System Maintenance Activities Research Articles

Two-stage distributionally robust optimization for joint system design and maintenance scheduling in high-consequence systems

The failures of high-consequence systems can cause serious harm to humans, including loss of human health, life security, finance, and even social chaos. To protect high-consequence systems, both optimal system design and maintenance activities contribute to improving system reliability and social safety. The existing works generally optimize these two problems sequentially and assume that the degradation process of components is precisely known. However, sequential optimization often results in significant losses due to redundancies, and such a presumption usually cannot be guaranteed in practice, due to limited historical data or a lack of expert knowledge, referred to as epistemic uncertainty. To fill this gap, in this article, we consider an integrated optimization of system design and maintenance scheduling for multi-state high-consequence systems in which the component’s degradation is known with limited distributional information. To address this issue, we utilize the framework of distributionally robust optimization to provide a risk-averse decision to decision-makers even under the worst realizations of random parameters, and develop a two-stage integer distributionally robust model with moment-based ambiguity set to determine the system design and maintenance scheduling simultaneously. The proposed model can be converted to a tractable approximation as an integer linear stochastic programming problem. In order to solve large-scale problems, we develop a sample-based adaptive large neighborhood search algorithm to find the optimal system designs. In the numerical experiments, we present a case study on feedwater heating systems in nuclear power plants and demonstrate that an integrated optimization consideration creates significant benefits in profitability. We also present the out-of-sample performance of the distributionally robust design to avoid extreme risk.

Mediation Effects of Fraud Prevention on the Relationship of Internal Control, Risk Management and Organizational Performance

This study aims to determine the effect of internal control and risk management on organizational performance through fraud prevention. This quantitative research type uses descriptive analysis methods and inferential statistics, namely Structural Equation Modeling (SEM) using Partial Least Square (PLS) and Microsoft Excel software. The population in this study were all auditors who worked at the Inspectorate of Southeast Sulawesi Province, amounting to 37 apparatus. By taking a sample using a saturated piece, the number of samples is 37 Apparatus at the Inspectorate of Southeast Sulawesi Province. This research is sourced from primary data and secondary data. Primary data is obtained from the results of questionnaires distributed to each respondent; secondary data is data that has been collected or data obtained from previous research results—analysis of the Structural Equation Model (SEM) using the PLS program. The study's results found that internal control and risk management had a positive and significant effect on fraud prevention; fraud prevention has a positive and significant impact on organizational performance; internal control and risk management have a positive and significant impact on organizational performance through fraud prevention. Although the internal control implemented is reasonable, it needs to be improved by increasing the identification of every possible risk to avoid risks that will occur in the future. We suggest that the Southeast Sulawesi Provincial Inspectorate can review the performance of each division in carrying out operational activities based on the achievement of performance indicators. Improve regular system maintenance activities, thereby minimizing system disturbances—more follow-up on recommendations on audit findings.

Analysis of Indonesian Naval Ship Maintenance Strategy at Jakarta Military Sea Lift Unit to Support Sea Transportation

The background of the research is the limited readiness of ships at the Jakarta Military Sea Lift Unit caused by the age of most of the ships more than 20 years. The purpose of the study was to analyze the strategy of maintaining ship readiness through system maintenance activities. The research method is quantitative with a survey approach with an analysis model based on Strength, Weakness, Opportunity, and Threat (SWOT). Research respondents are purposive sampling that have relevance in the field of ship maintenance. The results showed that to improve ship readiness through maintenance systems, was carried out by increasing the capabilities of human resources, Management Planned maintenance systems, The availability of spare parts, and the capability of the Ship Maintenance Facility Unit. The improvement of personnel capabilities and skills is carried out through training activities in collaboration with the original engine manufacturer (OEM). This ship maintenance system is based on a planned maintenance system supported by the availability of spare parts and the capability of Ship Maintenance Facility Units. Contribution of the research to maintain the readiness of ships to support operational activities, which has implications for the readiness and sustainability .

CMS RPC activities during LHC LS-2

The second LHC long shutdown period (LS2) is an important opportunity for the CMS Resistive Plate Chambers (RPC) to complete their consolidation and upgrade projects. The consolidation includes detector maintenance for gas tightness, HV (high voltage), LV (low voltage) and slow control operation. All services for the RPC Phase-2 upgrade: improved RPC in stations RE3/1 and RE4/1, were anticipated for installation to LS2. This paper summarises the RPC system maintenance and upgrade activities.

A Method to Account for Personnel Risk Attitudes in System Design and Maintenance Activity Development

Systems engineering practices in the maritime industry and the Navy consider operational availability as a system attribute determined by system components and a maintenance concept. A better understanding of the risk attitudes of system operators and maintainers may be useful in understanding potential impacts the system operators and maintainers have on operational availability. This article contributes to the literature a method that synthesizes the concepts of system reliability, and operator and maintainer risk attitudes to provide insight into the effect that risk attitudes of systems operators and maintainers have on system operational availability. The method consists of four steps providing the engineer with a risk-attitude-adjusted insight into the system’s potential operational availability. Systems engineers may use the method to iterate a system’s design or maintenance concept to improve expected operational availability. If it is deemed necessary to redesign a system, systems engineers will likely choose new system components and/or alter their configuration; however, redesign is not limited to physical alteration of the system. Several other options may be more practical depending the system’s stage in the life cycle to address low risk-adjusted operational availability such as changes to maintenance programs and system supportability rather than on component and system reliability. A simple representative example implementation is provided to demonstrate the method and discussion of the potential implications for Navy ship availability are discussed. Potential future work is also discussed.

An Empirical Study on the Evolution of Design Smells

The evolution of software systems often leads to its architectural degradation due to the presence of design problems. In the literature, design smells have been defined as indicators of such problems. In particular, the presence of design smells could indicate the use of constructs that are harmful to system maintenance activities. In this work, an investigation on the nature and presence of design smells has been performed. An empirical study has been conducted considering the complete history of eight software systems, commit by commit. The detection of instances of multiple design smell types has been performed at each commit, and the analysis of the relationships between the detected smells and the maintenance activities, specifically due to refactoring activities, has been investigated. The proposed study evidenced that classes affected by design smells are more subject to change, especially when multiple smells are detected in the same classes. Moreover, it emerged that in some cases these smells are removed, and this occurs involving more smells at the same time. Finally, results indicate that smells removals are not correlated to the refactoring activities.

A Multiple-Model Reliability Prediction Approach for Condition-Based Maintenance

Numerous prognostic methods have been developed, aiming at predicting future system reliability with the highest possible accuracy. It is striking that the relation with the subsequent maintenance optimization process is generally overlooked, while it is important in practice. Additionally, almost all existing methods are based on a single degradation measure, and focus on systems with only one degradation and failure mode. In practice, however, multiple degradation measures are often available and needed to adequately predict future system degradation. Moreover, systems may suffer from various kinds of faults, all resulting in different degradation behaviors. To accommodate these properties, we establish a link between failure prognosis and maintenance optimization, and accordingly propose a multivariate multiple-model approach to system reliability prediction. We conclude that in the presence of multiple degradation modes and provided they are correctly identified, a multiple-model approach outperforms a single-model approach with respect to the prediction accuracy. Moreover, in the presence of multiple degradation and failure modes, overall predictions of the remaining useful life as generated by common prognostic approaches are not directly suited for maintenance decision making, as different kinds of system failures and maintenance activities are associated with different costs. In contrast, our approach yields conditional predictions of future system reliability, which much better suit the maintenance optimization process.

Predicting the unpredictable: Consideration of human and organisational factors in maintenance prognostics

Human performance is a major contributor to system performance and maintenance errors can have a significant influence on system reliability. However, existing reliability modelling approaches lack any methodologies to take account of maintenance actions in predicting system failure probability. The primary objective of this work is the development of a methodological framework to enable the integration of human and organisational factors (HOFs) as quantitative metrics within prognostics maintenance models. Inclusion of significant HOF metrics derived from performance shaping factors (PSFs) should reduce the predictive uncertainty of models developed for system failure probability estimation. This research investigates human error during maintenance activities as one variable contributing to system failure events. The hypothesis is that including HOF metrics derived from the performance shaping factors (PSFs) influencing maintenance tasks can reduce the predictive uncertainty of models developed for system failure probability estimation, provided that the PSFs are found to be significant predictors of the failure event. This research uses a case study from the biopharmaceutical industry to demonstrate the industrial application of the developed methodology. Regarding the case study, current field data is unable to isolate a process variable that can reliably predict sudden component failure. Technician error during installation and system maintenance activities is therefore investigated as a potential significant variable. This applied research explores how human errors can be discovered and accounted for within the reliability modelling process. The use of PSFs in this way forms one part of the development of data driven soft-sensors using a knowledge fusion approach. This soft sensor approach utilises a combination of quantitative and qualitative information in the form of laboratory tests, historical industrial process data, and metrics derived from human factors analysis, the combination of which is unique in the literature.

Migration of Virtual Machine to improve the Security of Cloud Computing

Cloud services help individuals and organization to use data that are managed by third parties or another person at remote locations. With the increase in the development of cloud computing environment, the security has become the major concern that has been raised more consistently in order to move data and applications to the cloud as individuals do not trust the third party cloud computing providers with their private and most sensitive data and information. This paper presents, the migration of virtual machine to improve the security in cloud computing. Virtual machine (VM) is an emulation of a particular computer system. In cloud computing, virtual machine migration is a useful tool for migrating operating system instances across multiple physical machines. It is used to load balancing, fault management, low-level system maintenance and reduce energy consumption. Virtual machine (VM) migration is a powerful management technique that gives data center operators the ability to adapt the placement of VMs in order to better satisfy performance objectives, improve resource utilization and communication locality, achieve fault tolerance, reduce energy consumption, and facilitate system maintenance activities. In the migration based security approach, proposed the placement of VMs can make enormous difference in terms of security levels. On the bases of survivability analysis of VMs and Discrete Time Markov Chain (DTMC) analysis, we design an algorithm that generates a secure placement arrangement that the guest VMs can moves before succeeds the attack.

PERANCANGAN SISTEM APLIKASI REQUEST MAINTENANCE TEKNIK DI PERGURUAN TINGGI RAHARJA

The development of information technology is growing rapidly, making the system change and develop until the need for the desired information can be accessed easily and accurately. Likewise with the operational Higher Education Prog who want the reliability of a system. In the case of operational procurement needs and improvements in Higher Education Prog until now carried out by the technical staff directly working on demand through telvon or speak directly, so inadequate as a reminder of the task request repairs and procurement activity reports Staff. Itcreates the application of the procurement system maintenance activity reports technique realized with the use of paper media as the media filing staff. But the idea of the system method has the disadvantage that slows performance in making the report. From it does research bermetodekan data collection system is running, observation, interviews and analysis of the proposed system CSF, prototyping and testing methods as the establishment of the proposed system is adequate as the best alternative solution of the existing problems.

Algorithmic development of life-cycle assessment: Application of urban water infrastructure systems in Iran

Urban infrastructure has an indisputable role in society's productivity. Since the residents' quality of life is dependent on the performance of infrastructure systems, devising procedures for monitoring such systems' current performance and predicting their future capabilities are necessary. Proper monitoring regime will take into account the remaining efficient performance time of the system and allocate appropriate maintenance and rehabilitation activities, thereby increasing the system productivity. Due to the vital role of water in people's lives and the immense size and complexity of urban water-distribution systems, the operation of urban water infrastructure is worthy of special attention in this regard. This paper presents an advanced algorithm for life-cycle assessment (LCA) of urban water infrastructure that is capable of determining the optimal time for system rehabilitation, taking into account both the economic and structural aspects of the system performance. The efficiency of the proposed approach is examined through the case study on a real water-distribution system in Iran. The system performance is simulated over its projected performance period via different breakage scenarios, and its efficiency is quantified by using a reliability-based indicator. The costs and benefits associated with the infrastructure performance are then evaluated, and its remaining useful operational life is estimated based on the projected reliability of the system and revenue impacts. The results of the case study imply that the developed method can be used to complement current practices as a proper tool for life cycle assessment of urban water infrastructure.

A Study on the Information System Maintenance Activities and Performance

It is important to maintain information system (IS) following the business and institutional change. Even if successfully developed information systems, we cannot gain the benefit from the systems without the proactive maintenance activities. However, the importance of IS maintenance has not been considered as much as the system development, and we don’t have any specific performance management structure. The objective of this study is to identify the relationship between IS maintenance activities and utilization. For empirical test of the hypothesis model, the sample data is collected from public information system sites. Results from multiple regression analysis reveal that proactive maintenance activities including IS maintenance cost increase, improving functionality, and enhancing ease of use have a causal effect on the IS utilization.               1980년대까지 업무자동화 도구로 인식되던 정보기술은 조직 전반의 업무 지원과 업무 프로세스 재설계와 연계하여 업무효율성 확보뿐만 아니라 전략적 자원으로서의 가치도 중요해지고 있다. 정보기술의 가치를 높이려면, 단순한 정보기술의 보유가 아니라 조직전략과 정보기술을 일치화하고 정보기술 성과를 관리할 수 있는 역량이 강조되고 있다[21].정보기술역량은 조직이 보유하고 있는 자원의 종류와 성격에 따라 조직의 성과가 차별화 된다는 자원기반이론에 기반하고 있다. 이는 이질적 조직자원의 중요성을 강조하는 것으로 차별화된 정보기술 역량을 가진 조직은 다른 조직과 차별화를 통하여 나은 성과를 획득할 수 있다. Parker et al[14]는 자원의 이질성과 자원의 부동성을 변수로 정보기술과 조직의 지속가능성 관계를 자원기반관점에서 설명하였다. 또한 Ross et al.[16]은 정보기술 인프라스트럭처를 조직의 정보기술 능력을 높일 수 있는 물리적 자산이면서 경쟁력의 원천으로 강조하였다. 이와 같은 자원기반이론은 조직의 경쟁우위 자원 획득과정을 제시하지는 못하지만 정보기술을 조직의 차별화된 자원으로 인식하도록 기여하였다.정보기술인프라 보유뿐만 아니라 사용자 참여가 정보시스템의 성공적 개발에 중요한 요인이며, 운영 단계에 적극적으로 참여하게 되면 정보시스템 이용에 긍정적 영향을 주어 종국에는 업무성과가 향상된다[21][6]. 사용초기에 정보시스템에 만족하더라도 시간이 경과하면서 시스템에 대한 만족도가 변하거나 시스템에서 오류가 발생할 수 있으며[17], 환경변화에 정보시스템이 유연하게 대응하지 못하면 생산성이 저하될 수 있다. 따라서 정보시스템의 성공적 개발만큼이나 정보시스템의 운영은 조직에서 매우 중요하다. 그리고 대부분의 조직에서 개발과정은 체계적으로 관리하지만 운영 및 유지보수는 체계적으로 관리되고 있지 못하는 실정이다[11][19]. 이에 비용과 성과에 더 많은 영향을 주는 운영성과에 대한 단순하면서도 객관적인 관리체계에 대한 연구가 필요하다.따라서 본 연구에서는 정보시스템의 운영 및 유지보수 활동의 수준과 운영성과와의 인과관계를 연구하였다. 구체적으로는 유지보수비용 절감노력과 함께, 기능활용도, 사용편의성 등 유지보수 품질 개선 노력이 업무성과로 이어지는지를 공공부문의 정보시스템 유지보수 데이터를 사용하여 실증하였다.

Infrastructure Communication Sensitivity Analysis of Wireless Sensor Networks

Sensitivity or importance analysis has been widely used for identifying system weaknesses and supporting system improvement and maintenance activities. Despite the rich literature on the sensitivity analysis of many mission-critical and safety-critical systems, no existing work has been devoted to wireless sensor networks (WSN). In this paper, we first analyze link and node importance with respect to the infrastructure communication reliability of WSN systems. The binary decision diagrams based algorithms are implemented to evaluate and compare three importance measures: structural importance measure, Birnbaum's measure, and criticality importance measure. The effects of node degree, choice of the destination node, data delivery models, as well as mission time on the importance analysis results are investigated through examples. Results from this work can facilitate the design, deployment, and maintenance of reliable WSN for critical applications. Copyright © 2015 John Wiley & Sons, Ltd.

Comparing Two Meta-Heuristic Approaches for Solving Complex System Reliability Optimization

Using meta-heuristic approaches to solve reliability and redundancy allocation problems (RRAP) has become attractive for researchers in recent years. In this paper, an optimization model is presented to maximize system reliability and minimize system cost simultaneously for multi-state weighted k-out-of-n systems. The model tends to optimize system design and maintenance activities over functioning periods that provides a dynamic modeling. A recently developed meta-heuristic approach imperialist competitive algorithm (ICA) and genetic algorithm (GA) are used to solve the model. The computational results have been compared to find out which approach is more appropriate for solving complex system reliability optimization models. It is shown that GA can find the better solution while ICA is a faster approach. In addition, an investigation is done on different parameters of the ICA.

A Comparative Study of Pre-Copy based Live Virtual Machine Migration Techniques

Virtual Machine(VM) migration is a powerful management technique that gives data center users the ability to adapt the placement of VMs in order to better satisfy performance objectives, improve resource utilization and communication locality, load balancing, mitigate performance hotspots, achieve fault tolerance, reduce energy consumption, and facilitate system maintenance activities. Live migration defines movement of VMs form one physical host to another without disrupting the client or application. One of the objectives of live migration is that it should have minimum migration time as well as downtime so that applications running on VM are suspended for negligible time. In this paper we focus on various pre-copy based live virtual machine migration techniques and compare them based on key performance metrics like downtime, total migration time, total no of bytes transferred, etc. Keywords: Virtualization; Virtual Machine; Live Migration; Downtime; Total Migration Time; Pre Copy

Integrated importance of multi-state fault tree based on multi-state multi-valued decision diagram

Integrated importance measures have been developed to study the effect of component state probabilities and state transition rates on the multi-state system performance, identifying the weakest component to facilitate the system maintenance and optimization activities. This article proposes an analytical method based on multi-state multi-valued decision diagram for computing the integrated importance measure values. Following a discussion of decomposition and physical meaning of integrated importance measures, the modeling method of multi-state multi-valued decision diagram based on multi-state fault tree analysis is introduced. A five-step integrated importance measure analysis approach based on multi-state multi-valued decision diagram is then proposed. Two case studies are implemented to demonstrate the presented methods. Complexity analysis shows that the multi-state multi-valued decision diagram–based method is more computationally efficient than the existing method using Markov–Bayesian networks.

A Knowledge-Based System Approach for Extracting Abstractions from Service Oriented Architecture Artifacts

Rule-based methods have traditionally been applied to develop knowledge-based systems that replicate expert performance on a deep but narrow problem domain. Knowledge engineers capture expert knowledge and encode it as a set of rules for automating the expert’s reasoning process to solve problems in a variety of domains. We describe the development of a knowledge-based system approach to enhance program comprehension of Service Oriented Architecture (SOA) software. Our approach uses rule-based methods to automate the analysis of the set of artifacts involved in building and deploying a SOA composite application. The rules codify expert knowledge to abstract information from these artifacts to facilitate program comprehension and thus assist Software Engineers as they perform system maintenance activities. A main advantage of the knowledge-based approach is its adaptability to the heterogeneous and dynamically evolving nature of SOA environments.

A genetic algorithm approach for production scheduling with mould maintenance consideration

The traditional approach for maintenance scheduling concerns single-resource (machine) maintenance during production which may not be sufficient to improve production system reliability as a whole. Besides, in the literature many researchers schedule maintenance activities periodically with fixed maintenance duration. However, in a real manufacturing system maintenance activities can be executed earlier and the maintenance duration will become shorter since less time and effort are required. A practical example is that in a plastic production system, the proportion of machine-related downtime is even lower than mould-related downtime. The planned production operations are usually interrupted seriously because of the mismatch among the maintenance periods between injection machine and mould. In this connection, this paper proposes to jointly schedule production and maintenance tasks of multi-resources in order to improve production system reliability by reducing the mismatch among various processes. To integrate machine and mould maintenance tasks in production, this paper attempts to model the production scheduling with mould scheduling (PS-MS) problem with time-dependent deteriorating maintenance schemes. The objective of this paper is to propose a genetic algorithm approach to schedule maintenance tasks jointly with production jobs for the PS-MS problem, so as to minimise the makespan of production jobs.

Determining maintenance system requirements by viewpoint of reliability and lean thinking: a MODM approach

PurposeThe purpose of this paper is to formulate a model which not only determines minimum level of maintenance requirements but also satisfies expected reliability level.Design/methodology/approachA multi‐objective decision making (MODM) model has been developed by viewpoint of decreasing wastes and increasing system reliability. Wastes that have been minimized are maintenance requirements (i.e. labor, spare parts, reserve system and productive maintenance activities) and maintenance system reliability that has been maximized is a function of maintenance requirements. This paper proposed goal programming model for decision‐making aid and a real case in an existing Iranian automobile manufacturing company was studied.FindingsOutput of the proposed model was optimum level of maintenance requirements which satisfies the expected reliability level. For example, outputs of model for man hour approximately are the same as available maximum level and inspection, service and test and adjustment activities are not necessary 12 times a year for all the machineries.Practical implicationsThis model is useful for managers because they could use that in any maintenance systems and it would ensure them in achieving minimum level of maintenance requirements and the expected reliability level.Originality/valueSince lean concept has appeared, many works have been done on decreasing or even eliminating of waste such as extra inventory. Although these studies have not taken into account expected reliability seriously, this paper considers these two issues together.

EFFECTIVE COMPONENT IMPORTANCE ANALYSIS FOR THE MAINTENANCE OF SYSTEMS WITH COMMON-CAUSE FAILURES

In this paper, we consider the component importance analysis of coherent systems subject to common-cause failures. The purpose of component importance analysis is to obtain information regarding a component's contribution or importance to the system reliability. The results from the component importance analysis are key contributors to the system design, tuning, and maintenance activities. Various measures have been proposed for the component importance analysis, but little work has been done to compare their performance. In this research, we investigate and compare a set of nine existing importance measures and select the most informative and appropriate one for guiding the system maintenance activity. An important concern in the traditional fault tree reliability analysis, common-cause failures, is also considered in the component importance analysis. An example is designed and analyzed to show the selection process and to illustrate our efficient method for considering the effects of common-cause failures in the component importance analysis.