A hybrid reliability-centered maintenance approach for mining transportation machines: a real case in Esfahan

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rana Jafarpisheh ◽  
Mehdi Karbasian ◽  
Milad Asadpour
Keyword(s):  
Decision Making ◽  
High Risk ◽  
Failure Mode ◽  
Mining Industry ◽  
Preference Ranking ◽  
Real Case ◽  
Content Type ◽  
Reliability Centered Maintenance ◽  
Hybrid Reliability ◽  
Critical Machines

PurposeThe purpose of this study is to propose a hybrid reliability-centered maintenance (RCM) approach for mining transportation machines of a limestone complex, a real case in Esfahan, Iran.Design/methodology/approachCriteria for selecting critical machines were collected within literature and selected by decision-makers (DCs), and critical machines have been identified using the preference ranking organization method for enrichment of evaluations (PROMETHEE). Also, multi-criteria decision-making (MCDM) methods were used in addition to failure mode, effects and criticality analysis (FMECA) for selecting and prioritizing high-risk failures as well as optimizing the RCM performance. More specifically, the criteria of severity, detectability and frequency of occurrence were selected for risk assessment based on the previous studies, and were weighted using the analytic hierarchy process (AHP) method. Also, the technique for order of preference by similarity to ideal solution (TOPSIS) has been applied to prioritize failures' risk. Finally, the critical failures were inserted in the RCM decision-making worksheet and the required actions were determined for them.FindingsAccording to the obtained values from PROMEHTEE method, the machine with code 739-7 was selected as the first priority and the most critical equipment. Further, based on results of TOPSIS method, the failure mode of “Lubrication hole clogging in crankpin bearing due poor quality oil,” “Deformation of main bearing due to overwork” and “The piston ring hotness due to unusual increase in the temperature of cylinder” have the highest risks among failure modes, respectively.Originality/valueRCM has been deployed in various studies. However, in the current study, a hybrid MCDM-FMECA has been proposed to cope with high-risk failures. Besides, transportation machineries are one of the most critical equipment in the mining industry. Due to noticeable costs of this equipment, effective and continuous usage of this fleet requires the implementation of proper maintenance strategy. To the best of our knowledge, there is no research which has used RCM for transportation systems in the mining sector, and therefore, the innovation of this research is employment of the proposed hybrid approach for transportation machineries in the mining industry.

Selection of lean manufacturing systems using the PROMETHEE

2008 ◽  
Vol 3 (1) ◽  
pp. 40-70 ◽  
Author(s):  
G. Anand ◽  
Rambabu Kodali
Keyword(s):  
Decision Making ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Strategic Decision ◽  
Computer Integrated Manufacturing ◽  
Preference Ranking ◽  
Manufacturing Strategy ◽  
Manufacturing Companies ◽  
Content Type

PurposeIn recent years, many manufacturing companies are attempting to implement lean manufacturing systems (LMS) as an effective manufacturing strategy to survive in a highly competitive market. Such a process of selecting a suitable manufacturing system is highly complex and strategic in nature. The paper aims to how companies make a strategic decision of selecting LMS as part of their manufacturing strategy, and on what basis such strategic decisions are made by the managers.Design/methodology/approachA case study of a small‐ and medium‐sized enterprise is presented, in which the managers are contemplating on implementing either computer integrated manufacturing systems (CIMS) or LMS. To supplement the decision‐making process, a multi‐criteria decision making (MCDM) model, namely, the preference ranking organisation method for enrichment evaluations (PROMETHEE) is used to analyse how it will impact the stakeholders of the organisation, and the benefits gained.FindingsAn extensive analysis of PROMETHEE model revealed that LMS was the best for the given circumstances of the case.Research limitations/implicationsThe same problem can be extended by incorporating the constraints (such as financial, technical, social) of the organisation by utilising an extended version of PROMETHEE called the PROMETHEE V. Since, a single case study approach has been utilised, the findings cannot be generalized for any other industry.Practical limitations/implicationsThe methodology of PROMETHEE and its algorithm has been demonstrated in a detailed way and it is believed that it will be useful for managers to apply such MCDM tools to supplement their decision‐making efforts.Originality/valueAccording to the authors’ knowledge there is no paper in the literature, which discusses the application of PROMETHEE in making a strategic decision of implementing LMS as a part of an organisation's manufacturing strategy.

Evaluation of energy sources based on sustainability factors using integrated fuzzy MCDM approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Santosh K. Saraswat ◽  
Abhijeet K. Digalwar
Keyword(s):  
Decision Making ◽  
Research Work ◽  
Economic Benefits ◽  
Decision Makers ◽  
Preference Ranking ◽  
Energy Sources ◽  
Content Type ◽  
Weighted Sum Method ◽  
Weight Calculation ◽  
Social Environmental

Purpose The purpose of this paper is to develop an integrated fuzzy multi-criteria decision-making (MCDM) model for evaluation of the energy alternates in India based on their sustainability. Design/methodology/approach A fuzzy analytical hierarchy process approach is used for the weight calculation of the criteria and the fuzzy technique for order preference by similarity to the ideal solution is used for ranking of the energy alternates. Seven energy sources – thermal, gas power, nuclear, solar, wind, biomass and hydro energy are considered for the assessment purpose on the basis of sustainability criteria, namely, economic, technical, social, environmental, political and flexible. Findings The result of the analysis shows that economics is the highest weight criterion, followed by environmental and technical criteria. Solar energy was chosen as the most sustainable energy alternate in India, followed by wind and hydro energy. Research limitations/implications Few other MCDM techniques such as VIseKriterijumska Optimizacija I Kompromisno Resenje (multi-criteria optimization and compromise solution), weighted sum method and preference ranking organization method for enrichment evaluations – II can also be explored for the sustainability ranking of the energy alternates. However, the present model has also provided a good result. Practical implications The present research work will help the decision-makers and organizations in the evaluation and prioritizing the various energy sources on the scale of sustainability. Social implications Research finding provides guidance to government and decision-makers regarding the development of social conditions through energy security, job creation and economic benefits. Originality/value Research work can be act as a supplement for the investors and decision-makers specifically in prioritizing the investment perspective and to support other multi-perspective decision-making problems.

A hybrid multi-criteria decision-making model for optimal coal blending

2019 ◽  
Vol 14 (2) ◽  
pp. 339-359 ◽  
Author(s):  
Shankar Chakraborty ◽  
Ankan Mitra
Keyword(s):  
Decision Making ◽  
Optimization Problems ◽  
Research Work ◽  
Carbon Dioxide Emission ◽  
Preference Ranking ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Geographical Regions ◽  
Coal Blending ◽  
Decision Making Model

Purpose The purpose of this paper is thus to develop a hybrid decision-making model for optimal coal blending strategy. Coal is one of the major resources contributing to generation of electricity and anthropogenic carbon-dioxide emission. Being formed from dead plant matter, it undergoes a series of morphological changes from peat to lignite, and finally to anthracite. Because of non-uniform distribution of coal over the whole earth and continuous variation in its compositions, coals mined from different parts of the world have widely varying properties. Hence, it requires an ideal blending strategy such that the coking coal having the optimal combination of all of its properties can be used for maximum benefit to the steel making process. Design/methodology/approach In this paper, a multi-criteria decision-making approach is proposed while integrating preference ranking organization method for enrichment of evaluations (PROMETHEE II and V) and geometrical analysis for interactive aid (GAIA) method to aid in formulating an optimal coal blending strategy. The optimal decision is arrived at while taking into account some practical implications associated with blending of coal, such as coal price from different reserves. Findings Different grades of coal are ranked from the best to the worst to find out the composition of constituent coals in the final blending process. Coals from the mines of two different geographical regions are considered here so as to prove the applicability of the proposed model. Adoption of this hybrid decision-making model would subsequently improve the performance of coal after blending and help in addressing some sustainability issues, like less pollution. Originality/value As this model takes into account the purchase price of coals from different reserves, it is always expected to provide more realistic solutions. Thus, it would be beneficial to deploy this decision-making model to different blending optimization problems in other spheres of a manufacturing industry. This model can further accommodate some more realistic criteria, such as availability of coal in different reserves as a topic of future research work.

scholarly journals Flying asset

2018 ◽  
Vol 24 (2) ◽  
pp. 152-169 ◽  
Author(s):  
Alberto Martinetti ◽  
Erik Jan Schakel ◽  
Leo A.M. van Dongen
Keyword(s):  
Decision Making ◽  
Traditional Approach ◽  
Unmanned Aircraft ◽  
Research Approach ◽  
Maintenance Strategy ◽  
Component Level ◽  
Content Type ◽  
Reliability Centered Maintenance ◽  
Maintenance Program ◽  
Starting Point

Purpose The purpose of this paper is to create a framework to provide a scalable maintenance program for unmanned aircraft systems (UAS) in order to choose the most suitable and feasible maintenance strategy in terms of reliability. Design/methodology/approach The paper opted for a reliability-centered maintenance-based approach to develop the framework using a UAS as the starting point of the research. A linear and user-friendly design of the methodology based on a Boolean flowchart was chosen in order to lead the analyst through the process avoiding as much as possible subjectivity decision-making issues. Finally, the framework was, on the component level, performed by a UAS company gathering feedback on its applicability. Findings An agile and structured decision-making framework for developing scalable maintenance program of UAS is provided. The proposed solution gives the opportunity to tailor the maintenance strategy to the technical characteristics, considering not only the single component but also situations and conditions in which the machine will operate. Research limitations/implications Because of the chosen research approach, the framework is potentially applicable to every UAS. A first trial of the method was run on a multirotor vehicle equipped with eight electric brushless motors. Further studies focused on different UAS will be mandatory in order to obtain comparable and robust findings and a reliable approach. Practical implications This study offers a different scheme to elaborate a specific maintenance solution related to the characteristics of the system. It strives to remedy the drawbacks of the traditional approach for a manned aircraft not completely suitable for systems with such different functions, features and tasks. The authors believe that the method presented in this paper will provide a new selection tool for choosing maintenance actions based on the features of the UAS. Originality/value This paper provides a new and usable solution to include the maintenance actions in the management of pioneering products. In spite of the maintenance program representing an essential aspect to provide reliable assets, frameworks to create programs and to help manufacturers and users are still difficult to find or to apply to different UAS. This gap enhances the misunderstanding that the maintenance is not required or essential for the unmanned aircrafts management.

scholarly journals Maintenance strategies: Decision Making Grid vs Jack-Knife Diagram

2018 ◽  
Vol 24 (1) ◽  
pp. 61-78 ◽  
Author(s):  
Turuna Seecharan ◽  
Ashraf Labib ◽  
Andrew Jardine
Keyword(s):  
Decision Making ◽  
Industrial Applications ◽  
Maintenance Strategy ◽  
Maintenance Strategies ◽  
Content Type ◽  
Machine Performance ◽  
Equipment Failures ◽  
Maintenance Technicians ◽  
Increasing Demand ◽  
Critical Machines

Purpose Maintenance management is a vital strategic task given the increasing demand on sustained availability of machines. Machine performance depends primarily on frequency and downtime; therefore, ranking critical machines based on these two criteria is important to determine the appropriate maintenance strategy. The purpose of this paper is to compare two methods, using case studies, to allocate maintenance strategies while prioritising performance based on frequency and downtime or Mean Time to Repair: the Decision Making Grid (DMG) and Jack-Knife Diagram (JKD). Design/methodology/approach The literature indicates the need for an approach able to integrate maintenance performance and strategy in order to adapt existing data on equipment failures and to routinely adjust preventive measures. Maintenance strategies are incomparable; one strategy should not be applied to all machines, nor all strategies to the same machine. Findings Compared to the Pareto histogram, the DMG and JKD provide visual representations of the performance of the worst machines with respect to frequency and downtime, thus allowing maintenance technicians to apply the appropriate maintenance strategy. Each method has its own merits. Research limitations/implications This work compares only two methods based on their original conceptualisation. This is due to their similarities in using same input data and their main features. However, there is a scope to compare to other methods or variations of these methods. Practical implications This paper highlights how the DMG and JKD can be incorporated in industrial applications to allocate appropriate maintenance strategy and track machine performance over time. Originality/value Neither DMG nor JKD have been compared in the literature. Currently, the JKD has been used to rank machines, and the DMG has been used to determine maintenance strategies.

Enlightening grey portions of energy security towards sustainability

2017 ◽  
Vol 11 (1) ◽  
pp. 118-142 ◽  
Author(s):  
Vivek Soni ◽  
Surya Prakash Singh ◽  
Devinder Kumar Banwet
Keyword(s):  
Decision Making ◽  
Energy Security ◽  
Energy Supply ◽  
Energy Sector ◽  
Grey System Theory ◽  
Preference Ranking ◽  
Grey System ◽  
Content Type ◽  
Energy Projects ◽  
Priority Order

Purpose The purpose of this paper is to determine priority order of Indian energy sector projects on investments and strategic dimension angles. Grey System Theory (GST) and COmplex PRroportional ASsessment (COPRAS-G) method, a flexible multi-criteria decision-making (MCDM) analyses, is used for this purpose to prioritize Indian energy sector projects, namely, coal, gas, hydro, solar and nuclear. Design/methodology/approach The GST-based MCDM approach of COPRAS is used. Five projects of energy sector are compared based on various grey criteria. These criteria were selected on the perspectives of life-cycle costing and management-thinking approach for prioritizing these projects. The GST-based COPRAS-G is described, and results are discussed to draw a strategic road map for measuring the sustainability in the energy sector. Findings On applying COPRAS-G on five energy projects, solar projects get high-priority order, and realistic scenario of results shows that renewable energy projects are preferred over the conventional projects such as coal and gas. Research limitations/implications Here, COPRAS-G method is used as MCDM techniques. However, few other MCDM techniques such as fuzzy Preference Ranking Organization METHod for Enrichment Evolution, elimination and choice expressing reality and efficiency analysis technique with output satisficing can be also explored to outrank various Indian energy sector projects. Practical implications Indian energy sector involves high degree of complexity, and, therefore, it needs more flexibility to overcome the present barriers of effective decision-making. Grey decision theory-based method like COPRAS-G is able to address energy security dimensions on different scenario of energy supply, i.e. pessimistic, optimistic and realistic, precisely. Social implications The results can provide guidance to the government or public sector regarding various possible investment options for energy supply and can help in drawing a rough trajectory of strategy toward energy security of the country. Originality/value This paper can supplement and act as the support for decision-making in conflicting situations specifically to have outlook of the sub-sector project on different flexible scenarios. Moreover, such work can synergize conflicting ideas of decision makers and various stakeholders of the Indian energy sector.

Evaluation of risks in foodgrains supply chain using failure mode effect analysis and fuzzy VIKOR

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rishabh Rathore ◽  
J. J. Thakkar ◽  
J. K. Jha
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Supply Chain ◽  
Failure Mode ◽  
Risk Mitigation ◽  
Supply Chain System ◽  
Effect Analysis ◽  
Content Type ◽  
Fuzzy Vikor ◽  
Multiple Attribute

PurposeThis paper investigates the risks involved in the Indian foodgrain supply chain (FSC) and proposes risk mitigation taxonomy to enable decision making.Design/methodology/approachThis paper used failure mode and effect analysis (FMEA) for risk estimation. In the traditional FMEA, risk priority number (RPN) is evaluated by multiplying the probability of occurrence, severity and detection. Because of some drawbacks of the traditional FMEA, instead of calculating RPN, this paper prioritizes the FSC risk factors using fuzzy VIKOR. VIKOR is a multiple attribute decision-making technique which aims to rank FSC risk factors with respect to criteria.FindingsThe findings indicate that “technological risk” has a higher impact on the FSC, followed by natural disaster, communication failure, non-availability of procurement centers, malfunctioning in PDS and inadequate storage facility. Sensitivity analysis is performed to check the robustness of the results.Practical implicationsThe outcomes of the study can help in deriving detailed risk mitigation strategy and risk mitigation taxonomy for the improved resilience of FSC.Originality/valueSpecifically, this research investigates the risks for foodgrains supply chain system for a developing country such as India, an area which has received limited attention in the present literature.

Multi-criteria decision making towards selection of industrial robot

2015 ◽  
Vol 22 (3) ◽  
pp. 465-487 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
Saroj Kumar Patel ◽  
Siba Sankar Mahapatra
Keyword(s):  
Decision Making ◽  
Selection Problem ◽  
Preference Ranking ◽  
Multi Criteria Decision Making ◽  
Content Type ◽  
Promethee Ii ◽  
Advantages And Disadvantages ◽  
Wide Range ◽  
Robot Selection ◽  
Selection Of

Purpose – Robot selection is one of the critical decision-making tasks frequently performed by various industries in order to choose the best suited robot for specific industrial purposes. In recent marketplace, the number of robot manufacturers has increased remarkably offering a wide range of models and specifications; thus, robot selection has become indeed confusing as well as complicated task. Selection of an appropriate robot is a sensitive process; it may result massive letdown, if not chosen properly. Therefore, for unravel the selection problem; the purpose of this paper is to explore the preference ranking organization method for enrichment evaluation (PROMETHEE) II method. Design/methodology/approach – Apart from a large variety of robotic systems, existence of various multi-criteria decision making (MCDM) tools and techniques may create confusion to the decision makers’ in regards of application feasibility as well as superiority in performance to work under different decision-making situations. In this context, the PROMETHEE II method has been found as an efficient decision-making tool which provides complete ranking order of all available alternatives prudently, thus avoiding errors in decision making. Findings – In this context, the present paper highlights application potential of aforesaid PROMETHEE II method in relation to robot selection problem subjected to a set of quantitative (objective) evaluation data collected from the available literature resources. Advantages and disadvantages of PROMETHEE II method have also been reported in comparison to other existing MCDM approaches. Originality/value – The study bears significant managerial implications. Proper evaluation and selection of appropriate candidate robot would be helpful for the industries in order to improve product quality as well as to increase productivity. Proper utilization of resources could be ensured. Functioning would be accurate with reduced timespan. As a consequence, company can increase its profit margin in long run.

A novel FMEA model based on fuzzy multiple-criteria decision-making methods for risk assessment

2020 ◽  
Vol 33 (5) ◽  
pp. 881-904 ◽  
Author(s):  
Reza Fattahi ◽  
Reza Tavakkoli-Moghaddam ◽  
Mohammad Khalilzadeh ◽  
Nasser Shahsavari-Pour ◽  
Roya Soltani
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Decision Making ◽  
Failure Mode ◽  
Failure Modes ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Content Type ◽  
Proposed Model ◽  
Priority Weights

PurposeRisk assessment is a very important step toward managing risks in various organizations and industries. One of the most extensively applied risk assessment techniques is failure mode and effects analysis (FMEA). In this paper, a novel fuzzy multiple-criteria decision-making (MCDM)-based FMEA model is proposed for assessing the risks of different failure modes more accurately.Design/methodology/approachIn this model, the weight of each failure mode is considered instead of risk priority number (RPN). Additionally, three criteria of time, cost and profit are added to the three previous risk factors of occurrence (O), severity (S) and detection (D). Furthermore, the weights of the mentioned criteria and the priority weights of the decision-makers calculated by modified fuzzy AHP and fuzzy weighted MULTIMOORA methods, respectively, are considered in the proposed model. A new ranking method of fuzzy numbers is also utilized in both proposed fuzzy MCDM methods.FindingsTo show the capability and usefulness of the suggested fuzzy MCDM-based FMEA model, Kerman Steel Industries Factory is considered as a case study. Moreover, a sensitivity analysis is conducted for validating the achieved results. Findings indicate that the proposed model is a beneficial and applicable tool for risk assessment.Originality/valueTo the best of authors’ knowledge, no research has considered the weights of failure modes, the weights of risk factors and the priority weights of decision-makers simultaneously in the FMEA method.

scholarly journals Developing a Decision Making Grid for determining proactive maintenance tactics

2018 ◽  
Vol 29 (8) ◽  
pp. 1296-1315 ◽  
Author(s):  
Arash Shahin ◽  
Nahid Aminsabouri ◽  
Kamran Kianfar
Keyword(s):  
Decision Making ◽  
Maintenance Policy ◽  
Content Type ◽  
Mean Time Between Failures ◽  
Time Between Failures ◽  
Reliability Centered Maintenance ◽  
Innovative Solution ◽  
Maintenance Policies ◽  
Mean Time ◽  
Proactive Maintenance

Purpose The purpose of this paper is to further develop the Decision Making Grid (DMG) proposed by Ashraf Labib (e.g. Labib, 1998, 2004; Fernandez et al., 2003; Aslam-Zainudeen and Labib, 2011; Stephen and Labib, 2018; Seecharan et al., 2018) by proposing an innovative solution for determining proactive maintenance tactics based on mean time between failures (MTBF) and mean time to repair (MTTR) indicators. Design/methodology/approach First, the influence of MTTR and MTBF indicators on proactive maintenance tactics was computed. The tactics included risk-based maintenance (RBM), reliability-centered maintenance (RCM), total productive maintenance (TPM), design out maintenance (DOM), accessibility-centered maintenance (ACM) and business-centered maintenance (BCM). Then, the tactics were allocated to the cells of a DMG with MTTR and MTBF axes. The proposed approach was examined on 32 pieces of equipment of the Esfahan Steel Company and appropriate maintenance tactics were consequently determined. Findings The findings indicate that the DOM, BCM, RBM and ACM tactics with weights of 0.86, 0.94, 0.68 and 1.00 are located at the corners of the DMG, respectively. The two remaining tactics of TPM and RCM are located at the middle corners. Also, the results indicate that the share of tactics per spotted equipment in the grid as 62, 22 and 16 percent for RCM, DOM and BCM, respectively. Research limitations/implications While reactive and preventive maintenance strategies include corrective, prospective, predetermined, proactive and predictive policies, the focus of this study was merely on the tactics of proactive maintenance policy. The advantage of the developed DMG over Labib’s DMG lies in its application for equipment with the unique condition of the bathtub curve. Originality/value While the basic DMG has been mostly used regardless of the type of maintenance policies, this study provides a DMG for a specific application regarding the proactive policy. In addition, the heuristic approach proposed for the development of DMG distinguishes this study from other studies.

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