Search results

The purpose of this paper is to increase productivity through smart maintenance planning by including productivity as one of the objectives of the maintenance organization. Therefore, the goals of the paper are to investigate existing machine criticality assessment and identify components of the criticality assessment tool to increase productivity.

An embedded multiple case study research design was adopted in this paper. Six different cases were chosen from six different production sites operated by three multi-national manufacturing companies. Data collection was carried out in the form of interviews, focus groups and archival records. More than one source of data was collected in each of the cases. The cases included different production layouts such as machining, assembly and foundry, which ensured data variety.

The main finding of the paper is a deeper understanding of how manufacturing companies assess machine criticality and plan maintenance activities. The empirical findings showed that there is a lack of trust regarding existing criticality assessment tools. As a result, necessary changes within the maintenance organizations in order to increase productivity were identified. These are technological advancements, i.e. a dynamic and data-driven approach and organizational changes, i.e. approaching with a systems perspective when performing maintenance prioritization.

Machine criticality assessment studies are rare, especially empirical research. The originality of this paper lies in the empirical research conducted on smart maintenance planning for productivity improvement. In addition, identifying the components for machine criticality assessment is equally important for research and industries to efficient planning of maintenance activities.

Assessing project criticality in a project portfolio (PP) is of great practical significance to improve robustness from damage. While project criticality assessment has increased diversity in approaches, the understanding of vulnerable project impacts is still limited. To promote a better understanding of assessing project criticality, a vulnerability measurement model is constructed.

First, integrating the tasks, projects and corresponding relationships among them, a project portfolio network (PPN) is constructed. Second, the project's vulnerability is measured by combining the topological structure and functional attributes. Third, project criticality is assessed by the vulnerability measurement results. Lastly, the proposed model is applied in a numerical example to illustrate its suitability and effectiveness.

For academia, this study provides a novel perspective on project vulnerability measurement and expands project criticality assessment tools. For practitioners, the straightforward model provides an effective tool for assessing project criticality and contributes to enhancing project portfolio management (PPM).

The impact of the task on the project is considered in this study. Topological structure and functional attributes are also integrated for measuring project vulnerability due to the impact of random attacks in an uncertain environment, providing a new perspective on the requirements of project criticality assessment and the measurement of project vulnerability.

The purpose of this paper is to present a new index of social vulnerability (SV), based on local level data [statistical blocks (SBs)]. This same methodology was applied before at the municipal level, which is a level of analysis that under-evaluates local spots of high SV, by one side, and generalizes the coverage of support capacity equipment and infrastructure. The geographical level of detail of the input data allows to overcome those limitations and better inform infra-municipal risk practitioners and planners.

The assessment of SV in this paper adopts an inductive approach. The research context of this conceptual and methodological proposal derived from the need to operationalize the concept of SV as a planning tool. This approach required to distinguish between the components of criticality and support capability, as their assessment provides knowledge with distinct applications in risk management. The statistical procedure is based on principal components analysis, using the SB as the unit of analysis.

Support capability acts as a counter-weight of criticality. This understanding is well illustrated in the mapping of each component and the final score of SV. The methodological approach allowed to identify the drivers of criticality and support capability in each SB, aiding decision-makers and risk practitioners in finding the vulnerability forcers that require more attention (public or private social equipment, housing policies, emergency anticipatory measures, etc.).

An original approach to SV assessments is the consideration of the components of criticality and support capability. The results allow for the definition of adapted and specific strategies of risk mitigation and civil protection measures to distinct types of risk groups and by different stakeholders and risk practitioners. By predicting the impact and the recovery capacity of communities, the results have applicability in several fields of risk governance as, for example, risk communication and involvement, social intervention (health, education and housing), emergency response, contingency planning, early warning and spatial planning.

The purpose of this paper is to trial the application of a criticality framework for roads in an urban environment. The failure or disruption of critical transport routes can have substantial impacts on the economy and societal well-being. Determining the criticality of transport routes is thus of crucial importance for infrastructure providers, city planners and emergency management officials, as it enables appropriate resilience assessments and targeted improvement/intervention and investment strategies to be conducted.

The authors summarise the proposed criticality framework developed by Hughes (2016) for road networks and apply and validate the framework to an area containing 907 km of roads in the central Auckland area of New Zealand. Following an initial trial of the framework, alterations were made to the framework logic, which included the introduction of a new criticality level to account for some roads providing minimal direct societal and economic benefit and a rationalisation step to ensure that road sections always link to others with either an equal or higher criticality.

The modified framework and five-level criticality scale, when applied to the study area in central Auckland, is suitable for determining critical roads and can therefore assist with future assessments of road infrastructure resilience.

The framework also has the potential to be applied more widely and adapted so that it is applicable for determining the criticality of other infrastructure types and in other settings, which would allow improved assessments within and across sectors.

The purpose of this paper is to identify the productivity improvement potentials from maintenance planning practices in manufacturing companies. In particular, the paper aims at understanding the connection between machine criticality assessment and maintenance prioritization in industrial practice, as well as providing the improvement potentials.

An explanatory mixed method research design was used in this study. Data from literature analysis, a web-based questionnaire survey, and semi-structured interviews were gathered and triangulated. Additionally, simulation experimentation was used to evaluate the productivity potential.

The connection between machine criticality and maintenance prioritization is assessed in an industrial set-up. The empirical findings show that maintenance prioritization is not based on machine criticality, as criticality assessment is non-factual, static, and lacks system view. It is with respect to these finding that the ways to increase system productivity and future directions are charted.

In addition to the empirical results showing productivity improvement potentials, the paper emphasizes on the need for a systems view for solving maintenance problems, i.e. solving maintenance problems for the whole factory. This contribution is equally important for both industry and academics, as the maintenance organization needs to solve this problem with the help of the right decision support.

This paper aims to enable the analysts of reliability and safety systems to evaluate the risk and prioritize failure modes ideally to prefer measures for reducing the risk of undesired events.

To address the constraints considered in the conventional failure mode and effects analysis (FMEA) method for criticality assessment, the authors propose a new hybrid model combining different multi-criteria decision-making (MCDM) methods. The analytical hierarchy process (AHP) is used to construct a criticality matrix and calculate the weights of different criteria based on five criticalities: personnel, equipment, time, cost and quality. In addition, a preference ranking organization method for enrichment evaluation (PROMETHEE) method is used to improve the prioritization of the failure modes. A comparative work in which the robust data envelopment analysis (RDEA)-FMEA approach was used to evaluate the validity and effectiveness of the suggested approach and simplify the comparative analysis.

This work aims to highlight the real case study of the automotive parts industry. Using this analysis enables assessing the risk efficiently and gives an alternative ranking to that acquired by the traditional FMEA method. The obtained findings offer that combining of two multi-criteria decision approaches and integrating their outcomes allow for instilling confidence in decision-makers concerning the risk assessment and the ranking of the different failure modes.

This research gives encouraging outcomes concerning the risk assessment and failure modes ranking in order to reduce the frequency of occurrence and gravity of the undesired events by handling different forms of uncertainty and divergent judgments of experts.

The purpose of this study seeks to identify the critical barriers for the deployment of Lean Construction (LC).

In order to identify the barriers of Lean Construction, a systematic review of the scientific literature was carried out, in addition to analysis of the content of papers presented at a major Lean Construction conference. After the barriers were identified, a Lawshe study was conducted with experts in Lean Construction to verify the criticality of each of the barriers encountered.

This study identified 83 potential pre-deployment barriers in the literature, of which eight were considered critical by the experts. The results of Lawshe study pointed that critical barriers refer to leadership characteristics, cultural aspects and structural aspects.

Variations in the assessment of the criticality of the barriers may occur from one country to another due to regional differences in the construction sector.

The implications of this study are recognizing and identifying the characteristics of an organization that can hinder Lean Construction allows these issues to be resolved before beginning the Lean journey.

This article is the first of its kind to assess the criticality of barriers to Lean Construction using a quantitative technique. Knowledge of this set of barriers provides both practical and theoretical readers with an increased chance of success in the deployment of an LC project.

Mega-projects (MP) are important not only to the stakeholders involved in their development and construction, but also to the societies, economies, and environments impacted by them. Given the importance of MP and the prevailing trend toward poor performance, the purpose of this paper is to identify changes in project development and execution to increase the likelihood of success on MP.

The researchers performed an extensive literature review in the initial phase. Then, interviews with experienced mega-project professionals were conducted to gather information on factors contributing to success and failure on MP. A detailed survey was then carried out to quantify and assess the frequency and impact levels of these factors. Finally, case studies were performed to analyze the manifestations of these impact factors on MP and identify mitigation strategies.

After gathering data from more than 100 projects, the researchers identified and prioritized 34 factors that have high frequency and negative performance impacts on MP, categorizing them into five categories. These factors were then used to create a mega-project preparedness assessment process and a lessons learned repository around these factors, which includes factor descriptions, examples from actual projects, and recommendations. The result is a structured method for enabling comprehensive mega-project risk management and mitigation planning.

The research has gone beyond any previous generic lessons learned, to enable project teams to make structured assessments of critical mega-project impact factors. Assessing these impact factors will enable more accurate and thorough mitigation planning for them and, thus, improve mega-project performance.

The purpose of this paper is to introduce the JKM 2010 annual special issue on knowledge based development (KBD) with reference to the multi‐level analysis characteristic of the field.

A description of the knowledge management approach at ESOC (European Space Operations Centre of the European Space Agency) is provided first. At the core of this approach is the breakdown of knowledge in individual technical domains followed by coverage analysis and criticality assessment. Such a framework becomes the reference for best knowledge acquisition, transfer and storage locus identification and subsequent knowledge management practices and guidelines.

KBD provides an integrated framework to account for multidisciplinary analyses and multilevel practices in knowledge capital generation, distribution and utilization.

The collection of papers included in the annual special issue on KBD provides a representative, composite view of the research topics and applications concerns in the field. Involving a number of disciplines and levels of analysis, issues ranging from the technological gatekeeper to global knowledge flows show the interdependence of KBD concepts and tools.

Public Works and Government Services Canada (PWGSC) is the federal department responsible for housing over 190,000 Canadian federal public servants. During Y2K preparations, it became apparent that a single source or form of integrated, emergency response information at the infrastructure level did not exist. A process had to be created and developed that would serve as a single vehicle and source for building‐based emergency response. These preparations for Y2K saw the creation of the Infrastructure Continuity Unit (ICU) and a system for the creation, validation, and maintenance of Infrastructure Continuity Plans (ICPs). An ICP is an event‐management document that contains a series of procedures and protocols to be used during a building‐based incident or disruption of services. The ICU is supported nationally by a network of Regional Coordinators who oversee the gathering of information needed to create ICPs for their own parts of the country. This paper demonstrates how this system, along with the ICU’s recent certification by the Canadian General Standards Board (CGSB) to the ISO 9000 standard, have contributed to the ICU’s success. This paper takes the reader through an in‐depth exploration of the ICU’s processes, methodologies and procedures and demonstrates why, in a post‐September 11th world, the ICU has begun to attract international attention.