A hybrid model for ranking critical successful factors of Lean Six Sigma in the oil and gas industry

Abstract

PurposeThe aim of this paper is to find and prioritise multiple critical success factors (CSFs) for the implementation of LSS in the oil and gas industry.Design/methodology/approachBased on a preselected list of possible CFSs, experts are involved in screening them with the Delphi method. As a result, 22 customised CSFs are selected. To prioritise these CSFs, the step-wise weight assessment ratio analysis (SWARA) method is applied to find weights corresponding to the decision-making preferences. Since the regular permutation-based weight assessment can be classified as NP-hard, the problem is solved by a metaheuristic method. For this purpose, a genetic algorithm (GA) is used.FindingsThe resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them. The less important factors can be neglected and thus do not require limited resources.Research limitations/implicationsOnly a specific set of methods have been considered.Practical implicationsThe resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them.Social implicationsThe methodology supports respective evaluations in general.Originality/valueThe paper contributes to the very limited research on the implementation of LSS in the oil and gas industry, and, in addition, it suggests the usage of SWARA, a permutation method and a GA, which have not yet been researched, for the prioritisation of CSFs of LSS.

Organizational change towards Lean Six Sigma implementation in the manufacturing supply chain: an integrated approach

“…As such, this study is in line with past published studies which laud the importance of promulgating government policies to encourage organizational change towards LSS implementation in the Nigerian plastics manufacturing clime (Gruenhagen et al. , 2022; Hariyani and Mishra, 2022; Yazdi et al. , 2021).…”

“…Specifically, within the institution-based context, as illustrated in Figures 3 and 4, the most significant factor for the successful implementation of LSS in supply chains of the Nigerian plastics manufacturing firms is government policies and regulatory framework, followed by stakeholders' requirements for high quality. As such, this study is in line with past published studies which laud the importance of promulgating government policies to encourage organizational change towards LSS implementation in the Nigerian plastics manufacturing clime (Gruenhagen et al, 2022;Hariyani and Mishra, 2022;Yazdi et al, 2021). Also, the current study corroborates prior published studies (Gilsbach et al, 2022).…”

“…Furthermore, other applications of MCDM in the area of CSFs in LSS implementation have also been studied by other research scholars (Masekwameng, 2020; Swarnakar et al. , 2020; Yazdi et al. , 2021).…”

“…Furthermore, other applications of MCDM in the area of CSFs in LSS implementation have also been studied by other research scholars (Masekwameng, 2020;Swarnakar et al, 2020;Yazdi et al, 2021). Despite all the aforementioned studies, the research on CSF assessment in LSS implementation is still in the nascent stage and as such far from substantial when compared with studies on continuous improvement (Raja et al, 2018).…”

Selection methods of lean management tools: a review

“…, 2011; Yazdi, 2015). There are several types of MADM, such as technique for order of preference by similarity to ideal solution (TOPSIS), analytic hierarchy process (AHP), MACBETH method, VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR), analytic network process (ANP), multi-criteria acceptability analysis (SMAA), best worst method (BWM), grey relational analysis, multi-attribute global inference of quality (MAGIQ), entropy method, simple additive weighting (SAW) and simple multi-attribute rating techniques (Tavana et al , 2011; Yazdi, 2015; Yazdi et al , 2021; Yazdi and Esfeden, 2017).…”