An Extension of the Failure Mode and Effect Analysis with Hesitant Fuzzy Sets to Assess the Occupational Hazards in the Construction Industry

The construction industry is considered as one of the most dangerous industries in terms of occupational safety and has a high rate of occupational incidents and risks compared to other industries. Given the importance of identifying and assessing the occupational hazards in this industry, researchers have conducted numerous studies using statistical methods, multi-criteria decision-making methods, expert-based judgments, and so on. Although, these researchers have used linguistic variables, fuzzy sets and interval-valued intuitionistic fuzzy sets to overcome challenges such as uncertainty and ambiguity in the risk assessment conducted by experts; the previous models lack in efficiency if the experts are hesitant in their assessment. This leads to the inability to assign a specific membership degree to any risk. Therefore, in this research, it is tried to provide an improved approach to the Failure Mode and Effects Analysis (FMEA) method using an Multi-Criteria Decision-Making (MCDM) method based on the hesitant fuzzy set, which can effectively cope with the hesitance of the experts in the evaluation. Also, Stepwise Weight Assessment Ratio Analysis (SWARA) method is applied for risk factor weighing in the proposed approach. This model is applied to a construction industry case study to solve a realistic occupational risk assessment. Moreover, a comparison is made between the results of this model and those obtained by the conventional FMEA and some other aggregation operators. The results indicate that the newly developed approach is useful and flexible to address complex FMEA problems and can generate logical and reliable priority rankings for failure modes.

[1]  Shib Sankar Sana,et al.  Evaluation and selecting the contractor in bidding with incomplete information using MCGDM method , 2019, Soft Comput..

[2]  Zeshui Xu,et al.  Hesitant fuzzy geometric Bonferroni means , 2012, Inf. Sci..

[3]  Nune Ravi Sankar,et al.  Modified approach for prioritization of failures in a system failure mode and effects analysis , 2001 .

[4]  Edmundas Kazimieras Zavadskas,et al.  Developing a new hybrid MCDM method for selection of the optimal alternative of mechanical longitudinal ventilation of tunnel pollutants during automobile accidents , 2013 .

[5]  Hu-Chen Liu,et al.  Failure mode and effects analysis using D numbers and grey relational projection method , 2014, Expert Syst. Appl..

[6]  Zenonas Turskis,et al.  Integrated Fuzzy Multiple Criteria Decision Making Model for Architect Selection , 2012 .

[7]  G. Emre Gürcanli,et al.  An occupational safety risk analysis method at construction sites using fuzzy sets , 2009 .

[8]  Seyed Ali Jozi,et al.  Environmental Risk Assessment of Dams in Construction Phase Using a Multi-Criteria Decision-Making (MCDM) Method , 2015 .

[9]  Hong-yu Zhang,et al.  The fuzzy cross-entropy for intuitionistic hesitant fuzzy sets and their application in multi-criteria decision-making , 2015, Int. J. Syst. Sci..

[10]  Animesh Biswas,et al.  Assessment of Occupational Risks in Construction Sites Using Interval Type-2 Fuzzy Analytic Hierarchy Process , 2018 .

[11]  Hao-Tien Liu,et al.  A fuzzy risk assessment approach for occupational hazards in the construction industry , 2012 .

[12]  Sarfaraz Hashemkhani Zolfani,et al.  New Application of SWARA Method in Prioritizing Sustainability Assessment Indicators of Energy System , 2014 .

[13]  Hu-Chen Liu,et al.  Failure Mode and Effect Analysis Under Uncertainty: An Integrated Multiple Criteria Decision Making Approach , 2016, IEEE Transactions on Reliability.

[14]  Hu-Chen Liu,et al.  Hesitant fuzzy integrated MCDM approach for quality function deployment: a case study in electric vehicle , 2017, Int. J. Prod. Res..

[15]  G. Wei,et al.  Extension of VIKOR method for decision making problem based on hesitant fuzzy set , 2013 .

[16]  Dejian Yu,et al.  Intuitionistic fuzzy geometric Heronian mean aggregation operators , 2013, Appl. Soft Comput..

[17]  Edmundas Kazimieras Zavadskas,et al.  Decision making in machine tool selection: An integrated approach with SWARA and COPRAS-G methods , 2013 .

[18]  Hu-Chen Liu,et al.  Failure mode and effect analysis with extended grey relational analysis method in cloud setting , 2019 .

[19]  Wenkai Zhang,et al.  Multiple criteria decision analysis based on Shapley fuzzy measures and interval-valued hesitant fuzzy linguistic numbers , 2017, Comput. Ind. Eng..

[20]  Marcello Braglia,et al.  MAFMA: multi‐attribute failure mode analysis , 2000 .

[21]  Zeshui Xu,et al.  Geometric Bonferroni means with their application in multi-criteria decision making , 2013, Knowl. Based Syst..

[22]  Yejun Xu,et al.  A consensus model for hesitant fuzzy preference relations and its application in water allocation management , 2017, Appl. Soft Comput..

[23]  Hu-Chen Liu,et al.  Evaluating the risk of failure modes with a hybrid MCDM model under interval-valued intuitionistic fuzzy environments , 2016, Comput. Ind. Eng..

[24]  Mohammed Khurshid Khan,et al.  A study into the use of the process failure mode and effects analysis (pfmea) in the automotive industry in the uk , 2003 .

[25]  Yang Gao,et al.  Combining FMEA with DEMATEL models to solve production process problems , 2017, PloS one.

[26]  Sutapa Pramanik,et al.  Interval type-2 fuzzy logic and its application to occupational safety risk performance in industries , 2019, Soft Comput..

[27]  Ahmet Can Kutlu,et al.  Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP , 2012, Expert Syst. Appl..

[28]  Yong Deng,et al.  Failure mode and effects analysis based on D numbers and TOPSIS , 2016, Qual. Reliab. Eng. Int..

[29]  Marcello Braglia,et al.  MULTI ATTRIBUTE FAILURE MODE ANALYSIS , 2000 .

[30]  Arash Alizadeh,et al.  HSE risk prioritization using robust DEA-FMEA approach with undesirable outputs: A study of automotive parts industry in Iran , 2018 .

[31]  Dejian Yu,et al.  Interval-valued intuitionistic fuzzy Heronian mean operators and their application in multi-criteria decision making , 2012 .

[32]  Morteza Yazdani,et al.  An extended stepwise weight assessment ratio analysis (SWARA) method for improving criteria prioritization process , 2018, Soft Comput..

[33]  Zeshui Xu,et al.  Hesitant fuzzy ELECTRE II approach: A new way to handle multi-criteria decision making problems , 2015, Inf. Sci..

[34]  L. S. Ganesh,et al.  Modelling and assessment of critical risks in BOT road projects , 2006 .

[35]  Hong-yu Zhang,et al.  A likelihood-based TODIM approach based on multi-hesitant fuzzy linguistic information for evaluation in logistics outsourcing , 2016, Comput. Ind. Eng..

[36]  Zeshui Xu,et al.  Hesitant fuzzy Bonferroni means for multi-criteria decision making , 2013, J. Oper. Res. Soc..

[37]  Edmundas Kazimieras Zavadskas,et al.  Risk evaluation of tunneling projects , 2012 .

[38]  Behnam Vahdani,et al.  A new FMEA method by integrating fuzzy belief structure and TOPSIS to improve risk evaluation process , 2014, The International Journal of Advanced Manufacturing Technology.

[39]  Edmundas Kazimieras Zavadskas,et al.  Application of Fuzzy DEMATEL Method for Analyzing Occupational Risks on Construction Sites , 2017 .

[40]  Arash Shahi,et al.  Safety Performance in the Construction Industry: Quasi-Longitudinal Study , 2017 .

[41]  Abel Pinto,et al.  Risk Assessment in Construction Industry ? Overview and Reflection , 2011 .

[42]  J. B. Bowles,et al.  Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis , 1995 .

[43]  Vicenç Torra,et al.  On hesitant fuzzy sets and decision , 2009, 2009 IEEE International Conference on Fuzzy Systems.

[44]  Marcello Braglia,et al.  Fuzzy criticality assessment model for failure modes and effects analysis , 2003 .

[45]  Radko Mesiar,et al.  Hesitant L ‐Fuzzy Sets , 2017, Int. J. Intell. Syst..

[46]  Zhaojun Li,et al.  New approach for failure mode and effect analysis using linguistic distribution assessments and TODIM method , 2017, Reliab. Eng. Syst. Saf..

[47]  Yong Hu,et al.  A Novel Weighted Average Index Method of Interval Valued Intuitionistic Fuzzy Sets and Its Application to Outsourced Software Project Risk Assessment , 2016 .

[48]  Samuel Yousefi,et al.  An extended FMEA approach based on the Z-MOORA and fuzzy BWM for prioritization of failures , 2019, Appl. Soft Comput..

[49]  Yongtae Park,et al.  A systematic approach for diagnosing service failure: Service-specific FMEA and grey relational analysis approach , 2011, Math. Comput. Model..

[50]  Brahim Ouhbi,et al.  A knowledge-based outranking approach for multi-criteria decision-making with hesitant fuzzy linguistic term sets , 2017, Appl. Soft Comput..

[51]  T. Yiu,et al.  A new approach to predict safety outcomes in the construction industry , 2018, Safety Science.

[52]  Jian-Bo Yang,et al.  Risk evaluation in failure mode and effects analysis using fuzzy weighted geometric mean , 2009, Expert Syst. Appl..

[53]  Dejian Yu,et al.  Hesitant fuzzy multi-criteria decision making methods based on Heronian mean , 2015 .

[54]  H. Schneider Failure mode and effect analysis : FMEA from theory to execution , 1996 .

[55]  Edmundas Kazimieras Zavadskas,et al.  Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (Swara) , 2010 .

[56]  Dong‐Shang Chang,et al.  Applying DEA to enhance assessment capability of FMEA , 2009 .

[57]  Wen-Chang Ko,et al.  Exploiting 2-tuple linguistic representational model for constructing HOQ-based failure modes and effects analysis , 2013, Comput. Ind. Eng..

[58]  Hu-Chen Liu,et al.  Failure mode and effect analysis using multi-criteria decision making methods: A systematic literature review , 2019, Comput. Ind. Eng..

[59]  S. M. Seyed Hosseini,et al.  Reprioritization of failures in a system failure mode and effects analysis by decision making trial and evaluation laboratory technique , 2006, Reliab. Eng. Syst. Saf..

[60]  Mohammad A. Khalilzadeh,et al.  Risk evaluation using a novel hybrid method based on FMEA, extended MULTIMOORA, and AHP methods under fuzzy environment , 2018, Safety Science.

[61]  Edmundas Kazimieras Zavadskas,et al.  A Hybrid MCDM Technique for Risk Management in Construction Projects , 2018, Symmetry.

[62]  Norhazilan Md Noor,et al.  Hybrid SWARA-COPRAS method for risk assessment in deep foundation excavation project: an Iranian case study , 2017 .

[63]  J. Szer,et al.  The analysis of the stages of scaffolding “life” with regard to the decrease in the hazard at building works , 2015 .

[64]  Jalil Heidary Dahooie,et al.  Competency‐based IT personnel selection using a hybrid SWARA and ARAS‐G methodology , 2018 .

[65]  Ajith Abraham,et al.  Fuzzy logic-based FMEA robust design: a quantitative approach for robustness against groupthink in group/team decision-making , 2019, Int. J. Prod. Res..

[66]  Dejian Yu,et al.  Hesitant fuzzy prioritized operators and their application in multi-criteria group decision making , 2012 .

[67]  Subhashis Sahu,et al.  Fuzzy inference model for assessing occupational risks in construction sites , 2016 .