Study of Asset Management Support Tools for Electric Power Equipments

This chapter will present an overview of the challenges presented to modern power utility companies and how many organizations are facing particularly pressing problems with regards to an ageing workforce and a general shortage of skills; a situation that is anticipated to worsen in the future. It is proposed that knowledge management (KM) and decision support (DS) may contribute to a solution to these challenges. The chapter describes the end-to-end processes associated with KM and DS in a power utility context and attempts to provide guidance on effective practices for each stage of the described processes. An overview of one particular power utility company that has embraced KM is presented, and it is proposed that the function of asset management within power utilities in particular may benefit from KM. The chapter focuses not only on KM techniques and implementation, but, equally, if not more importantly, on the various cultural and behavioural aspects that are critical to the success of any KM/DS initiative.

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Empirical Investigation of Critical Success Factors for Implementing Business Intelligence Systems in Multiple Engineering Asset Management Organisations

Strategic Information Systems ◽

10.4018/978-1-60566-677-8.ch129 ◽

2011 ◽

pp. 2039-2063

Author(s):

William Yeoh ◽

Jing Gao ◽

Andy Koronios

Keyword(s):

Business Intelligence ◽

Asset Management ◽

Delphi Study ◽

Critical Success Factors ◽

Success Factors ◽

Business Case ◽

Management Support ◽

Critical Success ◽

Compliance Requirements ◽

Development Approach

Engineering asset management organisations (EAMOs) are increasingly motivated to implement business intelligence (BI) systems in response to dispersed information environments and compliance requirements. However, the implementation of a business intelligence (BI) system is a complex undertaking requiring considerable resources. Yet, so far, there are few defined critical success factors (CSFs) to which management can refer. Drawing on the CSFs framework derived from a previous Delphi study, a multiple-case design was used to examine how these CSFs could be implemented by five EAMOs. The case studies substantiate the construct and applicability of the CSFs framework. These CSFs are: committed management support and sponsorship, a clear vision and well-established business case, business-centric championship and balanced team composition, a business-driven and iterative development approach, user-oriented change management, a business-driven, scalable and flexible technical framework, and sustainable data quality and integrity. More significantly, the study further reveals that those organisations which address the CSFs from a business orientation approach will be more likely to achieve better results.

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Expert System for an Optimized Asset Management in Electric Power Transmission Systems

Journal of Control Automation and Electrical Systems ◽

10.1007/s40313-019-00451-4 ◽

2019 ◽

Vol 30 (3) ◽

pp. 434-440

Author(s):

Danilo H. Spatti ◽

Luisa Liboni ◽

Rogério A. Flauzino ◽

Renato P. Bossolan ◽

Bruno C. Vitti

Keyword(s):

Expert System ◽

Electric Power ◽

Asset Management ◽

Power Transmission ◽

Transmission Systems ◽

Power Transmission Systems

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PrimaVera: Synergising Predictive Maintenance

Applied Sciences ◽

10.3390/app10238348 ◽

2020 ◽

Vol 10 (23) ◽

pp. 8348

Author(s):

Bram Ton ◽

Rob Basten ◽

John Bolte ◽

Jan Braaksma ◽

Alessandro Di Bucchianico ◽

...

Keyword(s):

Asset Management ◽

Process Model ◽

Building Blocks ◽

Predictive Maintenance ◽

Full Potential ◽

Support Tools ◽

Maintenance Cycle ◽

Optimal Maintenance ◽

Organisational Factors ◽

Maintenance Process

The full potential of predictive maintenance has not yet been utilised. Current solutions focus on individual steps of the predictive maintenance cycle and only work for very specific settings. The overarching challenge of predictive maintenance is to leverage these individual building blocks to obtain a framework that supports optimal maintenance and asset management. The PrimaVera project has identified four obstacles to tackle in order to utilise predictive maintenance at its full potential: lack of orchestration and automation of the predictive maintenance workflow, inaccurate or incomplete data and the role of human and organisational factors in data-driven decision support tools. Furthermore, an intuitive generic applicable predictive maintenance process model is presented in this paper to provide a structured way of deploying predictive maintenance solutions.

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Digital Self-Management Support Tools in the Care Plan of Patients With Cancer: Review of Randomized Controlled Trials

Journal of Medical Internet Research ◽

10.2196/20861 ◽

2021 ◽

Vol 23 (6) ◽

pp. e20861

Author(s):

Danielle JM Adriaans ◽

Angelique TM Dierick-van Daele ◽

Marc Johannes Hubertus Maria van Bakel ◽

Grard AP Nieuwenhuijzen ◽

Joep AW Teijink ◽

...

Keyword(s):

Quality Of Life ◽

Physical Activity ◽

Randomized Controlled Trials ◽

Self Management ◽

Controlled Trials ◽

Management Support ◽

Patients With Cancer ◽

Randomized Controlled ◽

Support Tools

Background Digital self-management support tools (DSMSTs)—electronic devices or monitoring systems to monitor or improve health status—have become increasingly important in cancer care. Objective The aim of this review is to analyze published randomized clinical trials to assess the effectiveness of DSMSTs on physical and psychosocial symptoms or other supportive care needs in adult patients with cancer. Methods Five databases were searched from January 2013 to January 2020. English or Dutch language randomized controlled trials comparing DSMSTs with no intervention, usual care, alternative interventions, or a combination and including patients aged ≥18 years with pathologically proven cancer in the active treatment or survivorship phases were included. The results were summarized qualitatively. Results A total of 19 publications describing 3 types of DSMSTs were included. Although the content, duration, and frequency of interventions varied considerably across studies, the commonly used elements included an assessment component, tailored symptom self-management support, an information section, a communication section, and a diary. Significant positive effects were observed on quality of life in 6 (out of 10) studies, on anxiety in 1 (out of 5) study and depression in 2 (out of 8) studies, on symptom distress in 5 (out of 7) studies, on physical activity in 4 (out of 6) studies, on dietary behavior in 1 (out of 4) study, and on fatigue in 2 (out of 5) studies. Moreover, significant negative effects were observed on anxiety in 1 (out of 5) study and depression in 1 (out of 8) study. Most interventions were web-based interventions; 2 studies used mobile apps, and 1 study used a game as a DSMST. The overall quality of the studies was found to be good, with 13 out of 19 studies classified as high quality. Conclusions This review suggests that DSMSTs have a beneficial effect on the quality of life. For effects on other patient outcomes (eg, anxiety and depression, symptom distress, physical activity, dietary behavior, and fatigue), the evidence is inconsistent and limited or no effect is suggested. Future research should focus on specific tumor types, study different types of interventions separately, and assess the effects of specific interventions at different stages of disease progression.

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Implementing Community-Created Self-Management Support Tools in Primary Care Practices: Multimethod Analysis From the INSTTEPP Study

Journal of Patient-Centered Research and Reviews ◽

10.17294/2330-0698.1634 ◽

2018 ◽

Vol 5 (4) ◽

pp. 267-275

Author(s):

Douglas H Fernald ◽

Matthew J Simpson ◽

Donald E Nease ◽

David L Hahn ◽

Amanda E Hoffmann ◽

...

Keyword(s):

Primary Care ◽

Self Management ◽

Management Support ◽

Support Tools ◽

Care Practices ◽

Primary Care Practices

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Managing the Implementation of Business Intelligence Systems

Strategic Information Systems ◽

10.4018/978-1-60566-677-8.ch090 ◽

2011 ◽

pp. 1412-1428

Author(s):

William Yeoh ◽

Andy Koronios ◽

Jing Gao

Keyword(s):

Asset Management ◽

Management Support ◽

Critical Factors ◽

Implementation Success ◽

Systems Implementation ◽

Business Intelligence Systems ◽

Contextual Elements ◽

Business User ◽

Research Gap ◽

Technical Framework

The implementation of a BI system is a complex undertaking requiring considerable resources. Yet there is a limited authoritative set of CSFs for management reference. This article represents a first step of filling in the research gap. The authors utilized the Delphi method to conduct three rounds of studies with 15 BI system experts in the domain of engineering asset management organizations. The study develops a CSFs framework that consists of seven factors and associated contextual elements crucial for BI systems implementation. The CSFs are committed management support and sponsorship, business user-oriented change management, clear business vision and well-established case, business-driven methodology and project management, businesscentric championship and balanced project team composition, strategic and extensible technical framework, and sustainable data quality and governance framework. This CSFs framework allows BI stakeholders to holistically understand the critical factors that influence implementation success of BI systems.

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