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1 – 10 of over 2000
Article
Publication date: 7 August 2017

Ming-Yi You

The purpose of this paper is to propose a predictive maintenance (PdM) system for hybrid degradation processes with continuous degradation and sudden damage to improve maintenance…

Abstract

Purpose

The purpose of this paper is to propose a predictive maintenance (PdM) system for hybrid degradation processes with continuous degradation and sudden damage to improve maintenance effectiveness.

Design/methodology/approach

The PdM system updates the degradation model using partial condition monitoring information based on degradation type judgment. In addition, an extended multi-step-ahead updating stopping condition is adopted for performance enhancement of the PdM system.

Findings

An extensive numerical investigation compares the performance of the PdM system with the corresponding preventive maintenance (PM) policy. By carefully choosing the updating stopping condition, the PdM policy performs better than the corresponding PM policy.

Research limitations/implications

The proposed PdM system is applicable to single-unit systems. And the continuous degradation process should be well modeled by the stochastic linear degradation model (Gebraeel et al., 2009).

Originality/value

In literature, there are abundant studies on PdM policies for continuous degradation processes. However, research on hybrid degradation processes still focuses on condition-based maintenance policy and a PdM policy for a hybrid degradation process is still unreported. In this paper, a PdM system for hybrid degradation processes with continuous degradation and sudden damage is proposed. The PdM system decides PM schedules by fully utilizing the condition monitoring data of each specific product, and can hopefully improve maintenance effectiveness.

Details

International Journal of Quality & Reliability Management, vol. 34 no. 7
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 13 February 2019

Kong Fah Tee and Ejiroghene Ekpiwhre

The purpose of this paper is to present a study of reliability-centred maintenance (RCM), which is conducted on the key sub-assets of a newly constructed road junction…

Abstract

Purpose

The purpose of this paper is to present a study of reliability-centred maintenance (RCM), which is conducted on the key sub-assets of a newly constructed road junction infrastructure in Nigeria.

Design/methodology/approach

The classical RCM methodology, a type of RCM, which has a top down, zero-based approach for maintenance analysis, is implemented in this study.

Findings

The implementation of the classical RCM is successful in its application of various PM policies assigned to the assets and it shows that its application in the highway industry could reduce excessive maintenance backlog and frequent reactive maintenance by effective optimisation of its preventive maintenance (PM) intervals.

Practical implications

Road junctions are originators of more than 70 per cent of road traffic congestion and account for high accident rate. The traditional methods of reliability assurance used in the highway industry such as reactive maintenance and routine maintenance are often inadequate to meet the round the clock usage demands of these assets, thus the consideration for the application of a systematic RCM process for maintaining the system function by selecting and applying effective PM tasks.

Originality/value

It uses an approach that critically develops and analyses thoroughly preventive and continuous maintenance strategy in a new circumstance with environment of uncertainty and limited operating data. The case-based reasoning cycle has been applied in the RCM approach with real-time data obtained from a UK-based network maintenance management system for highway infrastructures.

Details

International Journal of Quality & Reliability Management, vol. 36 no. 5
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 19 February 2020

Shashidhar Kaparthi and Daniel Bumblauskas

The after-sale service industry is estimated to contribute over 8 percent to the US GDP. For use in this considerably large service management industry, this article provides…

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Abstract

Purpose

The after-sale service industry is estimated to contribute over 8 percent to the US GDP. For use in this considerably large service management industry, this article provides verification in the application of decision tree-based machine learning algorithms for optimal maintenance decision-making. The motivation for this research arose from discussions held with a large agricultural equipment manufacturing company interested in increasing the uptime of their expensive machinery and in helping their dealer network.

Design/methodology/approach

We propose a general strategy for the design of predictive maintenance systems using machine learning techniques. Then, we present a case study where multiple machine learning algorithms are applied to a particular example situation for an illustration of the proposed strategy and evaluation of its performance.

Findings

We found progressive improvements using such machine learning techniques in terms of accuracy in predictions of failure, demonstrating that the proposed strategy is successful.

Research limitations/implications

This approach is scalable to a wide variety of applications to aid in failure prediction. These approaches are generalizable to many systems irrespective of the underlying physics. Even though we focus on decision tree-based machine learning techniques in this study, the general design strategy proposed can be used with all other supervised learning techniques like neural networks, boosting algorithms, support vector machines, and statistical methods.

Practical implications

This approach is applicable to many different types of systems that require maintenance and repair decision-making. A case is provided for a cloud data storage provider. The methods described in the case can be used in any number of systems and industrial applications, making this a very scalable case for industry practitioners. This scalability is possible as the machine learning techniques learn the correspondence between machine conditions and outcome state irrespective of the underlying physics governing the systems.

Social implications

Sustainable systems and operations require allocating and utilizing resources efficiently and effectively. This approach can help asset managers decide how to sustainably allocate resources by increasing uptime and utilization for expensive equipment.

Originality/value

This is a novel application and case study for decision tree-based machine learning that will aid researchers in developing tools and techniques in this area as well as those working in the artificial intelligence and service management space.

Details

International Journal of Quality & Reliability Management, vol. 37 no. 4
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 10 December 2019

Narges Hemmati, Masoud Rahiminezhad Galankashi, D.M. Imani and Farimah Mokhatab Rafiei

The purpose of this paper is to select the best maintenance policy for different types of equipment of a manufacturer integrating the fuzzy analytic hierarchy process (FAHP) and…

Abstract

Purpose

The purpose of this paper is to select the best maintenance policy for different types of equipment of a manufacturer integrating the fuzzy analytic hierarchy process (FAHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) models.

Design/methodology/approach

The decision hierarchy of this research includes three levels. The first level aims to choose the best maintenance policy for different types of equipment of an acid manufacturer. These equipment pieces include molten sulfur ponds, boiler, absorption tower, cooling towers, converter, heat exchanger and sulfur fuel furnace. The second level includes decision criteria of added-value, risk level and the cost. Lastly, the third level comprises time-based maintenance (TBM), corrective maintenance (CM), shutdown maintenance and condition-based maintenance (CBM) as four maintenance policies.

Findings

The best maintenance policy for different types of equipment of a manufacturer is the main finding of this research. Based on the obtained results, CBM policy is suggested for absorption tower, boiler, cooling tower and molten sulfur ponds, TBM policy is suggested for converters and heat exchanger and CM policy is suggested for a sulfur fuel furnace.

Originality/value

This research develops a novel model by integrating FAHP and an interval TOPSIS with concurrent consideration of added-value, risk level and cost to select the best maintenance policy. According to the highlights of the previous studies conducted on maintenance policy selection and related tools and techniques, an operative integrated approach to combine risk, added-value and cost with integrated fuzzy models is not developed yet. The majority of the previous studies have considered classic fuzzy approaches such as FAHP, FANP, Fuzzy TOPSIS, etc., which are not completely capable to reflect the decision makers’ viewpoints.

Details

International Journal of Quality & Reliability Management, vol. 37 no. 9/10
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 2 September 2019

Kateryna Pollack and Jan Clemens Bongaerts

Priorities of decarbonizing the mining sector together with an availability of cost-effective technological solutions lead renewable energy (RE) to become an attractive energy…

320

Abstract

Purpose

Priorities of decarbonizing the mining sector together with an availability of cost-effective technological solutions lead renewable energy (RE) to become an attractive energy source for the mining industry. Several pilot projects are run as hybrid systems, providing additional capacity to traditional energy systems. The purpose of this paper is to develop a mathematical model as a decision-making tool. The decision refers to a replacement of the fossil fuel system contains by the hybrid system in the sense of no return.

Design/methodology/approach

Four systems are considered. System one contains only a diesel plant. System two consists of a hybrid energy system with a photovoltaic (PV) part and a genset as back-up. System three includes a conventional natural gas combined cycle (CGCC) plant. Finally, system four covers a hybrid energy system with a PV part and CGCC turbine. The mathematical model is based upon the well-known concept of levelized cost of electricity.

Findings

The scenarios account for the degradation rate of PV modules, the PV yields of mines in different locations and the greenhouse gas emissions impact. The results show the break-even times of each scenario and the years of no return for the four systems in each scenario.

Research limitations/implications

The solution of the model is performed for two case-studies. Case study 1 compares the diesel and hybrid PV-diesel systems. Case study 2 compares the CGCC and hybrid PV-natural gas systems.

Practical implications

This model can be generalized to all mining settings, with specific practical implications for off-grid mines.

Social implications

The results of this paper bring a valuable contribution to carbon dioxide emissions reduction.

Originality/value

The paper aims to enhance the attention of decision-makers on fossil fuel and RE technologies increase the attractiveness of RE in powering mining operations.

Details

International Journal of Energy Sector Management, vol. 14 no. 1
Type: Research Article
ISSN: 1750-6220

Keywords

Article
Publication date: 4 May 2020

Anh Thi Le and Swee-Yong Pung

This paper aims to investigate the reusability of metal/metal oxide-coupled ZnO nanorods (ZnO NRs) to degrade rhodamine B (RhB).

Abstract

Purpose

This paper aims to investigate the reusability of metal/metal oxide-coupled ZnO nanorods (ZnO NRs) to degrade rhodamine B (RhB).

Design/methodology/approach

ZnO NRs particles were synthesized by precipitation method and used to remove various types of metal ions such as Cu2+, Ag+, Mn2+, Ni2+, Pb2+, Cd2+ and Cr2+ ions under UV illumination. The metal/metal oxide-coupled ZnO NRs were characterized by scanning electron microscope, X-ray diffraction and UV-Vis diffuse reflectance. The photodegradation of RhB dye by these metal/metal oxide-coupled ZnO NRs under UV exposure was assessed.

Findings

The metal/metal oxide-coupled ZnO NRs were successfully reused to remove RhB dye in which more than >90% of RhB dye was degraded under UV exposure. Furthermore, the coupling of Ag, CuO, MnO2, Cd and Ni particles onto the surface of ZnO NRs even enhanced the degradation of dye. The dominant reactive species involved in the degradation of RhB dye were OH- and O2-free radicals.

Research limitations/implications

The coupling of metal/metal oxide onto the surface of ZnO NRs after metal ions removal could affect the photocatalytic performance of ZnO NRs in the degradation of organic pollutants in subsequent stage.

Practical implications

A good reusability performance of metal/metal oxide-coupled ZnO NRs make ZnO NRs become a desirable photocatalyst material for the treatment of wastewater, which consists of both heavy metal ions and organic dyes.

Originality/value

Metal/metal oxide coupling onto the surface of ZnO NRs particles improved subsequent UV-assisted photocatalytic degradation of RhB dye.

Details

Pigment & Resin Technology, vol. 50 no. 1
Type: Research Article
ISSN: 0369-9420

Keywords

Article
Publication date: 1 July 2014

Krzysztof Majerski, Barbara Surowska, Jarosław Bieniaś, Patryk Jakubczak and Monika Ostapiuk

The purpose of this paper is to present microstructural and fractographic analysis of damage in aluminum (2024T3)/carbon-fiber reinforced laminates (AlC) after static tensile…

Abstract

Purpose

The purpose of this paper is to present microstructural and fractographic analysis of damage in aluminum (2024T3)/carbon-fiber reinforced laminates (AlC) after static tensile test. The influence of fiber orientation on the failure was studied and discussed.

Design/methodology/approach

The subject of examination was AlC. The fiber–metal laminates (FMLs) were manufactured by stacking alternating layers of 2024-T3 aluminum alloy (0.3 mm per sheets) and carbon/epoxy composites made of unidirectional prepreg tape HexPly system (Hexcel, USA) in [0], [± 45] and [0/90]S configuration. The fractographic analysis was carried out after static tensile test on the damage area of the specimens. The mechanical tests have been performed in accordance to ASTM D3039. The microstructural and fractographic analysis of FMLs were studied using optical (Nikon SMZ1500, Japan) and scanning electron microscope (Zeiss Ultra Plus, Germany).

Findings

FMLs based on aluminum and carbon/epoxy composite are characterized by high tensile properties depending on their individual components and the orientation of the reinforcing fibers, failure of hybrid laminates indicates the complexity process of degradation of these materials. The nature of damage in FML layers is similar to that typical in polymer composites with interlaminar delaminations, transverse cracks of the composite layers, degradation of fiber/matrix interface, damage process in FMLs is also associated mainly with interface between metal and fiber reinforced composite. The mixed damage – cohesive and adhesive – was observed.

Originality/value

One of the most important aspect in the designing and manufacturing process in the service life of composite structures is damage mechanisms. The damage processes in composite materials, particularly in FMLs, are more complex in comparison to metal materials and fiber reinforced polymers.

Details

Aircraft Engineering and Aerospace Technology: An International Journal, vol. 86 no. 4
Type: Research Article
ISSN: 0002-2667

Keywords

Article
Publication date: 13 August 2018

Xiaomei Yang and Jianchao Zeng

According to the relevance of product quality and machine degradation state, a hybrid maintenance policy is designed. The paper aims to discuss this issue.

Abstract

Purpose

According to the relevance of product quality and machine degradation state, a hybrid maintenance policy is designed. The paper aims to discuss this issue.

Design/methodology/approach

Product quality control and machine maintenance are considered simultaneously in this policy. Based on this policy, the economic model of x-bar control chart is proposed using statistical process control and renewal reward theory.

Findings

This model is solved by genetic algorithm and the experimental results validated its feasibility.

Originality/value

In this model, the four corresponding relationship, which is between product quality monitoring result and machine degradation state, is analyzed.

Details

Journal of Quality in Maintenance Engineering, vol. 24 no. 3
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 22 April 2020

Maryam Khashij, Mohammad Mehralian and Zahra Goodarzvand Chegini

The purpose of this study to investigate acetaminophen (ACT) degradation efficiencies by using ozone/persulfate oxidation process in a batch reactor. In addition, the effects of…

Abstract

Purpose

The purpose of this study to investigate acetaminophen (ACT) degradation efficiencies by using ozone/persulfate oxidation process in a batch reactor. In addition, the effects of various parameters on the ACT removal efficiency toward pathway inference of ACT degradation were investigated.

Design/methodology/approach

The experiments were in the 2 L glass vessels. Ozone gas with flow rate at 70 L.h−1 was produced by ozone generator. After the adjustment of the pH, various dosages of persulfate (1, 3, 5, 7 and 9 mmol.L−1) were then added to the 500 mL ACT-containing solution with 150 mg.L−1 of concentration. Afterward, ozone gas was diffused in glass vessels. The solution after reaction flowed into the storage tank for the detection. The investigated parameters included pH and the amount of ozone and persulfate addition. For comparison of the ACT degradation efficiency, ozone/persulfate, ozone and persulfate oxidation in reactor was carried out. The ACT concentration using a HPLC system equipped with 2998 PDA detector was determined at an absorbance of 242 nm.

Findings

ACT degradation percentage by using ozone or persulfate in the process were at 63.7% and 22.3%, respectively, whereas O3/persulfate oxidation process achieved degradation percentage at 91.4% in 30 min. Degradation efficiency of ACT was affected by different parameter like pH and addition of ozone or persulfate, and highest degradation obtained when pH and concentrations of persulfate and ozone was 10 and 3 mmol.L−1 and 60 mg.L−1, respectively. O3, OH and SO4− were evidenced to be the radicals for degradation of ACT through direct and indirect oxidation. Gas chromatography–mass spectrometer analysis showed intermediates including N-(3,4-dihydroxyphenyl) formamide, hydroquinone, benzoic acid, 4-methylbenzene-1,2-diol, 4-aminophenol.

Practical implications

This study provided a simple and effective way for degradation of activated ACT as emerging contaminants from aqueous solution. This way was conducted to protect environment from one of the most important and abundant pharmaceutical and personal care product in aquatic environments.

Originality/value

There are two main innovations. One is that the novel process is performed successfully for pharmaceutical degradation. The other is that the optimized conditions are obtained. In addition, the effects of various parameters on the ACT removal efficiency toward pathway inference of ACT degradation were investigated.

Details

Pigment & Resin Technology, vol. 49 no. 5
Type: Research Article
ISSN: 0369-9420

Keywords

Article
Publication date: 8 May 2017

Nabil Laayouj and Hicham Jamouli

The purpose of this paper is to create a new method of prognosis based on remaining useful life (RUL) prediction for degradation assessment.

Abstract

Purpose

The purpose of this paper is to create a new method of prognosis based on remaining useful life (RUL) prediction for degradation assessment.

Design/methodology/approach

In the present paper the authors describe a new method of prognosis to improve the accuracy of forecasting the system state. This framework of forecasting integrates the model-based information and the hybrid approach, which employs the structured residuals in the first part and the particle filter in the second part.

Findings

The performance of the suggested fusion framework is employed to predict the RUL of battery pack in hybrid electric vehicle. The results show that the proposed method is plausible due to the good prediction of RUL, and can be effectively applied to many systems for prognosis.

Originality/value

In this study the authors illustrate how the suggested method can provide an accurate prediction of the RUL over conventional data-driven methods without physical model and classical particle filter with a single damage model.

Details

Journal of Quality in Maintenance Engineering, vol. 23 no. 2
Type: Research Article
ISSN: 1355-2511

Keywords

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