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The purpose of this paper is to suggest a framework for extracting the sequential patterns of maintenance activities and related spare parts information from historical records of maintenance data with pre-defined support or threshold values.

A data mining approach has been adopted for predicting the maintenance activity along with spare parts. It starts with a collection of spare parts and maintenance data, and then the development of sequential patterns followed by formation of frequent spare part groups, and finally, integration of sequential maintenance activities with the associated spare parts.

This study suggests a framework for extracting the sequential patterns of maintenance activities from historical records of maintenance data with pre-defined support or threshold values. A rule-based approach is proposed in this paper to predict the occurrence of next maintenance activity along with the information of spare parts consumption for that maintenance activity.

Presented model can be extended for analyzing the failure maintenance activities and performing root cause analysis that can give more valuable suggestion to maintenance managers to take corrective actions prior to next occurrence of failures. In addition, the timestamp information can be utilized to prioritize the maintenance activity that is ignored in this study.

The proposed model has a high potential for industrial applications and is validated through a case study. The study suggests that the model gives a better approach for selecting spare parts based on their similarity or correlation, considering their actual occurrence during maintenance activities. Apart from this, the clustering of spare parts also trains maintenance manager to learn about the dependency among the spares for group stocking and maintaining the parts availability during maintenance activities.

This study has used the technique of data mining to find dependent spare parts itemset from the database of the company and developed the model for associated spare parts requirement for subsequent maintenance activity.

The purpose of this paper is to present a fuzzy-rule-based model to classify spare parts inventories considering multiple criteria for better management of maintenance activities to overcome production down situation.

Fuzzy-rule-based approach for multi-criteria decision making is used to classify the spare parts inventories. Total cost is computed for each group considering suitable inventory policies and compared with other existing models.

Fuzzy-rule-based multi-criteria classification model provides better results as compared to aggregate scoring and traditional ABC classification. This model offers the flexibility for inventory management experts to provide their subjective inputs.

The web-based model developed in this paper can be implemented in various industries such as manufacturing, chemical plants, and mining, etc., which deal with large number of spares. This method classifies the spares into three categories A, B and C considering multiple criteria and relationships among those criteria. The framework is flexible enough to add additional criteria and to modify fuzzy-rule-base at any point of time by the decision makers. This model can be easily integrated to any customized Enterprise Resource Planning applications.

The value of this paper is in applying Fuzzy-rule-based approach for Multi-criteria Inventory Classification of spare parts. This rule-based approach considering multiple criteria is not very common in classification of spare parts inventories. Total cost comparison is made to compare the performance of proposed model with the traditional classifications and the result shows that proposed fuzzy-rule-based classification approach performs better than the traditional ABC and gives almost the same cost as aggregate scoring model. Hence, this method is valid and adds a new value to spare parts classification for better management decisions.

The purpose of this paper is to construct a fuzzy logic model that acts as a decision support system to minimize inventory-related costs in the field of industrial maintenance. Achieving a balance between the unavailability and over-storage of spare parts is a problem with potentially significant consequences. That significance increases proportionally with the ever-increasing challenge of reducing overall cost. Either scenario can result in substantial financial losses because of the interruption of production or the costs of tied-up capital, also called the “solidification of capital.” Moreover, there is that additional problem of the expiry of parts on the shelf.

The proposed approach relies on inputs from experts with consideration for incompleteness and inaccuracy. Two levels of decision are considered simultaneously. The first is whether a part should be stored or ordered when needed. The second involves comparing suppliers with their batch-size offers based on user-determined criteria. A mathematical model is developed in parallel for validation.

The results indicate that the fuzzy logic approach is accurate and satisfactory for this application and that it is advantageous because of its limited sensitivity to the inaccuracy and/or incompleteness of data. In addition, the approach is practical because it requires minimal user effort.

To the best of the authors’ knowledge, the exploitation of fuzzy-logic altogether with limited sensitivity experts' inputs were never combined for the solution of this particular problem; however, this approach's positive impact is expected to be highly significant in solving a chronic problem in industry.

The purpose of this paper is to present a new hybrid approach based on criticality analysis and optimisation to deal with spare parts inventory management in the initial provisioning phase in the mining industry. Spare parts represent a significant part of mining companies' expenditures, so it is important to develop new approaches to reduce the total inventory value of these items.

This hybrid approach combines qualitative and quantitative methods based on VED (vital, essential and desirable) analysis, analytical hierarchical process (AHP), and e-constraint optimisation method to obtain the spare parts to be stocked. The study was applied to a large mining company. The mineral sector was chosen due to the great importance to the emerging Brazilian economy and the lack of researches in this sector. In addition, the spare parts have a relevant weight on the total inventory cost.

Present a novel approach combining multi-objective optimisation and multi-criteria evaluation approaches to tackle the inventory decision in spare parts management. This work also defines and classifies relevant criteria for spare parts management in the mineral sector validated by specialists. The proposed approach achieves an average increase of 20.2% in the criticality and 16.6% in the number of items to be stocked compared to the historical data of the surveyed company.

This paper applies the proposed approach to a mining company in Brazil. Future research in other companies or regions should analyse the adequacy of the criticality criteria, hierarchy and weights adopted in this paper.

The proposed approach is useful for mining industries that deal with a large variety of resource constraints as it helps in formulating appropriate spare part strategies to rationalise financial resources at both tactical and strategic levels.

The paper presents a new hybrid method combining the AHP a multi-criteria decision making (MCDM) approach coupled with e-constraint optimisation to deal with spare parts inventory management allowing for a better spare parts inventory analysis in the initial provisioning phase and providing managers with a systematic tool to analyse the trade-off between spare parts criticality and total inventory value.

Spare Parts Management (SPM) and Industry 4.0 has proven their importance. However, employment of Industry 4.0 solutions for SPM is at emerging stage. To address the issue, this article is aimed toward a systematic literature review on SPM in Industry 4.0 era and identification of research gaps in the field with prospects.

Research articles were reviewed and analyzed through a content-based analysis using four step process model. The proposed framework consists of five categories such as Inventory Management, Types of Spares, Circularity based on 6Rs, Performance Indicators and Strategic and Operational. Based on these categories, a total of 118 research articles published between 1998 and 2022 were reviewed.

The technological solutions of Industry 4.0 concepts have provided numerous opportunities for SPM. Industry 4.0 hi-tech solutions can enhance agility, operational efficiency, quality of product and service, customer satisfaction, sustainability and profitability.

The review of articles provides an integrated framework which recognizes implementation issues and challenges in the field. The proposed framework will support academia and practitioners toward implementation of technological solutions of Industry 4.0 in SPM. Implementation of Industry 4.0 in SPM may help in improving the triple bottom line aspect of sustainability which can make significant contribution to academia, practitioners and society.

The examination uncovered a scarcity of research in the intersection of SPM and Industry 4.0 concepts, suggesting a significant opportunity for additional investigative efforts.

The purpose of this paper is to analyze issues pertaining to maintenance performance and to develop a framework that addresses challenges of maintenance management of an international lube blending plant in Malaysia. This study capitalizes on the contribution of selected maintenance department stakeholders from within the plant to develop “tailor-made” intervention strategies for maintenance performance improvement.

The study employed two focus group workshops to ascertain issues facing the maintenance department and identify intervention strategies. The final phase of the study employed fuzzy Delphi method (FDM) to prioritize and rank the intervention strategies for performance improvement.

The first focus group workshop identified 106 issues which could be classified under aspects of spare parts (n=8), equipment (n=14), communication (n=12), non-technical resource (n=8), health, safety and environment (n=4), technical skills and recruitment (n=27), and handling and procedures (n=33). Based on these findings, the second focus group revealed 28 significant performance initiatives to improve the issues identified for maintenance performance improvement. Through the FDM, 18 performance initiatives were ranked and prioritized. Performance improvement through leadership category leads the overall initiatives followed by equipment maintenance management, talent management, work environment and vendor management.

Interesting implications for maintenance management theory would be realized if future research were able to demonstrate that certain aspects or dimensions were related to high performing plant maintenance, and not with low performing ones. Apparently, the present study is not able to provide this clue because it is merely a case study of a single company.

As ILBP attempts to implement maintenance performance improvement, it is pertinent for the management to understand the relevant performance issues and concerns. The appropriate enablers have been identified and must be initiated to chart the strategic role of their maintenance organization.

This study contributes toward further understanding of the maintenance performance management. It has demonstrated the need of organizations to make infrastructural investments such as quality leadership, employee training and empowerment, to name a few, to strategically enhance their maintenance capabilities.

This study uses the FDM for the decision-making process of improving plant maintenance performance. It adds value to the body of knowledge of plant operation management.

This study aims to investigate a new circuitous minichannel cold plate (MCP) design involving flow fragmentation. The overall thermal performance and the temperature uniformity analysis are performed and compared with the traditional serpentine design. The substrate thickness and its thermal conductivity are varied to analyse the effect of axial-back conduction due to the conjugate nature of heat transfer.

The traditional serpentine minichannel is modified into five new fragmented designs with two inlets and two outlets. A three-dimensional numerical model involving the effect of conjugate heat transfer with a single-phase laminar fluid flow subjected to constant heat flux is solved using a finite volume-based computational fluid dynamics solver.

The minimum and maximum temperature differences are observed for the two branch fragmented flow designs. The two-branch and middle channel fragmented design shows better temperature uniformity over other designs while the three-branch fragmented designs exhibited better hydrodynamic performance.

MCPs could be used as an indirect liquid cooling method for battery thermal management of pouch and prismatic cells. Coupling the modified cold plates with a battery module and investigating the effect of different battery parameters and environmental effects in a transient state are the prospects for further research.

The study involves several aspects of evaluation for a conclusive decision on optimum channel design by analysing the performance plot between the temperature uniformity index, average base temperature and overall thermal performance. The new fragmented channels are designed in a way to facilitate the fluid towards the outlet in the minimum possible path thereby reducing the pressure drop, also maximizing the heat transfer and temperature uniformity from the substrate due to two inlets and a reversed-flow pattern. Simplified minichannel designs are proposed in this study for practical deployment and ease of manufacturability.

This paper aims to emphasize on studying various geometrical modification performed in wavy and raccoon microchannel by manipulating parameters, i.e. waviness (γ), expansion factor (α), wall to fluid thermal conductivity ratio (k_sf), substrate thickness to channel height ratio (d_sf) and Reynolds number (Re) for obtaining optimum parameter(s) that leads to higher heat dissipation rate.

A three-dimensional solid-fluid conjugate heat transfer numerical model is designed to capture flow characteristics and heat transfer in single-phase laminar flow microchannels. The governing equations are solved using finite volume method.

The results are presented in terms of average base temperature, average Nusselt number, pressure drop, dimensionless local heat flux, dimensionless wall and bulk fluid temperature, local Nusselt number and performance factor including axial conduction number. Heat dissipation rate with raccoon microchannel configuration is found to be higher compared to straight and wavy microchannel. With waviness of γ = 0.167, and 0.267 in wavy and raccoon microchannel, respectively, performance factor attains maximum value compared to other waviness for all values of Reynolds number. It is also found that the effect of axial wall conduction in wavy and raccoon microchannel is negligible. Additionally, thermal performance of wavy and raccoon microchannel is compared with straight microchannel.

In recent past years, much complex design of microchannel has been proposed for heat transfer enhancement, but the feasibility of available manufacturing techniques to fabricate complex geometries is still questionable. However, fabrication of wavy and raccoon microchannel is easy, and their heat dissipation capability is higher.

This makes the difference in wall and bulk fluid temperature smaller. Thus, present work highlighted the dominance of axial wall conduction on thermal and hydrodynamic performance of wavy and raccoon microchannel under conjugate heat transfer situation.

This study aims to capture the heat transfer and entropy generation characteristics of temperature-dependent nano-encapsulated phase change material (NEPCM) slurry in a hybrid wavy microchannel. In addition, the effect of substrate material combined with NEPCM slurry on conjugate heat transfer condition is captured for different microchannel heat sinks.

A novel “hybrid wavy microchannel” is proposed to enhance the overall heat transfer and reduce the pressure drop by combining wavy and raccoon geometry. NEPCM–water slurry is implied in the hybrid wavy, conventional wavy and raccoon microchannel. A user-defined function (UDF) is used to observe the effect of phase-change of paraffin material in thermophysical properties of NEPCM–water nanofluid. All three (hybrid, wavy, raccoon) microchannels are engraved on a rectangular substrate of 1.8 mm width (ωs) and 30 mm length (L), respectively. For hybrid, wavy and raccoon microchannel, waviness (γ) of 0.067 is selected for the investigation.

The result shows that NEPCM particle presence reduces the fluid domain temperature. The thermal performance of proposed Heat sink 2 is found better than the Heat sink 1. The effect of the geometrical modification, wall thermal conductivity, different volumetric concentrations of nanoparticles (ϕ ∼ 1 – 5%) and Reynolds number (Re ∼ 100 – 500) on thermodynamic irreversibility is also observed. Additionally, the effect of thermal and frictional entropy generation is reduced with a combination of NEPCM slurry and higher conductive material for all heat sinks.

A combination of NEPCM slurry with laminar flow microchannel cooling system emerged as a better alternative over other cooling techniques for higher power density devices such as microprocessors, electronic radar systems, aerospace applications, semiconductors, power electronics in modern electronic vehicles, high power lasers, etc.

The phase-change process of the NEPCM slurry is tracked under conjugate heat transfer in a hybrid wavy microchannel. Furthermore, the phase-change process of NEPCM slurry is captured with different heat sink materials (SS316, silicon and copper) under conjugate heat transfer situation for different heat sinks and concentrations (ϕ ∼ 1–5) of NEPCM.

The purpose of this paper is to analyze the thermal, hydraulic and entropy generation characteristics for the magneto-hydrodynamic (MHD) pressure-driven flow of Al₂O₃-water nanofluid through an asymmetric wavy channel.

Galerkin finite element method is used to solve the governing transport equations numerically within the computational domain using the appropriate boundary conditions. The temperature and flow fields are computed by varying Reynolds number (Re), Hartmann number (Ha) and nano-particle volume fraction (ϕ) in the following range: 10 ≤ Re ≤ 500, 0 ≤ Ha ≤ 75 and 0 ≤ ϕ ≤ 5%.

The formation of the recirculation zones in the wavy passages, the size of it and the strength of the vortices formed can be modulated by the application of the magnetic field. The overall heat transfer rate increases with Ha for all ϕ both for a lower and higher regime of Re although the enhancement is more for lower values of Re and nanofluids as compared to base fluid and for intermediate values of Re, the effect of a magnetic field is almost insignificant. The magnetic performance factor (PF_magnetic) decreases with Ha although the rate of decrement varies with Re. The increase ϕ also enhances PF_magnetic especially at lower and higher values of Re. The addition of nano-particle enhances the entropy generation at lower values of the Re, while the opposite effect is seen for higher values of Re.

The present study has enormous practical relevance for the design of heat exchanger applied for solar collectors, process plants, textile and aerospace applications.

The combined effects on the heat transfer rate and the associated pressure drop penalty due to the applied magnetic field for the flow of nanofluid through an asymmetric wavy channel have not been reported to date. The effect of the magnetic field on the formation of recirculation zones and hot spot intensity in the asymmetric wavy channel has been examined in detail. The PF_magnetic is investigated first time for the MHD nanofluid flow through a wavy channel.