Sustainable Lean Six Sigma project selection in manufacturing environments using best-worst method

被引:10
作者
Swarnakar, Vikas [1 ]
Singh, A. R. [2 ]
Antony, Jiju [1 ]
Tiwari, Anil Kr [2 ]
Garza-Reyes, Jose Arturo [3 ]
机构
[1] Khalifa Univ, Dept Ind & Syst Engn, Abu Dhabi, U Arab Emirates
[2] Natl Inst Technol, Dept Mech Engn, Raipur, Madhya Pradesh, India
[3] Univ Derby, Ctr Supply Chain Improvement, Derby, England
关键词
Sustainable LSS; project selection; best worst method; sensitivity analysis; automotive component manufacturing organization; SUPPLIER SELECTION; GREEN; PRIORITIZATION; PERFORMANCE; BARRIERS;
D O I
10.1080/14783363.2022.2139675
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Manufacturing organizations have struggled with selecting right projects for sustainable LSS (SLSS) programs for operational excellence. This study is to propose a method for effective assessment of optimal SLSS projects. The importance weight of project selection criteria and prioritization of available projects are calculated using the novel best-worst-method (BWM) approach. The proposed methodology was authenticated through a real case example. The outcome reveals that out of five SLSS projects, P-1 is the optimal project. Project P-1 is the most significant production line for deploying the SLSS in case organization. The optimality in project ranking is tested through sensitivity analysis, the outcome noticed minimum sensitivity that claimed robust findings. This study is to be unique as there was very little evidence of prioritizing SLSS projects by utilizing a large set of criteria and applying the BWM approach. Further, BWM is the most suitable and reliable approach for prioritizing the alternatives when a large number of criteria are involved and it provides consistent outcomes with fewer inputs. The applied methodology will help top management to select the right project and opportunities in complex situations. Decision-makers and LSS consultants can also adopt the same approach for effective assessment of optimal SLSS projects for sustainable development.
引用
收藏
页码:990 / 1014
页数:25
相关论文
共 49 条
[31]   An evaluative economic development typology for sustainable rural economic development [J].
Rangarajan, Kiran ;
Long, Suzanna ;
Ziemer, Norbert ;
Lewis, Neal .
COMMUNITY DEVELOPMENT, 2012, 43 (03) :320-332
[32]   Urban sewage sludge, sustainability, and transition for Eco-City: Multi-criteria sustainability assessment of technologies based on best-worst method [J].
Ren, Jingzheng ;
Liang, Hanwei ;
Chan, Felix T. S. .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2017, 116 :29-39
[33]   Best-worst multi-criteria decision-making method [J].
Rezaei, Jafar .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2015, 53 :49-57
[34]   Lean Six Sigma in the public sector: yesterday, today and tomorrow [J].
Rodgers, Bryan ;
Antony, Jiju ;
Edgeman, Rick ;
Cudney, Elizabeth A. .
TOTAL QUALITY MANAGEMENT & BUSINESS EXCELLENCE, 2021, 32 (5-6) :528-540
[35]   Analyzing Challenges to Transportation for Successful Sustainable Food Supply Chain Management Implementation in Indian Dairy Industry [J].
Sharma, Yogesh Kumar ;
Mangla, Sachin Kumar ;
Patil, Pravin P. .
INFORMATION AND COMMUNICATION TECHNOLOGY FOR COMPETITIVE STRATEGIES, 2019, 40 :409-418
[36]   Prioritization of Lean Six Sigma project selection criteria using Best Worst Method [J].
Shukla, Vitthal ;
Swarnakar, Vikas ;
Singh, A. R. .
MATERIALS TODAY-PROCEEDINGS, 2021, 47 :5749-5754
[37]   Lean Six Sigma project selection using Best Worst Method [J].
Singh, Kritika ;
Swarnakar, Vikas ;
Singh, A. R. .
MATERIALS TODAY-PROCEEDINGS, 2021, 47 :5766-5770
[38]   Triple diode parameter estimation of solar PV cell using hybrid algorithm [J].
Singla, M. K. ;
Nijhawan, P. .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, 2022, 19 (05) :4265-4288
[39]  
Swarnakar V., 2014, P SOM INT C ORG DEP, P805
[40]   A multiple integrated approach for modelling critical success factors in sustainable LSS implementation [J].
Swarnakar, Vikas ;
Singh, A. R. ;
Antony, Jiju ;
Tiwari, Anil Kr ;
Cudney, Elizabeth ;
Furterer, Sandra .
COMPUTERS & INDUSTRIAL ENGINEERING, 2020, 150