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Article
Publication date: 6 June 2020

Reza Fattahi, Reza Tavakkoli-Moghaddam, Mohammad Khalilzadeh, Nasser Shahsavari-Pour and Roya Soltani

Risk assessment is a very important step toward managing risks in various organizations and industries. One of the most extensively applied risk assessment techniques is…

Abstract

Purpose

Risk 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/approach

In 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.

Findings

To 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/value

To 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.

Details

Journal of Enterprise Information Management, vol. 33 no. 5
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 13 April 2021

Maryam Eghbali-Zarch, Reza Tavakkoli-Moghaddam, Kazem Dehghan-Sanej and Amin Kaboli

The construction industry is a key driver of economic growth. However, the adverse impacts of construction and demolition waste (CDW) resulted from the active construction…

Abstract

Purpose

The construction industry is a key driver of economic growth. However, the adverse impacts of construction and demolition waste (CDW) resulted from the active construction projects on the economy, environment, public health and social life necessitates an appropriate control and management of this waste stream. Developing and promoting the construction and demolition waste management (CDWM) hierarchy program at the strategic level is essential.

Design/methodology/approach

This study aims to propose a hybrid decision model that hybridizes the Integrated Determination of Objective Criteria Weights (IDOCRIW) and weighted aggregated sum product assessment (WASPAS) under a fuzzy environment.

Findings

The proposed method ranks the potential strategic alternatives by the sustainable development criteria to improve the performance of CDWM. As indicated in the results, the fuzzy approach in the decision-making process enables the transformation of linguistic variables into fuzzy numbers that show uncertainty and ambiguity in real-world systems. Moreover, the close correlation between the final ranking of the proposed methodology and the average priority order of the strategic alternatives obtained by five different multi-criteria decision-making (MCDM) methods implies the validity of the model performance.

Practical implications

This proposed model is an appropriate tool to effectively decide on the development of CDWM from a strategic point of view. It aims to establish an MCDM framework for the evaluation of effective strategies for CDWM according to the indices of sustainable development. Implementing proper operational plans and conducting research in CDWM has the highest priority, and enacting new and more stringent laws, rules and regulations against the production of CDW has secondary priority. This study contributes to the field by optimizing the CDWM by applying the top-priority strategies resulted from the proposed fuzzy hybrid MCDM methodology by the decision-makers or policy-makers to reach the best managerial strategic plan.

Originality/value

In the proposed methodology, the IDOCRIW technique is utilized and updated with the triangular fuzzy numbers for the first time in the literature to derive the weights of sustainable development criteria. The fuzzy WASPAS method is utilized for evaluation and providing a final ranking of the strategic alternatives.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

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Article
Publication date: 17 June 2021

Abolghasem Yousefi-Babadi, Ali Bozorgi-Amiri and Reza Tavakkoli-Moghaddam

To avoid sub-optimization in wheat storage centers, one of the most strategic facilities, it is necessary to review and relocate them to be optimized regularly. The…

Abstract

Purpose

To avoid sub-optimization in wheat storage centers, one of the most strategic facilities, it is necessary to review and relocate them to be optimized regularly. The present study aims to propose an integrated method using geographic information systems (GISs) and an appropriate weighting algorithm for the relocation of wheat storage facilities.

Design/methodology/approach

To achieve the goal mentioned above, sustainability pillars in facility location and relocation are initially developed; afterward, a set of suitable criteria are obtained from various scientific resources. Then, the weight of each sustainable development pillar and its corresponding sub-criteria were identified through utilizing the best–worst method (BWM). By applying the obtained weights in the ArcGIS software package, various geographical layers were designed, and land-use planning, logistics planning and sustainable logistics planning are carried out in the regions. The regions are ranked based on the scores obtained in the processes, and the best regions are selected for sustainable relocation problem.

Findings

A case study including 430 regions (counties) in Iran is conducted to evaluate the efficiency of the suggested approach. The study results indicate that Iran possesses a superior state for establishing wheat storage centers in terms of infrastructural and social aspects. Also, it is established that 16% of counties are recognized as sustainable locations for relocating the wheat storage facilities.

Research limitations/implications

There is no most suitable analysis of the wheat storage facilities, as well as their strategic position in the supply chain, and there is a lack of considering sustainability in wheat storage facility location, despite the particular importance of it to the supply chain.

Practical implications

This framework is applied in an Iranian wheat-bread supply chain to find the best sustainable facilities. It is noted that this algorithm can be applied in other strategic facilities by minor and some major changes.

Originality/value

Decision-makers can apply the proposed methodology to find the best relocation sites for wheat storage facilities as the main part of wheat-bread supply chain in order to prevent sub-optimization and improve the efficiency of their supply chain.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 1 February 2021

Mahdi Bastan, Masoumeh Zarei, Reza Tavakkoli-Moghaddam and Hamed Shakouri G.

The Iranian construction industry has been grappling with numerous problems in recent years, including rework, high costs and design errors. Engineers in this field have…

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Abstract

Purpose

The Iranian construction industry has been grappling with numerous problems in recent years, including rework, high costs and design errors. Engineers in this field have always highlighted the use of modern technological methods of construction to improve quality and productivity and reduce time and cost. One of these technologies is the so-called building information modeling (BIM), which has been very difficult to adopt and implement in Iran. The purpose of this study is to propose a systemic and holistic model to analyze the dynamics of adoption and implementation of BIM in this country. The purpose of this paper is to understand the dynamics of BIM acceptance to identify the most effective policy to maximize it in the Iranian manufacturing industry.

Design/methodology/approach

A two-stage methodology has been developed to achieve the purpose of the research. In the first stage, a technology acceptance model for BIM acceptance was developed using the grounded theory (GT) method. This conceptual model provides a holistic basis for building a simulation model. Thus, in the second stage, we used the dynamics system methodology to extract a dynamic model from the conceptual one. This dynamic model can simulate different policies and may be used to evaluate their respective effectiveness.

Findings

In this study, using the GT method, we obtained 510 primary codes, 118 secondary codes, 50 concepts and 17 categories. After determining the relationships between categories through axial coding, we reached a conceptual model based on selective coding. Mention some of the variables of the conceptual model. Awareness, security, perceived usefulness and perceived ease of use are some of the most important variables of this model. In the next part, this conceptual model was run using system dynamics and, thus, turned into a causal model in which all the effective variables on BIM technology and their relationships with each other are specified. The stock and flow diagram of the problem and its related equations were presented. To improve the model and solve the problem, we examined the four policies as four future scenarios on the model: continuing the status quo, development of specialist workforce training, bolstering governmental support and increasing awareness via advertisement within. The simulation results showed that government support is the most effective policy for maximizing BIM acceptance in Iran.

Practical implications

In addition to enumerating all the factors affecting BIM technology, this paper proposes a systemic model that provides an accurate and comprehensive view of the acceptance of this technology. In this regard, by introducing feedback loops, as well as reinforcing and balancing factors versus factors causing stasis, the model offers a much deeper insight into mechanisms associated with BIM development and its barriers. Therefore, this study provides a very useful perspective and basis for policy-makers and all stakeholders to accept and implement BIM technology. The findings of this study can lead to more accurate policy-making, removal of acceptance barriers, promotion of incentives, and consequently more effective acceptance of BIM technology.

Originality/value

In this study, a new mixed research method was used. The innovation of our study lies in its simultaneous use of GT method to construct an accurate and holistic model and applying the system dynamics methodology to build a holistic and systemic model of the BIM acceptance problem. This research also provides a suitable standard and tool for studying BIM technology in developing countries.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 26 June 2020

Hesam Adarang, Ali Bozorgi-Amiri, Kaveh Khalili-Damghani and Reza Tavakkoli-Moghaddam

This paper addresses a location-routing problem (LRP) under uncertainty for providing emergency medical services (EMS) during disasters, which is formulated using a robust…

Abstract

Purpose

This paper addresses a location-routing problem (LRP) under uncertainty for providing emergency medical services (EMS) during disasters, which is formulated using a robust optimization (RO) approach. The objectives consist of minimizing relief time and the total cost including location costs and the cost of route coverage by the vehicles (ambulances and helicopters).

Design/methodology/approach

A shuffled frog leaping algorithm (SFLA) is developed to solve the problem and the performance is assessed using both the ε-constraint method and NSGA-II algorithm. For a more accurate validation of the proposed algorithm, the four indicators of dispersion measure (DM), mean ideal distance (MID), space measure (SM), and the number of Pareto solutions (NPS) are used.

Findings

The results obtained indicate the efficiency of the proposed algorithm within a proper computation time compared to the CPLEX solver as an exact method.

Research limitations/implications

In this study, the planning horizon is not considered in the model which can affect the value of parameters such as demand. Moreover, the uncertain nature of the other parameters such as traveling time is not incorporated into the model.

Practical implications

The outcomes of this research are helpful for decision-makers for the planning and management of casualty transportation under uncertain environment. The proposed algorithm can obtain acceptable solutions for real-world cases.

Originality/value

A novel robust mixed-integer linear programming (MILP) model is proposed to formulate the problem as a LRP. To solve the problem, two efficient metaheuristic algorithms were developed to determine the optimal values of objectives and decision variables.

Details

Journal of Humanitarian Logistics and Supply Chain Management, vol. 10 no. 3
Type: Research Article
ISSN: 2042-6747

Keywords

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Article
Publication date: 1 October 2018

Hadi Balouei Jamkhaneh, Javad Khazaei Pool, Seyed Mohammad Sadegh Khaksar, S. Mohammad Arabzad and Reza Verij Kazemi

The application of automated systems is rapidly increasing in different industries and organizations. In this regard, computerized maintenance management systems (CMMS…

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1035

Abstract

Purpose

The application of automated systems is rapidly increasing in different industries and organizations. In this regard, computerized maintenance management systems (CMMS) using information technology play an important role in the automating production systems. The purpose of this paper is to investigate the impacts of CMMSs and relevant supportive organizational factors on the effectiveness of total productive maintenance.

Design/methodology/approach

This study is classified as a quantitative survey-based research using structural equation modeling. The scope of the study includes manufacturing companies in Iran. A total of 125 questionnaires from 60 companies were collected from January to March 2014 to help validate the conceptual model and test the hypotheses.

Findings

The results support the concept CMMSs positively relates to relevant supportive organizational factors (resource allocation, decision-making structure, senior management support, employees’ involvement and effective instruction) on the effectiveness of total productive maintenance. The relevant supportive organizational factors can also be seen as the predictors of CMMSs.

Originality/value

This study integrates the CMMSs and relevant supportive organizational factors in a robust model to examine the effectiveness of total productive maintenance. This study also examines the impacts of CMMSs and relevant supportive organizational factors on total productive maintenance which seems to not be done previously.

Details

Benchmarking: An International Journal, vol. 25 no. 7
Type: Research Article
ISSN: 1463-5771

Keywords

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Article
Publication date: 3 January 2017

Reza Ghavijorbozeh and Ali Zeinal Hamadani

The purpose of this paper is to understand the consequence of the use of mixed Weibull distribution in the cell formation problem. In reliability theory, a mixed…

Abstract

Purpose

The purpose of this paper is to understand the consequence of the use of mixed Weibull distribution in the cell formation problem. In reliability theory, a mixed distribution is used for more than one hazard cause, and the Weibull distribution can be used for ascendant, monotonous and descendant failure rate. Here, the authors mixed these two theme and use it in a common problem in group technology.

Design/methodology/approach

In this paper, the authors made a non-polynomial-hard mathematical model based on past research and solved it with an exact algorithm. The algorithm is coded and solved in GAMS to illustrate the model, and the authors use simulation. A common numerical example is solved with the model, and the results are compared.

Findings

Reliability analysis model based on the mixed Weibull distribution approach will give options to a user to select the suitable failure rate and modes for a specific situation. If the user uses the exponential or Weibull distribution instead of the mixed Weibull distribution, the calculated cost and reliability are wrong; therefore, it leads to user making wrong decisions.

Originality/value

The model the authors use is the one used in past research, but in the past, researchers did not use the mixed distribution for explaining failure time. Therefore, the model can be considered as a new and more complete model.

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Article
Publication date: 28 December 2020

Mohammad Reza Moniri, Akbar Alem Tabriz, Ashkan Ayough and Mostafa Zandieh

The purpose of this paper is to propose a new framework for assessing the risks of turnaround projects in upstream oil process plants.

Abstract

Purpose

The purpose of this paper is to propose a new framework for assessing the risks of turnaround projects in upstream oil process plants.

Design/methodology/approach

This study represents a new hybrid framework for turnaround project risk assessment. First, according to experts’ opinions, the project risks were identified using interviews and brainstorming. The most important risks selected by experts and a hybrid multiple-attribute decision-making (MADM) method used to assess and prioritize them. The proposed MADM method uses fuzzy step-wise weight assessment ratio analysis (SWARA) and fuzzy evaluation based on distance from average solution (EDAS) methods based on trapezoidal fuzzy numbers.

Findings

In this research, 28 usual risks of turnaround projects are identified and 10 risks are then selected as the most important ones. The findings show, that among the risks of upstream oil industry turnaround projects from the perspective of experts, the risk of timely financing by the employer, with an appraisal score of 0.83, has the highest rank among the risks and the risk of machine and equipment failure during operation, with an appraisal score of 0.04, has the lowest rank.

Research limitations/implications

The risk analysis based on inputs collected from the experts in the Iranian upstream oil industry, and so the generalization of the results is limited to the context of developing countries, especially oil producer ones. However, the proposed risk analysis methodology and key insights developed can be useful for researchers and practitioners in any other process industry everywhere.

Originality/value

A novel framework for risk assessment is introduced for turnaround projects in the oil industry using MADM methods. There is no literature on using MADM methods for turnaround project risk analysis in the oil and gas industries. Furthermore, this paper presents a hybrid fuzzy method based on SWARA and EDAS.

Details

Journal of Engineering, Design and Technology , vol. 19 no. 4
Type: Research Article
ISSN: 1726-0531

Keywords

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Article
Publication date: 26 July 2021

Ehsan Mohebban-Azad, Amir-Reza Abtahi and Reza Yousefi-Zenouz

This study aims to design a reliable multi-level, multi-product and multi-period location-inventory-routing three-echelon supply chain network, which considers disruption…

Abstract

Purpose

This study aims to design a reliable multi-level, multi-product and multi-period location-inventory-routing three-echelon supply chain network, which considers disruption risks and uncertainty in the inventory system.

Design/methodology/approach

A robust optimization approach is used to deal with the effects of uncertainty, and a mixed-integer nonlinear programming multi-objective model is proposed. The first objective function seeks to minimize inventory costs, such as ordering costs, holding costs and carrying costs. It also helps to choose one of the two modes of bearing the expenses of shortage or using the excess capacity to produce at the expense of each. The second objective function seeks to minimize the risk of disruption in distribution centers and suppliers, thereby increasing supply chain reliability. As the proposed model is an non-deterministic polynomial-time-hard model, the Lagrangian relaxation algorithm is used to solve it.

Findings

The proposed model is applied to a real supply chain in the aftermarket automotive service industry. The results of the model and the current status of the company under study are compared, and suggestions are made to improve the supply chain performance. Using the proposed model, companies are expected to manage the risk of supply chain disruptions and pay the lowest possible costs in the event of a shortage. They can also use reverse logistics to minimize environmental damage and use recycled goods.

Originality/value

In this paper, the problem definition is based on a real case; it is about the deficiencies in the after-sale services in the automobile industry. It considers the disruption risk at the first level of the supply chain, selects the supplier considering the parameters of price and disruption risk and examines surplus capacity over distributors’ nominal capacity.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

Keywords

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Article
Publication date: 23 March 2012

Hamid Reza Golmakani and Ali Namazi

In many manufacturing systems, machines are subject to preventive maintenance. This paper aims to schedule the operations of jobs and preventive maintenance tasks in such…

Abstract

Purpose

In many manufacturing systems, machines are subject to preventive maintenance. This paper aims to schedule the operations of jobs and preventive maintenance tasks in such a way that the completion time of jobs and preventive maintenance tasks is minimized.

Design/methodology/approach

An heuristic approach based on artificial immune algorithm is proposed for solving the multiple‐route job shop‐scheduling problem subject to fixed periodic and age‐dependent preventive maintenance tasks. Under fixed periodic assumption, the time between two consecutive preventive maintenance tasks is assumed constant. Under age‐dependent assumption, a preventive maintenance task is triggered if the machine operates for a certain amount of time. The goal is to schedule the jobs and preventive maintenance task subject to makespan minimization.

Findings

In addition to presenting mathematical formulation for the multiple‐route job shop‐scheduling problem, this paper proposes a novel approach by which one can tackle the complexity that is raised in scheduling and sequencing the jobs and the preventive maintenance simultaneously and obtain the required schedule in reasonable time.

Practical implications

Integrating preventive maintenance tasks into the scheduling procedure is vital in many manufacturing systems. Using the proposed approach, one can obtain a schedule that defines the production route through which each part is processed, the time each operation must be started, and when preventive maintenance must be carried out on each machine. This, in turn, results in overall manufacturing cost reduction.

Originality/value

Using the approach proposed in this paper, good solutions, if not optimal, can be obtained for scheduling jobs and preventive maintenance task in one of the most complicated job shop configurations, namely, multiple‐route job shop. Thus, the approach can dominate all other simpler configurations.

Details

Journal of Quality in Maintenance Engineering, vol. 18 no. 1
Type: Research Article
ISSN: 1355-2511

Keywords

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