Critical infrastructures and the tragedy of the commons dilemma: Implications from institutional restructuring on reliability and safety

Through the influence of neoliberal ideas, many critical infrastructures that used to be under public ownership have been opened up for market competition. Using the Swedish railway system as a case, this paper empirically explores whether such reforms have given rise to common‐pool resource problems, and discusses possible implications. The results show that institutional restructuring has created challenges related to balancing the use of the infrastructure with a sufficient level of maintenance. The paper concludes that the main value of analysing critical infrastructures from the perspective of common‐pool resources is the possibility of juxtaposing the way organizational and institutional interactions across scales generate both short‐term gains and long‐term negative side effects influencing reliability and safety.     

Designing Infrastructures: Dilemmas of Design and the Reliability of Critical Infrastructures

Critical infrastructures (CIs) are ‘balky systems’ of highly diverse, networked components with such high performance variations among them that there are few modal behaviors that characterize these infrastructures as whole systems. Consequently, they are under‐determined with respect to design principles and the control variables available to operators. These features raise significant reliability challenges in the management of CIs. In particular, formal design strategies increasingly applied to these infrastructures threaten to undermine the skills and cognitive capacities of control operators and middle‐level ‘reliability professionals’ to manage them reliably and safely. We investigate these challenges and propose new design principles to protect and enhance high reliability management in CIs.     

Reliability Consequences of Liberalization in the Electricity Sector: Existing Research and Remaining Questions

The generation, transmission and distribution of energy are among the most vital prerequisites for the functioning of modern societies. Since the early 1990s, the energy sectors of Western societies have been through a process of institutional restructuring, where large state‐owned monopolies have been divided into several independent organizations. Also, the organizations responsible for providing energy, like most other industrial organizations today, have made increasing use of outsourcing strategies. Taken together, these developments represent a significant change in the framework conditions for the energy sector. How this development affects the reliability of energy supply and the capacity for effective crisis management is an important question from both a research perspective as well as from a societal point of view. This article reviews the current literature on these issues, aiming to identify research gaps in the existing literature. Several research gaps are identified.     

High Reliability and the Management of Critical Infrastructures

Organisation theorists and practitioners alike have become greatly interested in high reliability in the management of large hazardous technical systems and society's critical service infrastructures. But much of the reliability analysis is centred in particular organisations that have command and control over their technical cores. Many technical systems, including electricity generation, water, telecommunications and other “critical infrastructures,” are not the exclusive domain of single organisations. Our essay is organised around the following research question: How do organisations, many with competing, if not conflicting goals and interests, provide highly reliable service in the absence of ongoing command and control and in the presence of rapidly changing task environments with highly consequential hazards? We analyse electricity restructuring in California as a specific case. Our conclusions have surprising and important implications both for high reliability theory and for the future management of critical infrastructures organised around large technical systems.     

A Semi-Lagrangian CIP Fluid Solver without Dimensional Splitting

In this paper, we propose a new constrained interpolation profile (CIP) method that is stable and accurate but requires less amount of computation compared to existing CIP‐based solvers. CIP is a high‐order fluid advection solver that can reproduce rich details of fluids. It has third‐order accuracy but its computation is performed over a compact stencil. These advantageous features of CIP are, however, diluted by the following two shortcomings: (1) CIP contains a defect in the utilization of the grid data, which makes the method suitable only for simulations with a tight CFL restriction; and (2) CIP does not guarantee unconditional stability. There have been several attempts to fix these problems in CIP, but they have been only partially successful. The solutions that fixed both problems ended up introducing other undesirable features, namely increased computation time and/or reduced accuracy. This paper proposes a novel modification of the original CIP method that fixes all of the above problems without increasing the computational load or reducing the accuracy. Both quantitative and visual experiments were performed to test the performance of the new CIP in comparison to existing fluid solvers. The results show that the proposed method brings significant improvements in both accuracy and speed.     

The Commoditization of Societal Safety

New public management has led to major institutional changes in the sectors operating critical infrastructures. The previously integrated utility companies have been dismantled and are now run, regulated and organized more like private entities. This paper proposes two concepts that may aid the analysis of these organizational changes and the consequences they may have on societal safety. Commoditization refers to the process where work is sought transformed into atomistic standardized products to be ordered on a market. Modularization refers to the creation of discrete entities coordinated by market mechanisms and standardized interfaces. We argue that commoditization of work and modularization of organizational entities pose challenges to some of the informal characteristics of high‐reliability organization's, with recognized importance especially for crisis management. This is illustrated by examples from Norwegian electricity network operators.     

A hybrid methodology for restructuring decision of a manufacturing system: A case study

The output performance of a manufacturing system depends on its operational continuity. However, a manufacturing system can stop for a short time or it can be out of service for a long time due to crucial problems such as poor performance of old machines, unexpected breakdowns or faulty plant and system design. Many firms try to restructure their manufacturing systems to avoid these crucial problems and to be more efficient, profitable and better organized. However, the decision to begin the process of restructuring is a difficult and critical choice for most decision makers due to the fact that the decision threshold of the process is ambiguous. This paper proposes a hybrid methodology for the decision makers who will decide on restructuring a manufacturing system. The proposed methodology provides crucial information for the decision makers combining fuzzy logic approach and reliability analysis.     

Protecting Europe's Critical Infrastructures: Problems and Prospects

The European Union has become increasingly involved with protecting the security and safety of European citizens. The latest addition to this new policy space is critical infrastructure protection (CIP) at the EU level. A central role for the EU in guarding against infrastructural breakdowns and preparing for failures may seem self‐evident. In reality, the precise nature of such a role remains unclear. Moreover, enthusiastic rhetoric is not always matched by firm action. This article surveys what the EU has in place in terms of CIP and identifies outstanding issues for debate.     

Growth strategies in creative industries

In recent years there has been increased emphasis, in both academic and political arenas, on the economic importance of the creative industries (CIs). As a result, policymakers are increasingly looking to the CIs as a source of potential growth. The literature on CIs suggests that these industries are predominantly content based rather than market based, with artistic priorities taking precedence over business concerns. This research examines growth strategies in the CIs using qualitative and quantitative methods. An in‐depth case study of 23 firms in CIs suggests that these firms tend to view growth as a secondary goal compared to the goal of creative output. The case study further yields the proposition that firms in the CIs can benefit from adopting what we refer to as an accordion growth strategy, in which firms grow and shrink to accommodate artistic content as well as in response to external forces. Statistical analysis of survey data confirms that firms in the CIs are less likely to have ambitions to grow and more likely to adopt an accordion growth strategy than firms in technology industries. These findings suggest that the policy emphasis on growth in the CIs might be misguided and should allow for alternating periods of growth and shrinkage.     

Data aggregation in constructing composite indicators: A perspective of information loss

Composite indicators (CIs) have been widely accepted as a useful tool for performance comparisons, public communication and decision support in a wide spectrum of fields, e.g. economy, environment and knowledge/information/innovation. The quality and reliability of a CI depend heavily on the underlying construction scheme where data aggregation is a major step. This paper analyzes the data aggregation problem in CI construction from the point of view of information loss. Based on the “minimum information loss” principle, the distance-based and entropy-based aggregation models for constructing CIs are presented. The entropy-based aggregation model has also been extended to deal with qualitative data. It is shown that the proposed aggregation models have close relationships with several popular MCDA aggregation methods in CI construction, although our proposed models seem to be more flexible while more complex in application. Two case studies are presented to illustrate the use of the proposed aggregation models.     

Dynamic characteristics of flying head slider with ultra thin spacing (CIP method and linearized method)

The cubic interpolated propagation (CIP) method, which is an effective numerical scheme for differential equations that include advection and nonadvection terms, is employed for the dynamic analyses of ultra thin gas film lubrication using the molecular gas-film lubrication equation. First, pressure generation caused by the running wavy disk under the fixed slider was analyzed by the CIP method and is found to agree well with the analytical solution for the running wavy disk with a small amplitude. 2-DOF slider dynamics with the spacing of several tens of nanometers caused by a running disk with projections were investigated by the CIP method and the linearized solutions, which show that both results agree well with each other and the CIP method is promising scheme for slider dynamics even in the near-contact region.     

Achieving maximum reliability in fault tolerant network design for variable networks

The objective of this paper is to present a novel method to achieve maximum reliability for fault tolerant optimal network design when network has variable size. Reliability calculation is most important and critical component when fault tolerant optimal network design is required. A network must be supplied with certain parameters that guarantee proper functionality and maintainability under worse situations. Many alternative methods for measuring reliability have been stated in literature for optimal network design. Most of these methods mentioned in literature for evaluating reliability may be analytical and simulation based. These methods provide significant way to compute reliability when network has limited size. Also, significant computational effort is required for growing variable sized networks. Therefore, a novel neural network method is presented to achieve significant high reliability for fault tolerant optimal network design in highly growing variable networks. This paper computes reliability with improved learning rate gradient descent based neural network method. The result shows that improved optimal network design with maximum reliability is achievable by novel neural network at manageable computational cost.     

Incorporating sustainable criteria in a dynamic multi-objective recommendation planning tool for a continuous manufacturing process: A dairy case study

The activity of scheduling the production plan with the aim of achieving an optimal criterion has been explored in literature for several manufacturing sectors, in particular when it comes to solving scheduling NP-complete problems. In Dairy Manufacturing, determining an optimum criterion for the scheduling process has numerous internal and external challenges due to the complexity of this environment.The initial stages in the Dairy process are characterised by a continuous manufacturing environment and specific operational issues are observable: interruptions for the accomplishment of Cleaning-In-Place (CIP); a short raw material lifespan which demands a fast processing rate; and the stochastic raw material supply variation. By highlighting these three aspects, a critical trade-off emerges: CIP cycle-times heavily reduce the processing capacity, whereas the raw material processed requires an increase in available capacity due to the impact of seasonality, perishability and stochastic deliveries. Therefore, the scheduling plan must be dynamically readapted based on the current inventory, volume and frequency supplied, CIP cycle-times, maximum equipment running hours and downstream capacities.The aim of this research is to develop an integrated approach for generating equipment schedules under supply uncertainty typically observed in the dairy sector where criteria of sustainability are effortlessly incorporated for an improved decision-making process. An efficient Multi-objective Algorithm (MOA) combining conflicting key performance metrics such as minimising Work-In-Process (WIP), maximising Service Level Agreement (SLA), Utilisation and Energy consumption is proposed.The novelty consists of the ability to dynamically select trade-off criteria and visualise the optimum production plan according to the conditions defined by the decision-maker. The appropriate schedules are presented in a Pareto Frontier graph highlighting the entire non-dominance region according to the volume and frequency supplied. Even though sustainability metrics are usually ignored during production plan definitions, namely when a weak correlation between both environmental and profitable criteria is identified, the results demonstrate improved performance when both sustainable approaches are well explored.     

Critical Infrastructures,High Reliability and Their Enemy,Economism

This Forum contribution explains why economism – a form of bad economics – has become the enemy of reliable critical infrastructures and what must be done to remedy this. The perspective here is critical, but moves beyond critique to recommendation and proposals. The suggestions centre around taking advantage of the unique expertise of reliability professionals in infrastructures to catch big mistakes before they happen in real time. While economists call for greater efficiencies in critical service provision (see especially the long‐standing New Public Management literature), the most underutilized resource we have as a society are these reliability professionals. Without their expertise we would not have the infrastructure stability necessary for markets to function in the first place.     

A modified densenet approach with nearmiss for anomaly detection in industrial control systems

Multimedia Tools and Applications - The safety of Industrial Control Systems (ICSs) is of vital importance especially for critical infrastructures (CIs) that cause economic losses as well as...     

一种融合粗糙集与灰模的装备故障预测方法

结合粗糙集理论和灰色系统理论对不精确信息处理的优势,文中提出一种融合粗糙集理论与GM(1,1)灰色预测模型的故障预测方法,先运用粗糙集的属性约简算法对故障诊断决策表进行约简,推出最优诊断规则,再利用GM(1,1)灰色预测模型对约简决策表中的各条件属性测试值计算得到其预测值,从而代回约简的诊断决策表进行故障预测,最后在某型机载电台装备中以某一故障为例进行应用验证,结果表明故障预测效率和精度都较高,从而为提高装备的可靠性和维修性提供依据.     

An architecture framework for an adaptive extensible processor

To improve the performance of embedded processors, an effective technique is collapsing critical computation subgraphs as application-specific instruction set extensions and executing them on custom functional units. The problem with this approach is the immense cost and the long times required to design a new processor for each application. As a solution to this issue, we propose an adaptive extensible processor in which custom instructions (CIs) are generated and added after chip-fabrication. To support this feature, custom functional units are replaced by a reconfigurable matrix of functional units (FUs). A systematic quantitative approach is used for determining the appropriate structure of the reconfigurable functional unit (RFU). We also introduce an integrated framework for generating mappable CIs on the RFU. Using this architecture, performance is improved by up to 1.33, with an average improvement of 1.16, compared to a 4-issue in-order RISC processor. By partitioning the configuration memory, detecting similar/subset CIs and merging small CIs, the size of the configuration memory is reduced by 40%.     

Determining critical power equipment inventory using extreme value approach and an auxiliary Poisson model

This paper is devoted to the establishment of reasonable levels of critical power equipment inventory using available historical data and strict legal requirements for reliable electrical power supply. Several models, including an Extreme Value Theory and a Homogeneous Poisson model, are used with results compared to provide a probabilistic formulation of suggested inventory. Several procedures are provided to establish proper inventory levels of critical power equipment. Simplifications are suggested for automating the calculation process for large samples. The presented approaches have a wide scope of industrial applicability, and can be applied to different types of critical equipment. Mathematical background is provided to assist practitioners that do not have extensive knowledge of probabilistic tools such as Extreme Value Theory or Homogeneous Poisson Process models.     

A critical review of approaches to human reliability analysis

This paper provides a critical analysis of four major approaches to human reliability assessment: THERP, the use of qualitative models of human performance, simulation methods, and methods based on classical reliability theory. Methodologically and conceptually, these approaches are more representative of a multidimensional than unified perspective to the problem of human reliability analysis and are considered to encompass many of the other methods that have been proposed. Recent developments in each of these areas and the growing concern for the consequences of human error in highly complex systems requires that these approaches be sufficiently understood in order to identify both their strengths and their shortcomings. Although no single approach is advocated, this review intends to provide insights that could suggest improvements to these methods as well as aid the analyst in selecting the approach most optimal for the situation in question. In addition, critical research needs are identified and summarized.     

Wafer-scale integration using restructurable VLSI

Results from a restructurable very large scale integration (RVLSI) program show the viability of using a laser to restructure wafer-scale circuits for customization and defect avoidance. Wafer-scale circuits are built with a standard integrated circuit fabrication process when the diffused-link restructuring device is used. Nine wafer-scale systems that have been built using the RVLSI technique are described. It is shown that the laser interconnection process has high yield and provides the high reliability of monolithic circuitry. The technology is well suited to signal processing systems, which characteristically use many replications of a small number of circuits and often have modest interconnection requirements