to the full reorganization. This paper considers two structural deteriorations which increase with time and occur independently in time. When the amount of deterioration is estimated at periodic time and at a specified time, the expected cost rates are obtained, using the cumulative damage model, and optimal policies which minimize them are discussed and analytically. We compute optimal policies for two models and compare them numeically.

As an airframe has finite lifetime and has to be designed lightweight, the maintenance of airframe is indispensable to operate aircraft without any serious troubles. After an airframe begins to operate, it suffers stresses and the stress causes the damage such as cracks of the airframe. Cracks grow with operation time and cause catastrophic phenomenon such as the mid-air disintegration when they become greater than a critical size. So, the managerial crack size is prespecified and Preventive Maintenance (PM) undergoes when the inspected crack size exceeds it. In this paper, optimal PM policies of airframe crack failure are discussed. Airframe states are represented as the Markov renewal process, and one-step transition probabilities are discussed. The total expected cost from the start of operation to the end by failure is defined and the optimal PM policies which minimize it is discussed.

As the technology has developed, cloud computing which is a kind of Internet-based computing has widely spread. In terms of operating cloud system in remote locations, there exist some problems when the failure of cloud system occurs. In such cases, workers need to go to the remote locations and maintain the system. This paper considers stochastic models of a redundant cloud system in remote locations. The cloud system has active devices and standby devices. We derive the steady-state availability and discuss optimal policies which maximize it. Finally, numerical examples are given.

As the Internet technology has developed, the demands for the improvement of the reliability and security of the system connected with the Internet have increased. Although various services are performed on the Internet, illegal access on the Internet has become a problem in recent years. This paper formulates stochastic models for a system with illegal access. The server has the function of IDS, and illegal access is checked in multiple stages which consist of simple check, detailed check and dynamic check. We apply the theory of Markov renewal processes to a system with illegal access, and derive the mean time and the expected checking number until a server system becomes faulty. Further, optimal policies which minimize the expected cost are discussed. Finally, numerical examples are given.

In Japan, the annual sales share of supermarkets and convenience stores increased around 2000. Both self-servicing and delivering a wide variety of products are denominators of these stores, and they have an advantage in retail business competitions because self-service stores can reduce labor costs by engaging consumers with the provision of services and the productivity of these stores is higher than specialty stores. In case of self-service stores, miscellaneous jobs such as cash registering, goods arranging, and shelf reviewing, have to be performed by limited number of clerks and efficient operation methods are required. The inventory management of store shelves for avoiding out-of-stock is an important issue and the AHM-Model which is a famous periodic monitoring inventory utilizing dynamic programming was proposed.

In this paper, store shelves are monitored periodically and are replenished when the total amount of goods is below a threshold. Total expected cost rates are defined and optimal thresholds are discussed utilizing the cumulative damage model analytically.

This paper formulates a stochastic model for a system with illegal access. The server has the function of IDS, and illegal access is checked in multiple stages which consist of simple check and detailed check. In this model, we consider type I and II errors of simple check and a type I error of detailed check. There are two cases where IDS judges the occurrence of illegal access erroneously. One is when illegal access does not occur, and the other is when illegal access occurs. We apply the theory of Markov renewal processes to a system with illegal access, and derive the mean time and the expected checking number until a server system becomes faulty. Further, an optimal policy which minimizes the expected cost is discussed. Finally, numerical examples are given.

Code error correction methods have been important techniques at a radio environment and video stream transmission. In general, when a server transmits some data packets to a client, the server resends the only loss packets. But in this method, a delay occurs in a transmission. In order to prevent the transmission delay, the loss packets are restored by the error correction packet on a client side. The code error correction method is called Hybrid Automatic Repeat reQuest (ARQ) and has been researched. On the other hand, congestion control schemes have been important techniques at a data communication. Some packet losses are generated by network congestion. In order to prevent some packet losses, the congestion control performs by prolonging packet transmission intervals, which is called High-performance and Flexible Protocol (HpFP). In this paper, we present a stochastic model of congestion control based on packet transmission interval with Hybrid ARQ for data transmission. That is, if the packet loss occurs, the data packet received in error is restored by the error correction packet. Moreover, if errors occur in data packets, the congestion control performs by prolonging packet transmission intervals. The mean time until packet transmissions succeed is derived analytically, and a window size which maximizes the quantity of packets per unit of time until the transmission succeeds is discussed.

Cyber attack on the Internet has become a problem in recent years, and it has been becoming more sophisticated and complicated. As one of schemes to detect cyber attack, IDS has been widely used. IDS can detect cyber attack based on the signature which is the pattern of cyber attack and so on. There are signature-based and anomaly-based detection methods in terms of IDS. Signature detection compares activity and behavior to signatures of known attacks. Signatures need to be updated regularly to detect a new type of attacks. This paper considers extended stochastic models for a server system with signature update. The server has the function of IDS. In this model, we consider type II error where IDS judges the occurrence of cyber attack erroneously when it occurs. We assume that the check with signature update is performed at $N$th check or every $k$ checks. We obtain the expected costs until cyber attack is detected and discuss the optimal policies which minimize them. Finally, numerical examples are given.

E/E/PE safety-related systems play an important role in ensuring the functional safety especially for the safety-critical systems. In fact, the E/E/PE safety-related systems are widely implemented in several types of systems, such as automotive and chemical plant control systems, for the safe operation of them. In the operation of the systems, proof-testing, which is known as scheduled periodic inspections or maintenance activities, is conducted for maintaining certain level of safety integrity required to the E/E/PE safety-related system. However, the proof-testing needs a lot of time and cost for checking and proofing whether the safety-related system satisfies the safety requirement in operation. We discuss economic strategies for supporting design of proof-testing interval by focusing on the trade-off relationship between the maintenance cost and the risk at harmful event occurrence.

Employee training is essential for corporate activities to improve their production efficiency and product quality. The most representative two types of employee training are known, i.e., on-the-job training and off-the-job training. Off-the-job training can be classified into two types, i.e., compulsory training and non-compulsory training. Safety training and compliance are known as compulsory training, and they are needed to ensure that daily work continues without serious problems. Compulsory education is undertaken in a classroom every year by all employees of a department or section. Daily e-learning is effective for complementing and enhancing mandatory education and it helps employees to remember what they have learned during their annual education. In this paper, we discuss optimal employee safety education models that are complemented and enhanced by e-learning. The expected cost rate of education is expressed using the imperfect maintenance model, and the optimal policies that minimize it are discussed.

Maintenance activities for safety-related systems are generally required to ensure that the systems are working as intended. Regarding the maintenance activities, proof-testing is known as scheduled inspections and maintenance activities for detecting dangerous undetected faults which cannot be detected by diagnostic testing systems installed in the safety-related systems. However, the proof-testing needs a lot of cost and provokes decreasing of the availability for the whole system because the whole system is needed to shut down for proofing that the whole system is working as intended. We discuss analytical methodologies for obtaining optimal proof-testing interval with harmful risk and proof-testing cost by describing the behavior of the safety-related system based on a continuous-time Markov chain. Further, an analytical optimal policy for obtaining economic proof-testing interval is proposed in this paper.

Different types of social infrastructure, such as roads and bridges, are essential and necessary for supporting our daily lives and economic operations. Because 39% of Japan’s road bridges and 27% of its tunnels will have been in use for 50 years or more by 2023, maintaining them has become a significant national concern (Ministry of Land, Infrastructure, Transport and Tourism, White Paper on Land, Infrastructure, Transport and Tourism in Japan (2017), p. 114). Because of the declining birthrate, the deteriorating labor force, and the weakening local economy, the Japanese government must maintain these social infrastructures while facing severe budgetary challenges. And efficient and economical maintenance strategies and plans are required. This paper proposes optimal maintenance policies which consider the unique circumstances of social infrastructure and minimize maintenance costs. By applying these policies to wave-dissipating blocks in Japan, the effectiveness of them is confirmed.

This study discusses an opportunity-based age replacement policy for a system which has a warranty period (0, S]. When the system fails at its age x≤S, a minimal repair is performed. If an opportunity occurs to the system at its age x for S<x<T, we take the opportunity with probability p to preventively replace the system, while we conduct a corrective replacement when it fails on (S, T). Finally if its age reaches T, we execute a preventive replacement. Under this replacement policy, the design variable is T. For the case where opportunities occur according to a Poisson process, a long-run average cost of this policy is formulated under a general failure time distribution. It is, then, shown that one of the sufficient conditions where a unique finite optimal T* exists is that the failure time distribution is IFR (Increasing Failure Rate). Numerical examples are also presented for the Weibull failure time distribution.

In a declining market for goods, we optimize the net profit in business when inventory management allows change in the selling prices n times over time horizon. We are computing optimal number of changes in prices, respective optimal prices, and optimal profit in each of the cycle for a deteriorating product. This paper theoretically proves that for any business setup there exists an optimal number of price settings for obtaining maximum profit. Theoretical results are supported by numerical examples for different setups (data set) and it is found that for every setup the dynamic pricing policy outperforms the static pricing policy. In our model, the deterioration factor has been taken into consideration. The deteriorated units are determined by the recurrence method. Also we studied the effect of different parameters on optimal policy with simulation. For managerial purposes, we have provided some "suggested intervals" for choosing parameters depending upon initial demand, which help to predict the best prices and arrival of customers (demand).

Due to the crisis of 2007–2009, financial friction macro models are being used to provide a theoretical foundation for the evaluation of ‘unconventional policy’. In these models, banks take deposits from households and lend to firms. Empirically, other financial channels that are missing in the models, such as corporate bonds and equity, are also important. This paper analyzes a model in which bank loans and equity are both feasible. Households have limited ability to enforce their claims. If either the bank or the equity market are undistorted, the equilibrium is socially efficient. If both are distorted, the equilibrium is inefficient. In that case, government policy aimed at the bank or at the firm can be helpful. Suitably chosen equity injections, loans, or interest rate subsidies can all work. Interest rate subsidies have the advantage that they occur later and there is less concern about cheating. Equity injections have the advantage that they minimize the necessary level of tax imposed on households that is needed to achieve optimality. Optimal equity injections and optimal loan subsidies induce reductions in household savings (‘crowding out’). Optimal interest rate subsidies induce increases in household savings (‘crowding in’).

Existing literature does not capture efficiency losses on the dynamic adjustment path of smuggling control market from initial to final equilibrium after a shock in order to formulate an optimal smuggling control policy. Furthermore, a number of public service units and smuggling control rate are major determinants of smuggling cases controlled in a society, and a policy without taking into consideration such vital determinants cannot ensure adjustment of a number of smuggling cases controlled as a result of cost movement in desired time, which may lead to extra efficiency losses than those envisaged during policy formulation for an optimal level of smuggling control in a society. This article designs a comprehensive optimal smuggling control policy mechanism by modeling a three-dimensional smuggling control system in society capturing the number of public service units, smuggling control rate, and cost, while taking into account efficiency losses during adjustment of smuggling control market, smuggling control rate and the number of public service units in addition to those which result due to movements from initial to final equilibriums.