Fuzzy adaptive preventive maintenance in a manufacturing control system: a step towards self-maintenance

Yuniarto, Muhammad Nur; Labib, Ashraf

doi:10.1080/13528160500245723

Cited by 27 publications

(11 citation statements)

References 13 publications

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“…This illustrated by the work of [8]. In this work, a framework of integrating preventive maintenance (PM) and manufacturing control system is proposed.…”

Section: Nsf / Epsrc Proposalmentioning

confidence: 98%

Next Generation Maintenance Systems: Towards the Design of a Self-maintenance Machine

Labib

2006

2006 IEEE International Conference on Industrial Informatics

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We describe the evolution of maintenance generations, and the predicted areas of next generation maintenance systems (NGMS).Unmet needs in responsive maintenance are highlighted followed by research and development questions. Key Features of NGMS are outlined and examples of some approaches are highlighted.We then focus on a main characteristic of next generation maintenance systems which is self maintenance capabilities. A self maintenance model is then presented, followed by describing features of self maintenance systems.

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“…This illustrated by the work of [8]. In this work, a framework of integrating preventive maintenance (PM) and manufacturing control system is proposed.…”

Section: Nsf / Epsrc Proposalmentioning

confidence: 98%

Next Generation Maintenance Systems: Towards the Design of a Self-maintenance Machine

Labib

2006

2006 IEEE International Conference on Industrial Informatics

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“…This technique has been applied in a plant of 130 machines producing roof systems for cars [20,22], in a disc brake pad manufacturing company [23], in a desalination plant [24] and in a food processing company [25,26]. Later, it was combined with a fuzzy controller to regulate optimal production according to the recommended maintenance strategy [27]. [19,23,28] The Decision Making Grid is a simple bi-criteria matrix without any aggregation.…”

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confidence: 99%

Assigning machines to incomparable maintenance strategies with ELECTRE-SORT

Ishizaka

Nemery²

2014

Omega

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The increasing demand on productivity and quality requires machines to be constantly available for production. It is therefore crucial to develop an adequate maintenance programme. To facilitate this, several criteria need to be considered, such as: downtime, maintenance frequency, spare parts costs, bottleneck impacts, etc. In the literature, a strategy is selected for each machine with a multi-criteria decision choice method. However, before making an informed decision, each strategy needs to be tested on each machine and then their performances evaluated with a multicriteria decision method. This is time-consuming, inefficient and often unfeasible. As machines' performances are usually systematically collected by industries, a much more practical approach is to assign machines to a maintenance strategy. This is referred to as a sorting problem. However, this problem cannot be solved by existing multi-criteria sorting methods because maintenance strategies cannot always be completely ordered: incomparable strategies exist. Recently, a Decision Making Grid was proposed to allocate machines to incomparable strategies. However, this technique can only be applied to problems with two criteria. In this paper, we have developed ElectreSort, a new sorting method that is able to consider an unlimited number of criteria in order to assign machines to incomparable strategies. A case study illustrates that ElectreSort provides more precise and flexible maintenance strategies than the Decision Making Grid.

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“…During the last decade, several models for maintenance management problems have been incorporating uncertainty of their parameters by using fuzzy sets (e.g. Yuniarto and Labib, 2006;Khanlari et al, 2008;Sharma et al, 2008;Shen et al, 2009). Nevertheless, most of the current literature on maintenance simply omits the uncertainty that is inherent to real processes.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy maintenance costs of a wind turbine pitch control device

Carvalho

Nunes

Telhada

2015

Int. J. Prod. Manag. Eng.

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This paper deals with the problem of estimation maintenance costs for the case of the pitch controls system of wind farms turbines. Previous investigations have estimated these costs as (traditional) "crisp" values, simply ignoring the uncertainty nature of data and information available. This paper purposes an extended version of the estimation model by making use of the Fuzzy Set Theory. The results alert decision-makers to consequent uncertainty of the estimations along with their overall level, thus improving the information given to the maintenance support system.

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Fuzzy adaptive preventive maintenance in a manufacturing control system: a step towards self-maintenance

Cited by 27 publications

References 13 publications

Next Generation Maintenance Systems: Towards the Design of a Self-maintenance Machine

Next Generation Maintenance Systems: Towards the Design of a Self-maintenance Machine

Assigning machines to incomparable maintenance strategies with ELECTRE-SORT

Fuzzy maintenance costs of a wind turbine pitch control device

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