Simulation‐Based Lean Six‐Sigma and Design for Six‐Sigma

El‐Haik, Basem; Al‐Aomar, Raid

doi:10.1002/0470047720

Cited by 61 publications

(34 citation statements)

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“…To address this issue, Six Sigma applications have grown to include the design and redesign of both products and services, which is known as DFSS (El-Haik & Roy, 2005). DFSS focuses on building quality into products/services by identifying what customers want/need, translating these into critical-to-quality characteristics, deploying these through specific aspects of the product/service design, and verifying that the final design appropriately addresses the original intent (i.e., to fulfill customers' needs) (Mast, Diepstraten, & Does, 2011;El-Haik & Al-Aomar, 2006;Yang & El-Haik, 2003). Previous discussions in the literature have pointed out that as there is no standard framework to guide the use of the DFSS methodology (Watson & DeYong, 2010); yet, Yang (2005) suggests that the DMADV (Define, Measure, Analyze, Design, and Verify) methodology is appropriate to use when designing service processes, as it specifically addresses redesigning processes, which is a common occurrence in servicebased organizations.…”

Section: Supply Chain Improvement Methodsmentioning

confidence: 99%

Improving supply chain information sharing using Design for Six Sigma

Mitchell

Kovach

2016

European Research on Management and Business Economics

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Available online xxx JEL classification: L91 R49 M11a b s t r a c t Accurate and reliable information is needed to support decision-making processes. Due to the large number of participants typically involved in supply chain operations, organizations often find that it is difficult to effectively share information within a supply chain; hence, this research examined ways to improve information sharing within supply chain operations for one marine transportation services organization. An action research, case study approach used the Design for Six Sigma (DFSS) methodology to design an information technology solution that effectively communicates information between the layers within the supply chain regarding the movement of materials via inland tank barges. The comparative analysis of verification and baseline measurements conducted suggests this project was successful because the new process fulfilled the needs of the work environment for which it was designed. For the organization that participated in this research, the successful adoption of the new approach for information sharing improved communication and decision making within their supply chain. Códigos JEL: L91 R49 M11 Palabras clave: Diseño para Six Sigma Cadena de suministro Transporte Intercambio de información Estudio de casor e s u m e n Este trabajo se fundamenta en la necesidad de contar con información precisa y fiable en los procesos de toma de decisiones. Debido al gran número de personas que suelen participar en las operaciones de la cadena de suministro, las empresas se encuentran con que resulta difícil compartir información de manera efectiva en estas operaciones. En este trabajo se examinaron las maneras de mejorar el intercambio de información en estas operaciones en una empresa de servicios de transporte marítimo. Para ello, se realizó el estudio de un caso en el que se empleó la metodología de Diseño para Six Sigma (DFSS) para obtener una solución que permita la comunicación eficaz de la información entre las distintas etapas de la cadena de suministro con respecto al movimiento de materiales en aguas interiores a través de barcazas cisterna. El análisis comparativo de las medidas que se realizaron sugiere que este proyecto tuvo éxito gracias a que el nuevo proceso se ajusta a las necesidades del entorno de trabajo para el que fue diseñado. La puesta en marcha del nuevo enfoque para el intercambio de información mejoró sustancialmente la comunicación y la toma de decisiones dentro de la cadena de suministro de esta empresa.

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Section: Supply Chain Improvement Methodsmentioning

confidence: 99%

Improving supply chain information sharing using Design for Six Sigma

Mitchell

Kovach

2016

European Research on Management and Business Economics

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“…A convergence test at the end of each step controls whether any stopping criterion is met (maximum number of generations reached or convergence rate achieved). For a detailed discussion we refer to [27]. Because of the criticism on SNRs, some authors like [48] suggest to build separate models for the mean and variance of the system performance, adopting the so-called Dual Response Surface approach.…”

Section: Extensions To Taguchi's Methodsmentioning

confidence: 99%

Metamodel-Based Robust Simulation-Optimization: An Overview

Dellino

Kleijnen

Meloni

2015

Uncertainty Management in Simulation-Optimization of Complex Systems

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The simulation-optimization process aims to identify the setting of input parameters leading to optimal system performance, evaluated through a simulation model of the system itself. The factors involved in the simulation model are often noisy and cannot be controlled or varied during the decision process, due to measurement errors or other implementation issues; moreover, some factors are determined by the environment, rather than by managers or decision makers. Therefore, the presumed optimal solution may turn out to be sub-optimal or even infeasible. Robust optimization tackles problems affected by uncertainty, providing solutions that are in some sense insensitive to perturbations in the model parameters.G. Dellino ( ) Istituto per le Applicazioni del Calcolo "Mauro Picone",

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“…A simulation model of a system enhances the VSM model in multiple ways (Marvel and Standridge, 2009), (El-Haik and Al-Aomar, 2006). Both structural and random variability are commonly included in simulation models and the effects of variability on system performance can be determined.…”

Section: Value Stream Mapping (Vsm) and Discrete Event Simulationmentioning

confidence: 99%

Measuring lean implementation for maintenance service companies

Jong

Blokland

2016

International Journal of Lean Six Sigma

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Purpose -Implementation of lean manufacturing is currently performed in the production industry, however for the airline maintenance service industry it is still in its infancy. Indicators such as work in process, cycle time, on time performance and inventory are useful indicators to measure lean implementation, however a financial economic perspective taking fixed assets in consideration is still missing. Hence the purpose of this paper is to propose a method to measure lean implementation from a fixed asset perspective for this type of industry. With the indicators, continuous improvement scenarios are explored by value stream discrete event simulation. 2Practical implication -The Lean Transaction Cost Efficiency Model provides the capability for a maintenance service company to simulate the effects of process improvements on operations performance for service based companies prior to implementation.Social implication -Simulation of a Greenfield process can involve employees with possible changes in processes. This approach supports the adoption of anticipated changes.Originality/value -The found indicators form a preliminary model, which contributes to the usage and linkage of theories on lean manufacturing and transaction cost theory -asset specificity.

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Simulation‐Based Lean Six‐Sigma and Design for Six‐Sigma

Cited by 61 publications

References 0 publications

Improving supply chain information sharing using Design for Six Sigma

Improving supply chain information sharing using Design for Six Sigma

Metamodel-Based Robust Simulation-Optimization: An Overview

Measuring lean implementation for maintenance service companies

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