Optimal maintenance time for imperfect maintenance actions on repairable product

This paper develops a maintenance strategy for repairable products that combines imperfect maintenance actions at pre-scheduled times and minimal repair actions for failures. Under a power law process of failures, an expected total cost is developed that involves the sum of the total cost of imperfect preventive maintenances and the expected total cost of minimal repairs. Moreover, a searching procedure is provided to determine the optimal maintenance schedule within a finite time span of warranty. When the parameters of the power law process are unknown, the accuracy of the estimated maintenance schedule is evaluated based on data through an asymptotic upper bound for the difference of the true expected total cost and its estimate. The proposed method is applied to an example regarding the maintenance of power transformers and the performance of the proposed method is investigated through a numerical study. Numerical results show that the proposed maintenance strategy could save cost whether an imperfect maintenance action or the perfect maintenance action is implemented.     

Mental models and software maintenance

Understanding how a program is constructed and how it functions are significant components of the task of maintaining or enhancing a computer program. We have analyzed vidoetaped protocols of experienced programmers as they enhanced a personnel data base program. Our analysis suggests that there are two strategies for program understanding, the systematic strategy and the as-needed strategy. The programmer using the systematic strategy traces data flow through the program in order to understand global program behavior. The programmer using the as-needed strategy focuses on local program behavior in order to localize study of the program. Our empirical data show that there is a strong relationship between using a systematic approach to acquire knowledge about the program and modifying the program successfully. Programmers who used the systematic approach to study the program constructed successful modifications; programmers who used the as-needed approach failed to construct successful modifications. Programmers who used the systematic strategy gathered knowledge about the causal interactions of the program's functional components. Programmers who used the as-needed strategy did not gather such causal knowledge and therefore failed to detect interactions among components of the program.     

Interactive and diagnostic uses of management control systems in IS projects: Antecedents and their impact on performance

We attempted to determine how formal management control systems (MCS) are used by project managers in IS development (ISD) contexts. This involved investigating the antecedents of two types of project MCS use (interactive and diagnostic), and their direct and moderated impact on project performance. PLS analysis of data collected in a survey of 93 projects indicated that project managers’ level of discretion positively affected their level of interactive use of project MCS but did not influence their diagnostic use. Our findings also showed that interactive use of MCS enhanced performance when task uncertainty (task novelty and complexity) of an ISD was high, but worsened it when task uncertainty was low. Finally, diagnostic use of MCS apparently increased project performance when an ISD task uncertainty was low, but did not reduce it when task uncertainty was high. Overall, these results were stable across different size projects.     

Optimal lot sizing with maintenance actions and imperfect production processes

Porteus (1986) explored an economic order quantity model with imperfect production processes that the approximate lot size is derived. Basically, he dealt with the lot size problem is rather meaningful. However, for mathematical simplicity, he adopted a truncated Taylor series expansion to present the approximate expected total cost function that results in overvalue of expected total cost. In this paper, we extend Porteus (1986) to present the optimal lot size model for defective items with a constant probability when the system is out-of-control and taking the maintenance cost into account. We show that there exists a unique optimal lot size such that the expected total cost is minimised. In addition, the bounds of optimal lot size are provided to develop the solution procedure. Finally, numerical examples are given to illustrate the theoretical results and compare optimal solutions obtained by using our approach and Porteus's approach. Numerical results show that our approach is better.     

Error sources and their impact on c-velocity methods

We propose an efficient method for detecting 3D planes from a moving uncalibrated camera. It assumes only a 3D translation for the egomotion. The original idea is to get around the dependence between the 2D motion field, the depth (i.e. scene structure) and the ignored egomotion. Relations are established between predicted iso-velocity curves and 3D surface parameters in eliminating the depth variable from equations. Surface assessment is performed within a simple velocity voting-space: a 3D surface, like a given plane, emerges as a curve, like a parabola. Experimentations validate our approach for several applications including automatic driver assistance, showing a surprising robustness. The aim of the present paper is to analyze this robustness. Five main perturbations are focused on and their influence on the plane detection process is studied in details.     

The impact of IS sourcing type on service quality and maintenance efforts

The purpose of our work was to examine the effectiveness of information system sourcing from the perspective of service quality and maintenance efforts. We empirically found that there were significant differences in service quality, but not in maintenance efforts, between insourced and outsourced systems. We also found that the level of service quality and maintenance efforts across system sourcing types varied as a system grew older. Our results suggested that outsourcing may not always be the correct choice for reducing costs and increasing efficiency over the long term. This work also considered the effect of issues like productivity gains from a reduced need for system maintenance and the cost savings achieved by choosing sourcing options wisely.     

Atomic actions, and their refinements to isolated protocols

Inspired by the properties of the refinement development of the Mondex Electronic Purse, we view an isolated atomic action as a family of transitions with a common before-state, and different after-states corresponding to different possible outcomes when the action is attempted. We view a protocol for an atomic action as a computation DAG, each path of which achieves in several steps one of the outcomes of the atomic action. We show that in this picture, the protocol can be viewed as a relational refinement of the atomic action in a number of ways. Firstly, it yields a ‘big diagram’ simulation à la ASM. Secondly, it yields a ‘small diagram’ simulation, in which the atomic action is synchronised with an individual step along each path through the protocol, and all the other steps of the path simulate skip. We show that provided each path through the protocol contains one step synchronised with the atomic action, the choice of synchronisation point can be made freely. We describe the relationship between such synchronisations and forward and backward simulations. We relate this theory to serialisations of system runs containing multiple interleaved transactions, showing how the clean picture of the refinement of an isolated atomic action to an isolated protocol becomes obscured by the details of the interleaving. In effect, the fact that protocols are typically executed by a number of co-operating agents, not all of which embark on executing the protocol at the same moment, results in ‘ragged starts’ and ‘ragged ends’ to protocol instantiations, leading to potential overlaps between unrelated protocol instances that the theory must handle. We show how existing Mondex refinements embody the ideas developed, and describe a mechanical verification of the results presented.     

Physics-based modeling strategies for diagnostic and prognostic application in aerospace systems

This paper presents physics-based models as a key component of prognostic and diagnostic algorithms of health monitoring systems. While traditionally overlooked in condition-based maintenance strategies, these models potentially offer a robust alternative to experimental or other stochastic modeling data. Such a strategy is particularly useful in aerospace applications, presented in this paper in the context of a helicopter transmission model. A lumped parameter, finite element model of a widely used helicopter transmission is presented as well as methods of fault seeding and detection. Fault detection through diagnostic vibration parameters is illustrated through the simulation of a degraded rolling-element bearing supporting the transmission’s input shaft. Detection in the time domain and frequency domain is discussed. The simulation shows such modeling techniques to be useful tools in health monitoring analysis, particularly as sources of information for algorithms to compare with real-time or near real-time sensor data.     

Soft factors and their impact on time to market

Time to market is considered to be one of the most important quality attributes for an organization to retain its competitive edge. Soft factors are at least as important as technical issues in improving and controlling the time to market. Soft factors are used as a collective term for factors that are difficult to quantify exactly, i.e. non-technical aspects. Based on the identified importance of the soft factors, a method, incorporating the soft factors, has been developed to increase the predictability of time to market. The method consists of three main parts: model development, model usage and model maintenance. The proposed method is general, while the actual model is primarily useful for the organization for which data have been collected. The objective is two-fold: first to prevent a general method of incorporating soft factors into the prediction of the time to market, and secondly to identify a set of critical soft factors for the organization in which data have been collected. The model is based on data collection from 12 large software projects. Time to market, effort (manhours) and a grade for ten soft factors have been collected. The model is derived from a set of eight projects and it is evaluated using the remaining four projects. The method is shown to be superior to the prediction made without taking the soft factors into account. The need to maintain the model is stressed as the model will evolve with time through new experiences gained. The proposed method can be applied in practice to help software engineers and managers to plan and control time to market and soft factors in software projects.     

Generation maintenance scheduling based on multiple objectives and their relationship analysis

In a market environment of power systems, each producer pursues its maximal profit while the independent system operator is in charge of the system reliability and the minimization of the total generation cost when generating the generation maintenance scheduling （GMS）. Thus, the GMS is inherently a multi-objective optimization problem as its objectives usually conflict with each other. This paper proposes a multi-objective GMS model in a market environment which includes three types of objectives, i.e., each producer＇s profit, the system reliability, and the total generation cost. The GMS model has been solved by the group search optimizer with multiple producers （GSOMP） on two test systems. The simulation results show that the model is well solved by the GSOMP with a set of evenly distributed Pareto-optimal solutions obtained. The simulation results also illustrate that one producer＇s profit conflicts with another one＇s, that the total generation cost does not conflict with the profit of the producer possessing the cheapest units while the total generation cost conflicts with the other producers＇ profits, and that the reliability objective conflicts with the other objectives.     

Multiagent simulation subsystem of diagnostic complexes based on device models

Application of the multiagent approach in diagnostic systems based on device behavior models is considered. The architecture of a multiagent diagnostic system, as well as the semantic and spatial methods of the distribution of a device model among the agents, is presented. Working algorithms for a simulation subsystem are given and the efficiency of the multi-agent approach in diagnostic systems based on device behavior models is estimated. The described approach is tested for the semantic distribution of a device model among the agents. Our results confirm the efficiency of applying the multi-agent approach in diagnostic systems based on device behavior models.     

The impact of blockchain on business models in banking

Information Systems and e-Business Management - Blockchain technology is predicted to reshape existing business models of the financial services industry. But although blockchain is often seen as a...     

ARMA models,their Kronecker indices and their McMillan degree

This paper highlights some difficulties with the use of ARMA models with leading unit coefficient matrix in system identification. It is shown that the McMillan degree of such models is not in any easy way related to the row degrees of the polynomial factors of the ARMA model. A rank test is given for the McMillan degree of such models and it is shown that this degree will generically be a multiple of the dimension of the observation vector.     

Microcomputers and their impact on local-government operations: Position paper

The purpose of this paper is to set the stage for a productive workshop that will contribute to recognition of, and solutions to, issues and concerns arising from the expected impact of' microcomputers in the local-government environment.     

Semi-parametric marginal models for hierarchical data and their corresponding full models

Semi-parametrically specified models for multivariate, longitudinal, clustered, multi-level, and other hierarchical data, particularly for non-Gaussian outcomes, are ubiquitous because their parameters can most often be conveniently estimated using the important class of generalized estimating equations (GEE). The focus here is on marginal models, to be understood as models that condition neither on random effects nor on other outcomes, but merely on fixed covariates. In spite of their well-deserved popularity, concern could be raised as to whether such models can always be viewed as a partially specified version of a model with full distributional assumptions, or rather whether such a parent simply does not exist. It is shown, through the use of the hybrid marginal–conditional models, that the answer is affirmative. For conventional GEE with a working correlation structure, the Bahadur model is sometimes considered to be the natural parent candidate, but we show that this is a misconception. The result presented here, which is conceptual in nature, is valid whenever the exponential family is used for the semi-parametric specification, or when a straightforward transformation to an exponential family member is possible, implying validity for broad classes of binary, ordinal, nominal, and count data. The result is illustrated in the context of trivariate binary data. Further, as an illustration, many of the models considered are applied to data from a developmental toxicity study.     

The impact of UML documentation on software maintenance: an experimental evaluation

The Unified Modeling Language (UML) is becoming the de facto standard for software analysis and design modeling. However, there is still significant resistance to model-driven development in many software organizations because it is perceived to be expensive and not necessarily cost-effective. Hence, it is important to investigate the benefits obtained from modeling. As a first step in this direction, this paper reports on controlled experiments, spanning two locations, that investigate the impact of UML documentation on software maintenance. Results show that, for complex tasks and past a certain learning curve, the availability of UML documentation may result in significant improvements in the functional correctness of changes as well as the quality of their design. However, there does not seem to be any saving of time. For simpler tasks, the time needed to update the UML documentation may be substantial compared with the potential benefits, thus motivating the need for UML tools with better support for software maintenance.