A toolset for complex decision making in analyze phase of Lean Six Sigma Project: A case validation

The analyze phase of Lean Six Sigma (LSS) project is an important phase where the project heads and organizational directors need to select the critical issues for further improvements. The present work is primarily focused on analyze phase of LSS project to prioritized the Critical to Quality (CTQs) in a particular case industry. The CTQs prioritization is being done based on the five evaluation criteria found from the literature. The weights of the criteria are determined through the Modified Digital Logic (MDL) method. The identified CTQs in assembly section of case industry have been ranked through the Grey Relation Analysis (GRA) under fuzzy environment. The results of the study have been validated using fuzzy VIKOR. It is found that the ‘cost’ criterion is the most significant among other criteria with MDL weight of 0.3. Through fuzzy-GRA, out of ten identified CTQs, non availability of rack system is found to be the most critical issue in assembly section of case industry. The perceptions of industrial manager and production head of case industry are strongly in favor of the obtained results and has implemented the suggested solutions.To sustain in the competitive environment and produce quality product at right time, organizations need to control their CTQs as per their criticality. For this, the decision making becomes quite complex to select the most critical factors due to the fascinating nature of various criteria and sub-criteria. The present study is the first attempt that has implemented the multi-criteria decision-making approach in analyze phase of LSS project

Prioritizing lean techniques by employing Multi-Criteria Decision-Making (MCDM): The case of MCoutinho

The business cycle in the automotive industry follows the general economic cycle closely and therefore, undergoes cyclical fluctuations over time. Companies in the sector are faced with challenges and need to deal with market demands efficiently and quickly to stay competitive. Lean approach is one of the strategies that can aid firms to improve their competitiveness by minimizing waste (Pullan et al., 2013). In order to benefit from a lean approach, the first step is to select a proper tool based on the available resources and requirements of the company. Due to the fact that numerous lean tools have been introduced over time, decision makers in company may encounter challenges in selecting the proper one with regard to their demands. To deal with such an issue, Multi-Criteria Decision-Making (MCDM) can greatly assist decision makers to compare available alternatives and consequently select the best possible solution among them. This study aims at improving the operational process in MCoutinho Group, a Portuguese well-known company in the automotive sector, by helping the management board in selecting lean tool due to the company preferences. In this study, the applicability (and results) of the application of some MCDM techniques (SAW, TOPSIS, and VIKOR) is examined to compare ten lean tools, determined based on the literature. The results reveal some gaps between company requirements and the demands which have been considered in previous surveys. The process applied can save the costs of trial and error of implementing different lean tools. And finally, adopting such a lean tool that has been selected totally based on the exclusive requirements of the company can improve efficiency in the company.O ciclo de negócios na indústria automotiva segue de perto o ciclo econômico geral e, portanto, sofre flutuações cíclicas ao longo do tempo. As empresas do setor enfrentam desafios e precisam lidar com as demandas do mercado de forma eficiente e rápida para se manterem competitivas. A abordagem enxuta é uma das estratégias que pode ajudar as empresas a melhorar sua competitividade, minimizando o desperdício (Pullan et al., 2013). Para se beneficiar de uma abordagem enxuta, o primeiro passo é selecionar uma ferramenta adequada com base nos recursos disponíveis e requisitos da empresa. Devido ao fato de que várias ferramentas enxutas foram introduzidas ao longo do tempo, os tomadores de decisão na empresa podem encontrar desafios ao selecionar a ferramenta adequada com relação às suas demandas. Para lidar com essa questão, a Tomada de Decisão Multi-Critérios (MCDM) pode ajudar muito os tomadores de decisão a comparar as alternativas disponíveis e, conseqüentemente, selecionar a melhor solução possível entre elas. Este estudo tem como objetivo melhorar o processo operacional do Grupo MCoutinho, empresa portuguesa de renome no setor automóvel, auxiliando a administração na seleção da ferramenta enxuta em função das preferências da empresa. Neste estudo, a aplicabilidade (e resultados) da aplicação de algumas técnicas MCDM (SAW, TOPSIS e VIKOR) é examinada para comparar dez ferramentas enxutas, determinadas com base na literatura. Os resultados revelam algumas lacunas entre os requisitos da empresa e as demandas consideradas em pesquisas anteriores. O processo aplicado pode economizar os custos de tentativa e erro de implementação de diferentes ferramentas enxutas. E, por fim, a adoção de uma ferramenta tão enxuta que foi selecionada totalmente com base nos requisitos exclusivos da empresa pode melhorar a eficiência da empresa

VIKOR Technique:A Systematic Review of the State of the Art Literature on Methodologies and Applications

The main objective of this paper is to present a systematic review of the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in several application areas such as sustainability and renewable energy. This study reviewed a total of 176 papers, published in 2004 to 2015, from 83 high-ranking journals; most of which were related to Operational Research, Management Sciences, decision making, sustainability and renewable energy and were extracted from the “Web of Science and Scopus” databases. Papers were classified into 15 main application areas. Furthermore, papers were categorized based on the nationalities of authors, dates of publications, techniques and methods, type of studies, the names of the journals and studies purposes. The results of this study indicated that more papers on VIKOR technique were published in 2013 than in any other year. In addition, 13 papers were published about sustainability and renewable energy fields. Furthermore, VIKOR and fuzzy VIKOR methods, had the first rank in use. Additionally, the Journal of Expert Systems with Applications was the most significant journal in this study, with 27 publications on the topic. Finally, Taiwan had the first rank from 22 nationalities which used VIKOR technique

Ranking the Suppliers using a Combined SWARA-FVIKOR Approach

People are evaluating suppliers due to their responsibility which requires the need of a structured process for supplier evaluation. In this paper we used a new model for weighting of criterias and ranking the alternatives. This model is the combination of SWARA (Stepwise weight assessment ratio analysis) and FVIKOR (VlseKriter ijumskaOptimizacija I KompromisnoResenje) methods which evaluate the main criterias based on evaluation of factors that have major impacts on quality of suppliers, and selects the best suppliers according to the criterias. SWARA method is used in determining the weights of the criteria by decision makers and then rankings of the suppliers were determined by Fuzzy VIKOR method. The proposed method in this study is used for ranking the three suppliers of ABZARSAZI in Iran by five indexes that have major impacts on it. For this purpose, in this paper, designed questionnaires are sent to 20 professional experts in different departments of ABZARSAZI COMPANY in Iran for evaluating the criterias using SWARA. The result showed that Delivery is the most important criterias. Such, the results of FVIKOR technique showed that supplier 1 is the best supplier. This proposed approach gives an evaluation method for all of the companies in order to help managers to identify the best suppliers

Decision-making through Fuzzy TOPSIS and COPRAS approaches for lean tools selection: A case study of automotive accessories manufacturing industry

Similarity in prioritization of lean tools (LTs) by different frameworks on the same problem is a point of contention. The goal of the present research is to address LTs selection problem through two commonly used multi-criteria decision making approaches, namely the technique for order preference by similarity to ideal solution (TOPSIS) and complex proportional assessment(COPRAS). A framework involving value stream mapping and plant layout through TOPSIS and COPRAS approaches to find the best possible LTs for an automotive accessories manufacturing plant is developed and assessed in this research. The obtained similarity of rankings between TOPSIS and COPRAS is 71.42% and the difference is 28.58%. Based on the assessment, systematic layout planning (SLP) is selected as the most suitable LT and its implementation is elaborated in detail. Significant reductions were obtained in lead time (16.44%), non-value added time (61.03%), transportation distances (40.42%), and waiting time (86%). Additionally, lean implementation resulted in reduced inventory, reduced internal traffic, improved productivity, and improved customer service.The LTs selection framework presented in this research work addresses the computational complexity associated with the existing models and allows the segregation of most preferable and least preferable criterion which eliminates the criteria weight generation methods

Bibliometric analysis of scientific production on methods to aid decision making in the last 40 years

Purpose: Multicriteria methods have gained traction in both academia and industry practices for effective decision-making over the years. This bibliometric study aims to explore and provide an overview of research carried out on multicriteria methods, in its various aspects, over the past forty-four years. Design/Methodology/Approach: The Web of Science (WoS) and Scopus databases were searched for publications from January 1945 to April 29, 2021, on multicriteria methods in titles, abstracts, and keywords. The bibliographic data were analyzed using the R bibliometrix package. Findings: This bibliometric study asserts that 29,050 authors have produced 20,861 documents on the theme of multicriteria methods in 131 countries in the last forty-four years. Scientific production in this area grows at a rate of 13.88 per year. China is the leading country in publications with 14.14%; India with 10.76%; and Iran with 8.09%. Islamic Azad University leads others with 504 publications, followed by the Vilnius Gediminas Technical University with 456 and the National Institute of Technology with 336. As for journals, Expert Systems With Applications; Sustainability; and Journal of Cleaner Production are the leading journals, which account for more than 4.67% of all indexed literature. Furthermore, Zavadskas E. and Wang J have the highest publications in the multicriteria methods domain regarding the authors. Regarding the most commonly used multicriteria decision-making methods, AHP is the most favored approach among the ten countries with the most publications in this research area, followed by TOPSIS, VIKOR, PROMETHEE, and ANP. Practical implications: The bibliometric literature review method allows the researchers to explore the multicriteria research area more extensively than the traditional literature review method. It enables a large dataset of bibliographic records to be systematically analyzed through statistical measures, yielding informative insights. Originality/value: The usefulness of this bibliometric study is summed in presenting an overview of the topic of the multicriteria methods during the previous forty-four years, allowing other academics to use this research as a starting point for their research

APPLICATION OF THE DIBR II – ROUGH MABAC DECISION-MAKING MODEL FOR RANKING METHODS AND TECHNIQUES OF LEAN ORGANIZATION SYSTEMS MANAGEMENT IN THE PROCESS OF TECHNICAL MAINTENANCE

This paper presents a multi-criteria decision-making model based on the application of two methods, DIBR II and MABAC. The DIBR II method was used to define weight coefficients. The MABAC method was used to rank alternatives, and it was applied in a rough environment. Four experts were engaged in defining the criteria and alternatives as well as in the relation of criteria. The model was applied for ranking the methods and techniques of Lean organization systems management in the maintenance of technical systems of special purposes. At the end of the application was conducted a sensitivity analysis which proved the stability of the obtained results

A Framework for Prioritizing Opportunities of Improvement in the Context of Business Excellence Model in Healthcare Organization

In today\u27s world, the healthcare sector is facing challenges to improve the efficiency and effectiveness of its operations. More and more improvement projects are being adopted to enhance healthcare services, making it more patient-centric, and enabling better cost control. Healthcare organizations strive to identify and carry out such improvement initiatives to sustain their businesses and gain competitive advantage. Seeking to reach a higher operational level of excellence, healthcare organizations utilize business excellence criteria to conduct assessment and identify organizational strengths and weaknesses. However, while such assessments routinely identify numerous areas for potential improvement, it is not feasible to conduct all improvement projects simultaneously due to limitations in time, capital, and personnel, as well as conflict with other organization\u27s projects or strategic objectives. An effective prioritization and selection approach is valuable in that it can assist the organization to optimize its available resources and outcomes. This study attempts to enable such an approach by developing a framework to prioritize improvement opportunities in healthcare in the context of the business excellence model through the integration of the Fuzzy Delphi Method and Fuzzy Interface System. To carry out the evaluation process, the framework consists of two phases. The first phase utilizes Fuzzy Delphi Method to identify the most significant factors that should be considered in healthcare for electing the improvement projects. The FDM is employed to handle the subjectivity of human assessment. The research identifies potential factors for evaluating projects, then utilizes FDM to capture expertise knowledge. The first round in FDM is intended to validate the identified list of factors from experts; which includes collecting additional factors from experts that the literature might have overlooked. When an acceptable level of consensus has been reached, a second round is conducted to obtain experts\u27 and other related stakeholders\u27 opinions on the appropriate weight of each factor\u27s importance. Finally, FDM analyses eliminate or retain the criteria to produce a final list of critical factors to select improvement projects. The second phase in the framework attempts to prioritize improvement initiatives using the Hierarchical Fuzzy Interface System. The Fuzzy Interface System combines the experts\u27 ratings for each improvement opportunity with respect to the factors deemed critical to compute the priority index. In the process of calculating the priority index, the framework allows the estimation of other intermediate indices including: social, financial impact, strategical, operational feasibility, and managerial indices. These indices bring an insight into the improvement opportunities with respect to each framework\u27s dimensions. The framework allows for a reduction of the bias in the assessment by developing a knowledge based on the perspectives of multiple experts

Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement-Intuitionistic Fuzzy Sets and Genetic Algorithm Approach

The aim of this research is to propose a hybrid decision-making model for evaluation and selection of quality methods whose application leads to improved reliability of manufacturing in the process industry. Evaluation of failures and determination of their priorities are based on failure mode and effect analysis (FMEA), which is a widely used framework in practice combining with triangular intuitionistic fuzzy numbers (TIFNs). The all-existing uncertainties in the relative importance of the risk factors (RFs), their values, applicability of the quality methods, as well as implementation costs are described by pre-defined linguistic terms which are modeled by the TIFNs. The selection of quality methods is stated as the rubber knapsack problem which is decomposed into subproblems with a certain number of solution elements. The solution of this problem is found by using genetic algorithm (GA). The model is verified through the case study with the real-life data originating from a significant number of organizations from one region. It is shown that the proposed model is highly suitable as a decision-making tool for improving the manufacturing process reliability in small and medium enterprises (SMEs) of process industry