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Limited funding to maintain and preserve short‐line railroad (SLRR) bridge infrastructure requires that important priority decisions be made on an annual basis. The compartmentalized, dispersed, and diverse nature of many SLRR owners and operators is such that there is a need for a coordinated and centralized effort to evaluate the state‐wide system as a whole, to ensure the most effective overall resource allocation and also identify assets that either outperform predictions or consume disproportionate levels of resources for maintenance and operation, allowing for review of design and construction practices. The purpose of this paper is to examine the state of the art for railroad bridge population management and resource allocation decisions and to develop a state‐wide SLRR bridge prioritization methodology, to be used as a tool by a state agency to assist in allocating limited public funding for bridge maintenance, rehabilitation and replacement activities.

A literature review examining the state of the art of railroad bridge population management and resource allocation decisions was conducted, which provided the foundation for the development of a bridge prioritization algorithm. A state‐wide survey was conducted to develop a bridge database. A detailed evaluation of a statistically significant sample of bridges was conducted, to determine the structural and maintenance needs and preservation status of sub‐populations. The research team developed methodologies, applicable to the entire population, to develop a ranking of bridge preservation candidates.

A risk‐based prioritization algorithm is proposed to assign a relative risk score to each bridge in the population. The algorithm provides a management tool for making more effective maintenance and preservation decisions. Additionally, the bridge database allows managers to examine sub‐populations according to structural parameters to evaluate performance.

The revisable, modular framework of the prioritization algorithm provides a simple, effective and versatile tool for asset management and evaluation. The present proposal of this new prioritization methodology for SLRR bridges is a valuable tool for agencies faced with making rational decisions with limited information. Such a methodology does not currently exist in the literature and is of significant interest to short‐line owners/operators and state transportation agencies.

Reviews the growth in importance of planned maintenance programming (PMP). Sets out the aims of computerising PMP at strategic and detailed levels. Provides a detailed analysis of successful systems characteristics. Lists considerations to be borne in mind and questions to ask before purchasing a system. Concludes that although the potential benefits of computerised PMP are great, careful consideration of the objectives and options is vital.

The purpose of this paper is to provide a theoretical framework to improve understanding of physical asset management (AM) practices contained in well-known AM standards and guidelines.

Textual thematic analysis of physical AM standards and guidelines was carried out after developing a priori template derived from existing theories in management knowledge. Triangulation to validate the developed theoretical framework was used based on a deductive logic of inquiry equipped with semi-structured interview. The interviewees were managers of physical asset departments of 15 out of 24 ministries of Saudi public sector.

The developed theoretical framework called “systematic asset management practices” (SAMP) explains the logic behind physical AM practices contained in well-known standards and guidelines in terms of the essence of directly related practices for the life cycle of physical assets. SAMP shows that all AM standards and guidelines use a similar logic for managing the life cycles of physical assets.

AM developers can use the SAMP theoretical framework to develop and improve AM guidelines. In addition, the framework enables practitioners to further understand differences among standards and guidelines in addition to their potential future development.

This paper provides an original theory for AM practices, which originally evolved from informal to formal on the basis of practitioners’ logic.

As cyber-attacks continue to grow, organisations adopting the internet-of-things (IoT) have continued to react to security concerns that threaten their businesses within the current highly competitive environment. Many recorded industrial cyber-attacks have successfully beaten technical security solutions by exploiting human-factor vulnerabilities related to security knowledge and skills and manipulating human elements into inadvertently conveying access to critical industrial assets. Knowledge and skill capabilities contribute to human analytical proficiencies for enhanced cybersecurity readiness. Thus, a human-factored security endeavour is required to investigate the capabilities of the human constituents (workforce) to appropriately recognise and respond to cyber intrusion events within the industrial control system (ICS) environment.

A quantitative approach (statistical analysis) is adopted to provide an approach to quantify the potential cybersecurity capability aptitudes of industrial human actors, identify the least security-capable workforce in the operational domain with the greatest susceptibility likelihood to cyber-attacks (i.e. weakest link) and guide the enhancement of security assurance. To support these objectives, a Human-factored Cyber Security Capability Evaluation approach is presented using conceptual analysis techniques.

Using a test scenario, the approach demonstrates the capacity to proffer an efficient evaluation of workforce security knowledge and skills capabilities and the identification of weakest link in the workforce.

The approach can enable organisations to gain better workforce security perspectives like security-consciousness, alertness and response aptitudes, thus guiding organisations into adopting strategic means of appropriating security remediation outlines, scopes and resources without undue wastes or redundancies.

This paper demonstrates originality by providing a framework and computational approach for characterising and quantify human-factor security capabilities based on security knowledge and security skills. It also supports the identification of potential security weakest links amongst an evaluated industrial workforce (human agents), some key security susceptibility areas and relevant control interventions. The model and validation results demonstrate the application of action research. This paper demonstrates originality by illustrating how action research can be applied within socio-technical dimensions to solve recurrent and dynamic problems related to industrial environment cyber security improvement. It provides value by demonstrating how theoretical security knowledge (awareness) and practical security skills can help resolve cyber security response and control uncertainties within industrial organisations.

Australia has a huge stock of community buildings built up over decades. Their replacements consume a large sum of money from country’s economy which has called for a strategy for their sustainable management. For this, a comprehensive decision-making structure is an utmost requirement. The purpose of this paper is to capture their sustainable management from four aspects, i.e. environmental, economic, social and functional.

The design process follows an extensive review of environmental and life cycle assessments and company context documents. Extracted factors are tailored to community buildings management following expert consultation. However, the resulted list of factors is extremely large, and “factor analysis” technique is used to group the factors. For this, an industry-wide questionnaire across Australian local councils is employed to solicit opinions of the list of factors.

The analysis has pinpointed 18 key parameters (criteria) to represent all four aspects. This paper presents the preliminary findings of the factors and the analysis results based on the questionnaire responses.

The final decision-making structure incorporates all these aspects and criteria. This can be used to develop a decision-making model which produces a sustainability index for building components. Asset managers can mainly use the sustainability index to prioritise their maintenance activities and eventually, to find out cost-optimisation options for them.

Most notably, this is the first study to apply all four sustainability aspects (environmental, economic, social and functional) to develop a decision-making structure for Australian community buildings’ sustainable management.

The purpose is to describe new business opportunities within the Swedish railway industry and to support the development of business models that corresponds with the needs and requirements of Industry 4.0, here denoted as Service Management 4.0.

The study is an in-depth and descriptive case study of the Swedish railway system with specific focus on a railway vehicle maintainer. Public reports, statistics, internal documents, interviews and dialogues forms the basis for the empirical findings.

The article describes the complex business environment of the deregulated Swedish railway industry. Main findings are in the form of identified business opportunities and new business model propositions for one of the key actors, a vehicle maintainer.

The article provides valuable understanding of business strategy development within complex business environments and how maintenance related business models could be developed for reaching Service Management 4.0.

Due to recent technological developments, many maintenance managers become overwhelmed by the vast amount of data available to support their decision making. The purpose of this paper is to discuss identifying and eliminating waste in information management processes through a value stream mapping (VSM)-based method.

A theoretical framework is constructed based upon a review of the previous academic literature. The application of the framework is demonstrated with an empirical case example of a maintenance information management process within a food manufacturing company.

The paper highlights existing examples of applying VSM in information management; however, the knowledge is fragmented and has not been extensively applied in a maintenance context. The case example shows that the suggested process offers a feasible method of mapping and evaluating the inherent waste in information management processes.

The paper summarizes the existing body of knowledge on lean information management in maintenance, and presents a theoretical framework on how VSM can be applied in the context. An empirical example is provided to show the method applied to a real industry case. The results will illustrate how the framework can support companies in identifying the waste and development potential in their maintenance information management.

The purpose of this paper is to develop a comprehensive approach to efficiently integrate maintenance and operation by combining process and condition monitoring data with performance measures.

Intelligent stress, condition and health indicators have been developed for control and condition monitoring by combining generalised moments and norms with efficient nonlinear scaling. The data analysis resulting nonlinear scaling functions can also be used to handle performance measures used for management. The generalised norms provide limits for an advanced statistical process control.

The data‐driven analysis methodology demonstrates that management‐oriented indicators can be presented in the same scale as intelligent condition and stress indices. Control, condition monitoring, maintenance and performance monitoring are represented as interactive feedback loops.

Performance analysis can be based on real‐time information by using various stress, condition and health indices as inputs. Similar approaches can be used for outputs: quality indices, harmonised indices, key performance indicators, process capability indices and overall equipment effectiveness. Since consistent linguistic explanations based on nonlinear scaling are available for all these indices, the analysis can be further deepened with LE modelling. Efficient monitoring with intelligent indices provides a good basis for control and condition‐based maintenance and performance monitoring.

The paper extends the nonlinear scaling methodology and linguistic equations to intelligent performance measures. The methodology provides a consistent way to also represent all information with linguistic terms.

The purpose of this paper is to present a definition of modern configuration for a medium-altitude long-endurance unmanned aerial vehicle (MALE UAV) and its on-board systems to obtain a suitable basis for future definitions such as a possible logistic support configuration first hypothesis.

Starting from high-level requirements, both the UAV conceptual design and on-board systems preliminary design have been carried out through proprietary tools. Then, some peculiarities from previous studies, such as systems advanced UAV alternative energy, have been maintained and confirmed (diesel propulsion and energy storage system).

The improvement of a component of an aircraft can play a relevant role in the whole system. In the paper, it is considered how a concept of MALE UAV can evolve (this topic is considered by the authors since many years) by incorporating advanced on-board systems concepts.

The numerical results promote and support the use of advanced on-board system solutions and architectures to improve the effectiveness, efficiency and performance of MALE UAVs.

Usually, conceptual and preliminary design phases analyze in-depth the aerodynamic and structural solutions and aircraft performance. In this study, the authors aim to focus on the advanced on-board systems for MALE UAVs. This kind of aircraft is not yet a mature concept, with very few operating machines and many projects in the development phase.