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Article
Publication date: 1 August 2016

Gabriele Arcidiacono, Nico Costantino and Kai Yang

The sustainability of the Lean Six Sigma (LSS) program represents the most challenging aspect for most of the organizations dealing with this methodology. In this scenario, the…

Abstract

Purpose

The sustainability of the Lean Six Sigma (LSS) program represents the most challenging aspect for most of the organizations dealing with this methodology. In this scenario, the purpose of this paper is the description of the AMSE (which stands for Assessment, Monitoring, Sustainability, Expansion) Model, that represents a leading-edge approach to implement an effective LSS deployment on a permanent basis, by means of a structured roadmap.

Design/methodology/approach

The AMSE roadmap is made of four operating phases – Assessment, Monitoring, Sustainability, Expansion – it is a Model to govern the LSS deployment and to maximize both operative and economical results on a long-term basis.

Findings

One of the main problems of LSS programs is their sustainability (sustainability of projects and the overall program) over time; the AMSE Model allows the deployment of an LSS Governance Structure with a clear definition of tasks; this model can be effectively applied both to small and medium enterprises (SMEs) and global companies, regardless of the sector.

Practical implications

Both SMEs and global corporations could benefit from applying the AMSE in terms of operational efficiency, culture improvement and people engagement.

Originality/value

The AMSE Model represents an innovative approach for sustaining a continuous improvement culture in the organizations over time, by defining four steps (Assessment, Monitoring, Sustainability, Expansion), divided into detailed tasks, each of which is characterized by its own specific tools.

Details

International Journal of Lean Six Sigma, vol. 7 no. 3
Type: Research Article
ISSN: 2040-4166

Keywords

Article
Publication date: 26 July 2018

Sonali Udeeka Pathiratne, Ali Khatibi and Md Gapar Md Johar

This paper aims to identify and review the critical success factors (CSFs) for successful Six Sigma implementation in service and manufacturing companies given in published…

Abstract

Purpose

This paper aims to identify and review the critical success factors (CSFs) for successful Six Sigma implementation in service and manufacturing companies given in published literature.

Design/methodology/approach

A descriptive evaluation of the literature body is followed by future research opportunities. Studies published on the topic of Six Sigma during 2005-2016 are reviewed to retrieve identified CSFs.

Findings

From published literature, 48 CSFs vital for Six Sigma implementation were identified. The identified CSFs were classified under eight core categories. As per the categorization, 35 out of 48 CSFs identified are either Company Strategy related, Six Sigma Project related or Human Resources related. Only a limited number of studies are carried out mainly focusing on the stated three core areas. Hence, it is vital that these three core areas are further explored in future research.

Originality/value

With the outcome of this paper, the identified CSFs for Six Sigma will be taken for further studies, where they will be applied to service and manufacturing companies based in Sri Lanka. Hence, it would provide Sri Lankan service and manufacturing companies guidelines for successful implementation of Six Sigma for future endeavors.

Details

International Journal of Lean Six Sigma, vol. 9 no. 4
Type: Research Article
ISSN: 2040-4166

Keywords

Article
Publication date: 1 January 1992

A. Kos

Temperature field computations of hybrid power circuits require considerable numerical effort. This paper presents rules which show both how to limit the number of terms of the…

Abstract

Temperature field computations of hybrid power circuits require considerable numerical effort. This paper presents rules which show both how to limit the number of terms of the Fourier series and how to estimate the error which is the effect of this reduction.

Details

Microelectronics International, vol. 9 no. 1
Type: Research Article
ISSN: 1356-5362

Article
Publication date: 1 January 1991

Jose A.D. PINTO, Paulo B. COIMBRA and Carlos F.L. ANTUNES

Empirical rules and experimental evidence are not capable of dealing with both geometric complexity and nonlinearities to design a sufficient accurate, reliable and affordable…

Abstract

Empirical rules and experimental evidence are not capable of dealing with both geometric complexity and nonlinearities to design a sufficient accurate, reliable and affordable electrical device. To minimize this gap and to achieve an high performance level in the industry design of an electromagnetic device two CAD packages (electromagnetic CAD package and thermal CAD package) working in parallel processing should be used. In this paper these two packages have been used separately. The finite element technique is used to solve the heat conduction problem in complex devices of arbitrary shape with imposed boundary conditions. As an application example, the steady‐state temperature distribution will be produced for an high voltage cross‐linked polyethylene insulated power cable. The results are discussed and the importance of such a study as an aid to improve the life expectancy of high voltage power cables is pointed out. Finally, several conclusions are suggested to increase the power cable current transmission capacity.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 10 no. 1
Type: Research Article
ISSN: 0332-1649

Article
Publication date: 1 February 2004

Zhijie Chen, Qile Chen, Weizhen Chen and Yinao Wang

This paper describes the use of grey system theory in mathematical programming problems. In particular, the linear programming problem, which is one of the most widely used…

1658

Abstract

This paper describes the use of grey system theory in mathematical programming problems. In particular, the linear programming problem, which is one of the most widely used mathematical programming problems, with grey interval and grey forecasting are developed. The adaptability of both these linear programming problems is rather satisfactory.

Details

Kybernetes, vol. 33 no. 2
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 17 August 2018

Michael Popp and Wolfgang Mathis

The purpose of this paper is to present the embedding of linear and nonlinear order reduction methods in a theoretical framework for handling hierarchically interconnected…

Abstract

Purpose

The purpose of this paper is to present the embedding of linear and nonlinear order reduction methods in a theoretical framework for handling hierarchically interconnected dynamical systems.

Design/methodology/approach

Based on the component connection modeling (CCM), a modified framework called mCCM for describing interconnected dynamic systems especially with hierarchical structures is introduced and used for order reduction purposes. The balanced truncation method for linear systems and the trajectory piecewise linear reduction scheme are used for the order reduction of systems described within the mCCM framework.

Findings

It is shown that order reduction methods can be embedded into the context of interconnected dynamical systems with the benefit of having a further degree of freedom in form of the hierarchical level, on which the order reduction is performed.

Originality/value

The aspect of hierarchy within system descriptions is exploited for order reduction purposes. This distinguishes the presented approach from common methods, which already start with single large-scale systems without explicitly considering hierarchical structures.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 37 no. 4
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 17 June 2020

Davood Darvishi, Sifeng Liu and Jeffrey Yi-Lin Forrest

The purpose of this paper is to survey and express the advantages and disadvantages of the existing approaches for solving grey linear programming in decision-making problems.

Abstract

Purpose

The purpose of this paper is to survey and express the advantages and disadvantages of the existing approaches for solving grey linear programming in decision-making problems.

Design/methodology/approach

After presenting the concepts of grey systems and grey numbers, this paper surveys existing approaches for solving grey linear programming problems and applications. Also, methods and approaches for solving grey linear programming are classified, and its advantages and disadvantages are expressed.

Findings

The progress of grey programming has been expressed from past to present. The main methods for solving the grey linear programming problem can be categorized as Best-Worst model, Confidence degree, Whitening parameters, Prediction model, Positioned solution, Genetic algorithm, Covered solution, Multi-objective, Simplex and dual theory methods. This survey investigates the developments of various solving grey programming methods and its applications.

Originality/value

Different methods for solving grey linear programming problems are presented, where each of them has disadvantages and advantages in providing results of grey linear programming problems. This study attempted to review papers published during 35 years (1985–2020) about grey linear programming solving and applications. The review also helps clarify the important advantages, disadvantages and distinctions between different approaches and algorithms such as weakness of solving linear programming with grey numbers in constraints, inappropriate results with the lower bound is greater than upper bound, out of feasible region solutions and so on.

Details

Grey Systems: Theory and Application, vol. 11 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 1 June 2004

F.M.E. Uzoka and J.O. Famuyiwa

Medical diagnosis and treatment constitute a network of inter‐related processes. The conventional method of medical diagnosis and treatment of diseases involves a state space…

Abstract

Medical diagnosis and treatment constitute a network of inter‐related processes. The conventional method of medical diagnosis and treatment of diseases involves a state space search of the medical knowledge of diseases and patient history, which could be combinatorially explosive. This paper presents a report on the experimental study of an intelligent, interactive, user‐friendly, knowledge‐based system which performs a stepwise analysis of a patient's complaints, filtering cognitive and emotional elements to be able to make inferences. It applies both forward and backward chaining in making inferences concerning the management of disease. A case study of the system is carried out using some tropical diseases. It is believed that the system will serve as a useful contribution towards tropical medical informatics.

Details

International Journal of Health Care Quality Assurance, vol. 17 no. 4
Type: Research Article
ISSN: 0952-6862

Keywords

Book part
Publication date: 13 May 2017

David Card, David S. Lee, Zhuan Pei and Andrea Weber

A regression kink design (RKD or RK design) can be used to identify casual effects in settings where the regressor of interest is a kinked function of an assignment variable. In…

Abstract

A regression kink design (RKD or RK design) can be used to identify casual effects in settings where the regressor of interest is a kinked function of an assignment variable. In this chapter, we apply an RKD approach to study the effect of unemployment benefits on the duration of joblessness in Austria, and discuss implementation issues that may arise in similar settings, including the use of bandwidth selection algorithms and bias-correction procedures. Although recent developments in nonparametric estimation (Calonico, Cattaneo, & Farrell, 2014; Imbens & Kalyanaraman, 2012) are sometimes interpreted by practitioners as pointing to a default estimation procedure, we show that in any given application different procedures may perform better or worse. In particular, Monte Carlo simulations based on data-generating processes that closely resemble the data from our application show that some asymptotically dominant procedures may actually perform worse than “sub-optimal” alternatives in a given empirical application.

Details

Regression Discontinuity Designs
Type: Book
ISBN: 978-1-78714-390-6

Book part
Publication date: 13 May 2017

Otávio Bartalotti, Gray Calhoun and Yang He

This chapter develops a novel bootstrap procedure to obtain robust bias-corrected confidence intervals in regression discontinuity (RD) designs. The procedure uses a wild…

Abstract

This chapter develops a novel bootstrap procedure to obtain robust bias-corrected confidence intervals in regression discontinuity (RD) designs. The procedure uses a wild bootstrap from a second-order local polynomial to estimate the bias of the local linear RD estimator; the bias is then subtracted from the original estimator. The bias-corrected estimator is then bootstrapped itself to generate valid confidence intervals (CIs). The CIs generated by this procedure are valid under conditions similar to Calonico, Cattaneo, and Titiunik’s (2014) analytical correction – that is, when the bias of the naive RD estimator would otherwise prevent valid inference. This chapter also provides simulation evidence that our method is as accurate as the analytical corrections and we demonstrate its use through a reanalysis of Ludwig and Miller’s (2007) Head Start dataset.

Details

Regression Discontinuity Designs
Type: Book
ISBN: 978-1-78714-390-6

Keywords

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