Maximise asset availability and reduce maintenance costs – an integrated approach combining condition assessment with data analytics

The OEM, using a set of planned maintenance schedules that are based upon running hours or inspections, has traditionally formulated gas turbine maintenance practice. This maintenance concept has been reasonably successful, but it fails to take into account the introduction of new technologies than can provide the operator with a more meaningful insight into the condition of the turbine, perhaps even in a prognostic manner. The application of computer based technology to gas turbine condition monitoring can provide a significant reduction in maintenance costs. At the same time, condition-monitoring technology can provide an improvement in reliability and availability by extending the maintenance intervals and reducing the number of unplanned outages. This paper will discuss the introduction of an integrated approach to gas turbine control and engine condition assessment. This integrated approach enables the control to turn engine data into useful information and knowledge that assists the operator with trouble shooting and maintenance condition assessments thus lowering the overall engine maintenance costs.

Download Full-text

Big data analytics capabilities and knowledge management: impact on firm performance

Management Decision ◽

10.1108/md-07-2018-0825 ◽

2019 ◽

Vol 57 (8) ◽

pp. 1923-1936 ◽

Cited By ~ 42

Author(s):

Alberto Ferraris ◽

Alberto Mazzoleni ◽

Alain Devalle ◽

Jerome Couturier

Keyword(s):

Big Data ◽

Knowledge Management ◽

Data Analytics ◽

Structural Equation ◽

Positive Impact ◽

Big Data Analytics ◽

Integrated Approach ◽

Content Type ◽

Decision Making Processes ◽

External Sources

Purpose Big data analytics (BDA) guarantees that data may be analysed and categorised into useful information for businesses and transformed into big data related-knowledge and efficient decision-making processes, thereby improving performance. However, the management of the knowledge generated from the BDA as well as its integration and combination with firm knowledge have scarcely been investigated, despite an emergent need of a structured and integrated approach. The paper aims to discuss these issues. Design/methodology/approach Through an empirical analysis based on structural equation modelling with data collected from 88 Italian SMEs, the authors tested if BDA capabilities have a positive impact on firm performances, as well as the mediator effect of knowledge management (KM) on this relationship. Findings The findings of this paper show that firms that developed more BDA capabilities than others, both technological and managerial, increased their performances and that KM orientation plays a significant role in amplifying the effect of BDA capabilities. Originality/value BDA has the potential to change the way firms compete through better understanding, processing, and exploiting of huge amounts of data coming from different internal and external sources and processes. Some managerial and theoretical implications are proposed and discussed in light of the emergence of this new phenomenon.

Download Full-text

Big data analytics based enablers of supply chain capabilities and firm competitiveness: a fuzzy-TISM approach

Journal of Enterprise Information Management ◽

10.1108/jeim-02-2020-0080 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Nisha Bamel ◽

Umesh Bamel

Keyword(s):

Big Data ◽

Supply Chain ◽

Data Analytics ◽

Structural Model ◽

Big Data Analytics ◽

Integrated Approach ◽

Interpretive Structural Modeling ◽

Content Type ◽

People Skills ◽

Interpretive Structural Model

PurposeThis paper aims to identify the big data analytics (BDAs) based enablers of supply chain capabilities (SCCs) and competitiveness of firms. This paper also models the interaction among identified enablers and thus projects the relationship strength of these enablers with SCC and a firm's competitiveness.Design/methodology/approachIn order to achieve the research objectives of this paper, we employed fuzzy total interpretive structural modeling (TISM), an integrated approach of an interpretive structural model and TISM.FindingsResults suggest that BDA-based enablers namely, IT infrastructure for BDA; leadership commitment; people skills for use of BDA and financial support for BDA significantly enable SCC and enhance firm competitiveness.Practical implicationsResults of the present study have implications for researchers and practitioners; the results will enable them to design policies around identified enablers of BDA initiatives.Originality/valueThe present paper is one of a few early efforts that address the role of BDA in augmenting SCC and subsequently a firm's competitiveness from a resource-dynamic capability perspective.

Download Full-text

Predicting rail defect frequency: An integrated approach using fatigue modeling and data analytics

Computer-Aided Civil and Infrastructure Engineering ◽

10.1111/mice.12453 ◽

2019 ◽

Vol 35 (2) ◽

pp. 101-115 ◽

Cited By ~ 3

Author(s):

Faeze Ghofrani ◽

Abhishek Pathak ◽

Reza Mohammadi ◽

Amjad Aref ◽

Qing He

Keyword(s):

Data Analytics ◽

Integrated Approach ◽

Defect Frequency ◽

Fatigue Modeling

Download Full-text

A big data analytics strategy for scalable urban infrastructure condition assessment using semi-supervised multi-transform self-training

Journal of Civil Structural Health Monitoring ◽

10.1007/s13349-020-00386-4 ◽

2020 ◽

Vol 10 (2) ◽

pp. 313-332 ◽

Cited By ~ 1

Author(s):

Mohamad Alipour ◽

Devin K. Harris

Keyword(s):

Big Data ◽

Data Analytics ◽

Big Data Analytics ◽

Urban Infrastructure ◽

Condition Assessment

Download Full-text

Exploring the paths to big data analytics implementation success in banking and financial service: an integrated approach

Industrial Management & Data Systems ◽

10.1108/imds-04-2021-0209 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Nastaran Hajiheydari ◽

Mohammad Soltani Delgosha ◽

Yichuan Wang ◽

Hossein Olya

Keyword(s):

Big Data ◽

Delphi Study ◽

Data Analytics ◽

Service Sector ◽

Big Data Analytics ◽

Integrated Approach ◽

Financial Service ◽

Influential Factors ◽

Successful Implementation ◽

Content Type

PurposeBig data analytics (BDA) is recognized as a recent breakthrough technology with potential business impact, however, the roadmap for its successful implementation and the path to exploiting its essential value remains unclear. This study aims to provide a deeper understanding of the enablers facilitating BDA implementation in the banking and financial service sector from the perspective of interdependencies and interrelations.Design/methodology/approachWe use an integrated approach that incorporates Delphi study, interpretive structural modelling (ISM) and fuzzy MICMAC methodology to identify the interactions among enablers that determine the success of BDA implementation. Our integrated approach utilizes experts' domain knowledge and gains a novel insight into the underlying causal relations associated with enablers, linguistic evaluation of the mutual impacts among variables and incorporating two innovative ways for visualizing the results.FindingsOur findings highlight the key role of enabling factors, including technical and skilled workforce, financial support, infrastructure readiness and selecting appropriate big data technologies, that have significant driving impacts on other enablers in a hierarchical model. The results provide reliable, robust and easy to understand insights about the dynamics of BDA implementation in banking and financial service as a whole system while demonstrating potential influences of all interconnected influential factors.Originality/valueThis study explores the key enablers leading to successful BDA implementation in the banking and financial service sector. More importantly, it reveals the interrelationships of factors by calculating driving and dependence degrees. This exploration provides managers with a clear strategic path towards effective BDA implementation.

Download Full-text

An Integrated Approach to Shipboard System and Equipment Testing for Improved Maintenance Management

Marine Technology and SNAME News ◽

10.5957/mt1.1989.26.2.105 ◽

1989 ◽

Vol 26 (02) ◽

pp. 105-119

Author(s):

Charles Blatchley ◽

Joseph Connors ◽

Anthony Vecino

Keyword(s):

Comprehensive Evaluation ◽

Integrated Approach ◽

Condition Assessment ◽

Maintenance Management ◽

Service Levels ◽

Material Condition ◽

Ship Maintenance ◽

Equipment Testing ◽

Vessel Material ◽

Critical Components

Commercial operators today are required to maintain maximum vessels in-service levels and, with government vessel operators competing for decreasing operating funds, the management of ship maintenance and repair (M&R) has become a highly visible area which can have a significant impact on overall vessel operating costs. As an approach to consolidate, improve, and simply better manage a vessel's state of material condition and M&R requirements, an integrated shipboard Material Condition Assessment Program can be implemented which provides a comprehensive evaluation and assessment of the various critical components on a ship-specific basis. This approach will integrate all vessel material condition assessment techniques and periodic surveys whose results can be used for advanced maintenance planning and budgeting. The approach and methodology employed and described in this paper are not new, having been tried and proven to varying degrees in the marine and related industrial fields, and are considered within the constraints of day-to-day vessel operation and maintenance management.

Download Full-text

An approach for Industrie 4.0-compliant and data-sovereign Digital Twins

at - Automatisierungstechnik ◽

10.1515/auto-2021-0074 ◽

2021 ◽

Vol 69 (12) ◽

pp. 1051-1061

Author(s):

Michael Jacoby ◽

Friedrich Volz ◽

Christian Weißenbacher ◽

Ljiljana Stojanovic ◽

Thomas Usländer

Keyword(s):

Data Sharing ◽

Industrial Production ◽

Data Analytics ◽

Integrated Approach ◽

Industrie 4.0 ◽

Application Domain ◽

Digital Twins ◽

Implementation Approach ◽

Architectural Framework ◽

International Data

Abstract Data sharing between enterprises requires both interoperability and data sovereignty. In the application domain of industrial production an integrated approach is required that encompasses standards and technologies of both Industrie 4.0 and the International Data Spaces (IDS). This paper describes how to combine them for the concept of Digital Twins following the architectural framework given in ISO DIS 23247. Furthermore, an implementation approach is described relying upon the Fraunhofer Advanced AAS Tools for Digital Twins (FA³ST). The resulting architectural approach may be combined with further open manufacturing standards, and may be applied for data analytics and the engineering of AI-based systems.

Download Full-text

Towards a Guideline Affording Overarching Knowledge Building in Data Analysis Projects

Business Information Systems ◽

10.52825/bis.v1i.56 ◽

2021 ◽

pp. 49-59

Author(s):

Dorothea Schneider ◽

Wibke Kusturica

Keyword(s):

Data Analysis ◽

Learning Curve ◽

Data Analytics ◽

Manufacturing Industry ◽

Knowledge Building ◽

Integrated Approach ◽

Competitive Market ◽

Use Of Data ◽

Course Of Action

Tight and competitive market situations pose a serious challenge to enterprises in the manufacturing industry domain. Competing in the use of data analytics to enhance products and processes requires additional resources to deal with the complexity. On the contrary, the possibilities afforded by digitization and data analysis-based approaches make for a valuable asset. In this paper we suggest a guideline to a systematic course of action for the data-based creation of holistic insight. Building an overlaying corpus of knowledge accelerates the learning curve within specific projects as well as across projects by exceeding the project-specific view towards an integrated approach.

Download Full-text