A Six Sigma DMAIC Process for Supplier Performance Evaluation using AHP and Kano's Model

Fırat, Seniye Ümit Oktay; Akan, Mahmure Övül Arıoğlu; Ersoy, Ece; Gök, Serpil; Ünal, Uğur

doi:10.4018/ijban.2017040103

Cited by 16 publications

(12 citation statements)

References 110 publications

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“…The two major issues that are to be taken care of while developing an effective vendor/supplier evaluation and selection model are -"evaluation criteria and the method to be used". (Fırat et al, 2017). Both of these have been discussed in detail.…”

Section: Literature Reviewmentioning

confidence: 97%

“…Hence Kano Model can be used to identify the "spoken" and "unspoken" customer expectations. (Fırat et al, 2017). "Spoken" expectations are the ones which the customer openly and directly states as wants.…”

Section: Kano Modelmentioning

confidence: 99%

“…AHP being a mathematical model "provides a hierarchical representation that enables analytic decision-making" and is quite versatile in the fields of both qualitative and quantitative analysis. (Fırat et al, 2017). "The AHP method is flexible and allows development stakeholders to assign a priority (relative weight) to each factor through pairwise comparison" (Pesonen et al, 2001) "In AHP analysis, participatory consultation with stakeholders is an initial step for constructing indicators critical for attaining the overall goal and deciding on their corresponding weights" (Baffoe, 2019).…”

Section: The Analytic Hierarchy Process (Ahp)mentioning

confidence: 99%

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RPA Vendor Evaluation and Selection using AHP and Kano Model

Banerjee¹

2021

pae

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Robotic Process Automation (RPA) as a technology has gained momentum due to the onset of Industry 4.0. RPA is considered to be the simplest forms of automation in which, typically, the human actions are mimicked without taking into account the complex judgements associated with it. Hence, RPA is deemed fit for the rule-based tasks which are highly repetitive, bulky and are error-prone. Traditionally, organizations looking to increase its operations efficiency improve workforce utilisation, turn to RPA. With the shift in working pattern enforced by COVID-19, RPA adoption is no more a luxury, but a necessity. In a short span of time, the number of RPA vendors, that is the developers and providers of RPA software have significantly increased and due to current demands of RPA, it is expected to grow further. This increase in choices makes the vendor selection part of any RPA Implementation Project highly complex and confusing. Keeping in mind the significance of the vendor selection process, various methods of RPA Vendor Selection have been previously proposed but it is still evolving along with the changing needs of the Businesses. This Research paper aims to propose a standard model using Kano Model and Analytic Hierarch Process (AHP) such that it can be customized during each new RPA implementation project without compromising on the basic structure and method for evaluation.

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Section: Literature Reviewmentioning

confidence: 97%

Section: Kano Modelmentioning

confidence: 99%

Section: The Analytic Hierarchy Process (Ahp)mentioning

confidence: 99%

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RPA Vendor Evaluation and Selection using AHP and Kano Model

Banerjee¹

2021

pae

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“…Segundo Sokovic et al (2010), o DMAIC nasceu do Six Sigma como uma "abordagem cíclica orientada por dados para melhoria de processos". Atualmente sua aplicação já vai além da esfera industrial em que foi criado, podendo ser adaptado a praticamente qualquer processo de melhoria, inclusive áreas de gestão e cadeia de suprimentos (FIRAT et al, 2017).…”

Section: Introductionunclassified

Aplicação do método DMAIC na melhoria do processo de gerenciamento de fornecedores em uma empresa do setor de óleo e gás

Rodrigues

Angra²,

Ribeiro³

2020

POEE

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Em qualquer tipo de indústria a busca por maior eficiência e melhores resultados é constante. No mercado de óleo e gás a pressão sofrida pelas empresas é ainda maior. As altas cifras movimentadas, as constantes oscilações e as crises do mercado tornam o setor um dos mais desafiadores para se operar. Nesse contexto, as exigências por redução de custos, tempos de processamento e desperdícios cresce continuamente, tornando o gerenciamento da cadeia de suprimentos um dos pontos estratégicos na busca por vantagens competitivas. Ao gerenciar qualquer cadeia de suprimentos o desempenho dos fornecedores é primordial. Uma organização que não gerencia de perto sua rede de fornecedores não alcançará os benefícios inerentes a essa prática e ficará certamente um passo atrás de seus concorrentes. O objetivo deste trabalho é a melhoria no processo de gerenciamento de fornecedores de uma empresa do setor de óleo e gás por meio da aplicação da metodologia lean. Por intermédio da aplicação do método DMAIC foram identificados e tratados pontos de melhoria no sistema, buscando eliminar focos de desperdício e aumentar a eficiência do processo. Como resultado, houve uma redução do número de fornecedores, tornando seu gerenciamento mais eficiente; obteve-se um menor lead time total na compra de materiais; diminuição do número de atrasos na entrega e no número de não conformidades identificadas. O método DMAIC se mostrou eficaz ao ser aplicado na cadeia de suprimentos, melhorando a gestão de fornecedores da companhia e trazendo um melhor desempenho para o processo.

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“…It is related to improvement projects following the define, measure, analyse, improve and control methodology (known as DMAIC), a well-defined project approach, utilisation of selected quality tools, and, in many circumstances, applying lean methodologies and many other specific quality tools. Theory, applications and developments can be found in many references, like Aboelmaged (2010), Antony and Banuelas (2002), Firat et al (2017), Ward, Poling and Clipp (2008), Thomas, Barton and Chuke-Okafor (2009), Tjahjono et al (2010).…”

Section: Introductionmentioning

confidence: 99%

Six Sigma: Main Metrics and R Based Software for Training Purposes and Practical Industrial Quality Control

et al. 2019

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Purpose: To clarify the different types of data likely to occur in any service or industrial process, the main applicable statistics for each type of data and the Six Sigma metrics that allow characterising and benchmarking organisational processes.Methodology/Approach: A short reference to the statistical process control is carried out, from Shewhart’s works to Motorola’s achievements, followed by a short discussion of the use of Six Sigma tools as a part of today’s total quality approaches, and by a discussion of the continuous, attribute and counting data worlds and their main applications in process analysis. Because many quality professionals may have difficulties dealing with engineering perspectives, a review of main classic and Six Sigma process metrics is done with examples. Complementing discussions, four functions written in the R language are presented, which can deal with real organisational data, or can be used for training purposes.Findings: The functions developed provide useful graphical displays and calculate all necessary metrics, having the ability to let the user provide theoretical values for training activities. Real and simulated case studies help understanding data worlds and respective Six Sigma metrics.Research Limitation/implication: This paper reports an intentionally simple theoretical perspective of Six Sigma metrics and friendly software which is available to all interested professionals on request to the authors.Originality/Value of paper: The paper presents clear definitions of main data types and metrics and is supported by a set of four new functions that can be used by any researcher with a minimum knowledge of the R software.

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A Six Sigma DMAIC Process for Supplier Performance Evaluation using AHP and Kano's Model

Cited by 16 publications

References 110 publications

RPA Vendor Evaluation and Selection using AHP and Kano Model

RPA Vendor Evaluation and Selection using AHP and Kano Model

Aplicação do método DMAIC na melhoria do processo de gerenciamento de fornecedores em uma empresa do setor de óleo e gás

Six Sigma: Main Metrics and R Based Software for Training Purposes and Practical Industrial Quality Control

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