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Article
Publication date: 1 May 1999

Brian Wood

Discusses perceptions of building maintenance and care. Contrasts the “received wisdom” of planned preventive maintenance with the concept of “Just‐ in‐time maintenance”…

2395

Abstract

Discusses perceptions of building maintenance and care. Contrasts the “received wisdom” of planned preventive maintenance with the concept of “Just‐ in‐time maintenance”. Identifies possible locations of “intelligence” in people and buildings. Also examines the relationship between technology and users, particularly regarding user‐satisfaction. Considers the penetration of the maintenance/care market by non‐traditional players and describes features of “Call‐centred maintenance”. Identifies the opportunity within the Private Finance Initiative for total building care services.

Details

Facilities, vol. 17 no. 5/6
Type: Research Article
ISSN: 0263-2772

Keywords

Article
Publication date: 1 December 2002

Peter W. Tse

With the shift of manufacture to mainland China, the utility and building services industries in Hong Kong have become dominant. To ensure adherence to proper routine…

1617

Abstract

With the shift of manufacture to mainland China, the utility and building services industries in Hong Kong have become dominant. To ensure adherence to proper routine operations and the provision of quality services, the equipment of these sectors must be maintained in good condition. The results of a recently conducted survey indicate that equipment failure‐driven and time‐based maintenance are most commonly used in Hong Kong. Only a few companies use condition‐based preventive maintenance. This paper presents an overview of maintenance practice in Hong Kong, and introduces the novel concept of intelligent predictive maintenance. In this maintenance system, the seriousness of the damage that is caused by faults in equipment can be determined, and the remnant life of the defective equipment can be predicted. Moreover, the system can automatically schedule maintenance activities in an efficient manner. With such abilities in equipment prognosis and automatic maintenance scheduling, the “fire‐fighting” situations that often occur in failure‐driven and time‐based maintenance can be avoided. Hence, any waste of resources and loss of production that are due to the mismanagement of maintenance can be substantially reduced.

Details

Journal of Quality in Maintenance Engineering, vol. 8 no. 4
Type: Research Article
ISSN: 1355-2511

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Article
Publication date: 1 July 2000

Farid Meziane, Sunil Vadera, Khairy Kobbacy and Nathan Proudlove

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly…

4408

Abstract

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence (AI) will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of AI techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different AI techniques to be considered and then shows how these AI techniques are used for the components of IMS.

Details

Integrated Manufacturing Systems, vol. 11 no. 4
Type: Research Article
ISSN: 0957-6061

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Article
Publication date: 23 December 2020

Henrique Costa Marques, Alessandro Giacotto, Carlos Eduardo Scussiatto and Fernando Teixeira Mendes Abrahão

A framework is being developed to help Integrated Electronic Technical Publications (IETP) consultation inside and outside the aviation maintenance hangar. The expected…

Abstract

Purpose

A framework is being developed to help Integrated Electronic Technical Publications (IETP) consultation inside and outside the aviation maintenance hangar. The expected results are the reduction in time to access the desired IETP and to assist mechanics while performing maintenance tasks using voice recognition.

Design/methodology/approach

The work is being conducted based on literature review and consultation with mechanics from the aviation industry, through questionnaires. The development will be made through study cases by building a core search engine and mobile applications to support the mechanics during the maintenance activities.

Findings

The identified problem in small maintenance shops and defence organizations suggests that IETP are not entirely accessible before and during the maintenance activity. Such organizations suffer from information and communications technology (ICT) low infrastructure capability and demand access to multiple IETP databases as they usually support different aircraft. To have access to the IETP through voice assistant application will help mechanics to access the IETP, including when they would be with dirty hands and having difficulty in using mobile devices with touch displays.

Originality/value

The framework being developed will give mechanics the ability to quickly find any existing IETP to support its maintenance task at any time and in any place with low demanding for ICT infrastructure. The architecture will support different applications, and the identified priority is for IETP viewers to the most demanding functionality of specification ASD S1000D. This approach could also help in troubleshooting activities since COVID-19 brought new demands for the social distancing for mechanics.

Details

Journal of Quality in Maintenance Engineering, vol. 27 no. 3
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 5 September 2016

Olasumbo Ayodeji Makinde, Khumbulani Mpofu and Boitumelo Ramatsetse

Reconfigurable vibrating screen (RVS) is an innovative beneficiation machine designed at Tshwane University of Technology, Republic of South Africa (RSA); with adjustable…

Abstract

Purpose

Reconfigurable vibrating screen (RVS) is an innovative beneficiation machine designed at Tshwane University of Technology, Republic of South Africa (RSA); with adjustable screen structure to ensure sorting, sizing and screening of varying mineral particles (sizes and quantities) demanded by the customers in a cost-effective manner through the screen structure geometric transformation. In order to ensure that this machine is optimally maintained and managed when utilized in surface and underground mining industries, there is a need to establish or ascertain the best maintenance practices that would be used in optimally managing the RVS machine using decision making techniques. In view of this, the purpose of this paper is to ascertain the best maintenance practices that would be used to optimally maintain and manage the RVS machine when used in surface and underground mines.

Design/methodology/approach

Decision making techniques such as weighted decision matrix (WDM) and analytical hierarchy process (AHP) were used in this research work to establish the best maintenance practice for optimally maintaining and managing the RVS machine using relevant literature survey on maintenance management systems as well as the different maintenance criteria decision indices obtained from different conventional vibrating screen machine manufacturers and maintenance experts.

Findings

Based on the results obtained from the WDM analysis, it was anticipated that e-maintenance (e-M) system embedded with diagnosing and prognosing algorithms; with a cumulative weight score of 2.37 is the best maintenance practice for managing the RVS machine when used in surface mines, while AHP with deeper decision making analysis anticipated that the robotic-driven maintenance (RM) system with an important decision criteria; safety, and a cumulative hierarchy score of 28.6 percent, supported by e-M management system with a cumulative hierarchy score of 17.6 percent are the best maintenance mix that could be used in optimally maintaining and managing the RVS machine, when used in a craggy and hazardous underground mining environment.

Practical implications

To this effect, it could be anticipated that e-M management system (endowed with the ability to detect fault on the machine, diagnose and prognose the different subsystems of the RVS machine and ascertain the reconfiguration time and process of the RVS machine in recovering production loss during the maintenance of the machine as well as meeting customers demand, etc.) is the best maintenance practice for optimally maintaining the RVS machine when utilized in surface mines while both e-M management system and RM management system (endowed with the ability to carry out automated maintenance tasks achievement under little or no maintenance manager intervention) are also anticipated as the best customized maintenance practices mix that could be used in optimally maintaining the RVS machine, when used in dangerous and hazardous underground mining environment.

Originality/value

This maintenance management system evaluation and selection for optimal RVS machine functionality will serve as a useful information to different mining machines (and other related machines) maintenance managers, in selecting the best maintenance management system for ensuring optimal functionality, reliability and maintainability of machines used in their industries.

Details

International Journal of Quality & Reliability Management, vol. 33 no. 8
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 26 July 2011

Khairy A.H. Kobbacy and Sunil Vadera

The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The…

2422

Abstract

Purpose

The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence, the purpose of this paper is to present a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research.

Design/methodology/approach

The paper builds upon our previous survey of this field which was carried out for the ten‐year period 1995‐2004. Like the previous survey, it uses Elsevier's Science Direct database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus, the application categories adopted are: design; scheduling; process planning and control; and quality, maintenance and fault diagnosis. Research on utilising neural networks, case‐based reasoning (CBR), fuzzy logic (FL), knowledge‐Based systems (KBS), data mining, and hybrid AI in the four application areas are identified.

Findings

The survey categorises over 1,400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: the trends for design and scheduling show a dramatic increase in the use of genetic algorithms since 2003 that reflect recognition of their success in these areas; there is a significant decline in research on use of KBS, reflecting their transition into practice; there is an increasing trend in the use of FL in quality, maintenance and fault diagnosis; and there are surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research.

Originality/value

This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research.

Details

Journal of Manufacturing Technology Management, vol. 22 no. 6
Type: Research Article
ISSN: 1741-038X

Keywords

Article
Publication date: 31 December 2020

Hatem Algabroun, Jon Bokrantz, Basim Al-Najjar and Anders Skoogh

This paper presents a concept for digitalised maintenance (DM), maps the conceptualised DM to maintenance problems in industries and highlights challenges that might be…

Abstract

Purpose

This paper presents a concept for digitalised maintenance (DM), maps the conceptualised DM to maintenance problems in industries and highlights challenges that might be faced when realizing this concept.

Design/methodology/approach

First, maintenance problems that are faced by the industry are presented, followed by a conceptualisation of DM. Next, a typical operational scenario is used as an exemplification to show system dynamics. The characteristics of this conceptualised DM are then mapped to the identified maintenance problems of industry. Then, interesting initiatives in this domain are highlighted, and finally, the challenges to realize this approach are discussed.

Findings

This paper identified a set of problems related to maintenance in industry. In order to solve current industrial problems, exploit emerging digital technologies and elevate future industries, it will be necessary to develop new maintenance approaches. The mapping between the criteria of DM and maintenance problems shows the potential of this concept and gives a reason to examine it empirically in future work.

Originality/value

This paper aims to help maintenance professionals from both academia and industry to understand and reflect on the problems related to maintenance, as well as to comprehend the requirements of a digitalised maintenance and challenges that may arise.

Details

Journal of Quality in Maintenance Engineering, vol. 28 no. 2
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 1 March 2003

Brian Wood

Alternative approaches to maintenance are facilitating a fresh look at design and operation of buildings. For some time, planned preventive maintenance has been the…

1515

Abstract

Alternative approaches to maintenance are facilitating a fresh look at design and operation of buildings. For some time, planned preventive maintenance has been the predominant paradigm, based on periodic condition surveys, predictions of future performance, and production of programmes of work. Advances in technology and management techniques have enabled more rapid responses and a focus on meeting user needs. Also there has been a growth of interest in sustainability and “saving the planet”. This paper examines the concepts presented by the author at the Brisbane conference of CIB W70. Suggests that designing and providing for today’s needs is difficult enough without trying to anticipate unknown futures. “Take therefore no thought for the morrow; for the morrow shall take thought for the things of itself” (Matthew 6:34). Work stress could be reduced for facilities and maintenance managers by providing the “right” building – right design; right time; right place; nothing to worry about.

Details

Facilities, vol. 21 no. 3/4
Type: Research Article
ISSN: 0263-2772

Keywords

Article
Publication date: 1 May 2019

Arian Razmi-Farooji, Hanna Kropsu-Vehkaperä, Janne Härkönen and Harri Haapasalo

The purpose of this paper is twofold: first, to understand data management challenges in e-maintenance systems from a holistically viewpoint through summarizing the…

Abstract

Purpose

The purpose of this paper is twofold: first, to understand data management challenges in e-maintenance systems from a holistically viewpoint through summarizing the earlier scattered research in the field, and second, to present a conceptual approach for addressing these challenges in practice.

Design/methodology/approach

The study is realized as a combination of a literature review and by the means of analyzing the practices on an industry leader in manufacturing and maintenance services.

Findings

This research provides a general understanding over data management challenges in e-maintenance and summarizes their associated proposed solutions. In addition, this paper lists and exemplifies different types and sources of data which can be collected in e-maintenance, across different organizational levels. Analyzing the data management practices of an e-maintenance industry leader provides a conceptual approach to address identified challenges in practice.

Research limitations/implications

Since this paper is based on studying the practices of a single company, it might be limited to generalize the results. Future research topics can focus on each of mentioned data management challenges and also validate the applicability of presented model in other companies and industries.

Practical implications

Understanding the e-maintenance-related challenges helps maintenance managers and other involved stakeholders in e-maintenance systems to better solve the challenges.

Originality/value

The so-far literature on e-maintenance has been studied with narrow focus to data and data management in e-maintenance appears as one of the less studied topics in the literature. This research paper contributes to e-maintenance by highlighting the deficiencies of the discussion surrounding the perspectives of data management in e-maintenance by studying all common data management challenges and listing different types of data which need to be acquired in e-maintenance systems.

Details

Journal of Quality in Maintenance Engineering, vol. 25 no. 3
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 6 May 2020

Jon Bokrantz, Anders Skoogh, Cecilia Berlin and Johan Stahre

Scholars and practitioners within industrial maintenance management are focused on understanding antecedents, correlates and consequences of the concept of “Smart…

Abstract

Purpose

Scholars and practitioners within industrial maintenance management are focused on understanding antecedents, correlates and consequences of the concept of “Smart Maintenance,” which consists of the four dimensions, namely, data-driven decision-making, human capital resource, internal integration and external integration. In order to facilitate this understanding, valid and reliable empirical measures need to be developed. Therefore, this paper aims to develop a psychometric instrument that measures the four dimensions of Smart Maintenance.

Design/methodology/approach

The results from two sequential empirical studies are presented, which include generating items to represent the constructs, assessment of content validity, as well as an empirical pilot test. With input from 50 industrial experts, a pool of 80 items that represent the constructs are generated. Thereafter, using data from 42 industrial and academic raters, the content validity of all items is assessed quantitatively. Finally, using data from 59 manufacturing plants, the dimensionality and factor structure of the instrument are tested.

Findings

The authors demonstrate content validity and provide evidence of good model fit and psychometric properties for one-factor models with 8–11 items for each of the four constructs, as well as a combined 24-item four-factor model.

Originality/value

The authors provide recommendations for scholarly use of the instrument in further theory-testing research, as well as its practical use to assess, benchmark and longitudinally evaluate Smart Maintenance within the manufacturing industry.

Details

International Journal of Operations & Production Management, vol. 40 no. 4
Type: Research Article
ISSN: 0144-3577

Keywords

1 – 10 of over 8000