Infrastructure information management of bridges at local authorities in the UK

Behind the largest infrastructure construction projects currently underway is a system of managing information known as Building Information Modelling (BIM). This represents a collaborative approach to civil engineering and makes use of advances in computer technology to link seamlessly many information repositories together across organisational boundaries. Alongside the developments in BIM, the world of asset management has also seen a major leap forward with the release of ISO 5500x – the family of international standards for asset management. This is now being adopted by many industries – particularly those in the infrastructure sectors – to maximise the value which is returned from their assets. In addition, the Highways Maintenance Efficiency Programme has released a guidance for highway authorities wishing to improve their asset management systems. However, infrastructure managers in local authorities such as county councils are significantly less engaged in both of these developments than their counterparts in strategic infrastructure networks. This paper presents the findings of a study of the ‘information system landscape’ at local authorities from across England, UK. The study reveals a number of recurring information management challenges that are frequently present. The paper finally provides a number of recommendations with specific reference to information management and encourages councils to consider adopting the standards. EPSRC/Innovate U

Evaluation criteria for information quality research

Evaluation of research artefacts (such as models, frameworks and methodologies) is essential to determine their quality and demonstrate worth. However, in the information quality (IQ) research domain there is no existing standard set of criteria available for researchers to use to evaluate their IQ artefacts. This paper therefore describes our experience of selecting and synthesising a set of evaluation criteria used in three related research areas of information systems (IS), software products (SP) and conceptual models (CM), and analysing their relevance to different types of IQ research artefact. We selected and used a subset of these criteria in an actual evaluation of an IQ artefact to test whether they provide any benefit over a standard evaluation. The results show that at least a subset of the criteria from the other domains of IS, SP and CM are relevant for IQ artefact evaluations, and the resulting set of criteria, most importantly, enabled a more rigorous and systematic selection of what to evaluate.This is the author accepted manuscript. The final version is available from InderScience via https://doi.org/10.1504/IJIQ.2016.1000404

Federated Learning for Collaborative Prognosis

Modern industrial assets generate prodigious condition monitoring data. Various prognosis techniques can use this data to predict the asset’s remaining useful life. But the data in most asset fleets is distributed across multiple assets, bound by the privacy policies of the operators, and often legally protected. Such peculiar characteristics make data-driven prognosis an interesting problem. In this paper, we propose Federated Learning as a solution to the above mentioned challenges. Federated Learning enables the manufacturer to utilise condition monitoring data without moving it away from the corresponding assets. Concretely, we demonstrate Federated Averaging algorithm to train feed-forward, and recurrent neural networks for predicting failures in a simulated turbofan fleet. We also analyse the dependence of prediction quality on the various learning parameters.1. Siemens Industrial Turbomachinery U

Imperfect Preventive Maintenance Policies With Unpunctual Execution.

Traditional maintenance planning problems usually presume that preventive maintenance (PM) policies will be executed exactly as planned. In reality, however, maintainers often deviate from the intended PM policy, resulting in unpunctual PM executions that may reduce maintenance effectiveness. This article studies two imperfect PM policies with unpunctual executions for infinite and finite planning horizons, respectively. Under the former policy, imperfect PM actions are periodically performed and the system is preventively replaced at the last PM instant. The objective is to determine the optimal number of PM actions and associated PM interval so as to minimize the long-run average cost rate. While the latter policy specifies that a system is subject to periodic PM activities within a finite planning horizon and there is no PM activity at the end of the horizon. The aim is then to identify the optimal number of PM activities to minimize the expected total maintenance cost. We discuss the modeling and optimization of the two unpunctual PM policies, and then explore the impact of unpunctual executions on the optimal PM decisions and corresponding maintenance expenses in an analytical or numerical way. The resulting insights are helpful for practitioners to adjust their PM plans when unpunctual executions are anticipated

Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

Systems engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address systems engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in the industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant

A vulnerability-based approach to human-mobility reduction for countering COVID-19 transmission in London while considering local air quality

An ecologic analysis was conducted to explore the correlation between air pollution, and COVID-19 cases and fatality rates in London. The analysis demonstrated a strong correlation (R2>0.7) between increment in air pollution and an increase in the risk of COVID-19 transmission within London boroughs. Particularly, strong correlations (R2>0.72) between the risk of COVID-19 fatality and NO2 and PM2.5 pollution concentrations were also found. Although this study assumed the same level of air pollution across a particular London borough, it demonstrates the possibility to employ air pollution as an indicator to rapidly identify the vulnerable regions within a city. Such an approach can inform the decisions to suspend or reduce the operation of different public transport modes within a city. The methodology and learnings from the study can thus aid public transport to respond to the COVID-19 outbreak by adopting different levels of human-mobility reduction strategies based on the vulnerability of a given region

Towards the future-proofing of UK infrastructure

Ensuring long-term performance from key infrastructure is essential to enable it to serve society and to maintain a sustainable economy. The future-proofing of key infrastructure involves addressing two broad issues: (i) resilience to unexpected or uncontrollable events (e.g., extreme weather events); (ii) adaptability to required changes in structure and/or operations of the infrastructure in the future. Increasingly, infrastructure owners, designers, builders, governments and operators are being required to consider possible future challenges as part of the life cycle planning for assets and systems that make up key infrastructure. A preliminary study is reported here that aimed at exploring the following questions related to infrastructure (systems): what does ‘future-proofing’ of infrastructural assets mean? Why and when should critical infrastructure be future-proofed? How can infrastructure assets (systems) be prepared for uncertain future events? How can future-proofing considerations be incorporated into infrastructure asset management practices? To seek answers to the above questions, two industrial workshops were conducted that brought together leading practitioners in the UK infrastructure and construction sectors, along with government policymakers. This paper captures lessons learnt from the workshops and proposes a framework for linking future-proofing into asset management considerations. Case studies of Dawlish railway and Heathrow airport are also presented. The authors would like to acknowledge the Centre for Smart Infrastructure & Construction, EPSRC (Grant EP/K000314/1), Innovate UK and the industrial partners, which collectively funded this project. The authors are thankful to the CSIC industrial partners involved in the futureproofing project. The authors are also thankful to the speakers and delegates from London Underground, Costain, UCL, IBM, Crossrail, John Dora Consulting, Heathrow, Cementation Skanska, CIRIA, Network Rail, Arup, Highways Agency, Atkins, Halcrow/CH2M, Lang O’ Rourke, Lend Lease, Infrastructure UK, Committee on Climate Change and CSIC, who attended the CSIC workshop(s) on infrastructure futureproofing. The authors are also thankful to the following companies who responded to our questionnaire on futureproofing strategies for industrial assets and systems: ABB, BAE Systems, Boeing, Caterpillar, EA Technology, Exxon Mobil, Finning, Hitachi, IBM and Rolls-Royce.This is the final version of the article. It first appeared from ICE Publishing via http://dx.doi.org/10.1680/jinam.15.0000

Multi-agent system architectures for collaborative prognostics

Funder: Siemens Industrial Turbomachinery UKAbstract: This paper provides a methodology to assess the optimal multi-agent architecture for collaborative prognostics in modern fleets of assets. The use of multi-agent systems has been shown to improve the ability to predict equipment failures by enabling machines with communication and collaborative learning capabilities. Different architectures have been postulated for industrial multi-agent systems in general. A rigorous analysis of the implications of their implementation for collaborative prognostics is essential to guide industrial deployment. In this paper, we investigate the cost and reliability implications of using different multi-agent systems architectures for collaborative failure prediction and maintenance optimization in large fleets of industrial assets. Results show that purely distributed architectures are optimal for high-value assets, while hierarchical architectures optimize communication costs for low-value assets. This enables asset managers to design and implement multi-agent systems for predictive maintenance that significantly decrease the whole-life cost of their assets