scholarly journals A robust multi response surface approach for optimization of multistage processes

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amir Moslemi ◽  
Mahmood Shafiee
Keyword(s):  
Robust Optimization ◽  
Response Surface ◽  
Numerical Study ◽  
Ordinary Least Squares ◽  
Response Surfaces ◽  
Estimation Methods ◽  
Design Parameters ◽  
Optimization Approach ◽  
Content Type

PurposeIn a multistage process, the final quality in the last stage not only depends on the quality of the task performed in that stage but is also dependent on the quality of the products and services in intermediate stages as well as the design parameters in each stage. One of the most efficient statistical approaches used to model the multistage problems is the response surface method (RSM). However, it is necessary to optimize each response in all stages so to achieve the best solution for the whole problem. Robust optimization can produce very accurate solutions in this case.Design/methodology/approachIn order to model a multistage problem, the RSM is often used by the researchers. A classical approach to estimate response surfaces is the ordinary least squares (OLS) method. However, this method is very sensitive to outliers. To overcome this drawback, some robust estimation methods have been presented in the literature. In optimization phase, the global criterion (GC) method is used to optimize the response surfaces estimated by the robust approach in a multistage problem.FindingsThe results of a numerical study show that our proposed robust optimization approach, considering both the sum of square error (SSE) index in model estimation and also GC index in optimization phase, will perform better than the classical full information maximum likelihood (FIML) estimation method.Originality/valueTo the best of the authors’ knowledge, there are few papers focusing on quality-oriented designs in the multistage problem by means of RSM. Development of robust approaches for the response surface estimation and also optimization of the estimated response surfaces are the main novelties in this study. The proposed approach will produce more robust and accurate solutions for multistage problems rather than classical approaches.

Robust optimization of multistage process: response surface and multi-response optimization approaches

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Amir Moslemi ◽  
Mirmehdi Seyyed-Esfahani
Keyword(s):  
Response Surface ◽  
Model Building ◽  
Optimization Methods ◽  
Ordinary Least Squares ◽  
Response Surfaces ◽  
Estimation Methods ◽  
Multistage System ◽  
Multiple Components ◽  
Global Criterion ◽  
Response Optimization

Abstract A multistage system refers to a system contains multiple components or stages which are necessary to finish the final product or service. To analyze these problems, the first step is model building and the other is optimization. Response surfaces are used to model multistage problem as an efficient procedure. One regular approach to estimate a response surface using experimental results is the ordinary least squares (OLS) method. OLS method is very sensitive to outliers, so some multivariate robust estimation methods have been discussed in the literature in order to estimate the response surfaces accurately such as multivariate M-estimators. In optimization phase, multi-response optimization methods such as global criterion (GC) method and ε-constraints approaches are different methods to optimize the multi-objective-multistage problems. An example of the multistage problem had been estimated considering multivariate robust approaches, besides applying multi-response optimization approaches. The results show the efficiency of the proposed approaches.

Dynamic endogeneity and corporate governance-performance relationship

2017 ◽  
Vol 44 (5) ◽  
pp. 727-744
Author(s):  
Sujani Thrikawala ◽  
Stuart Locke ◽  
Krishna Reddy
Keyword(s):  
Corporate Governance ◽  
National Level ◽  
Estimation Method ◽  
Estimation Methods ◽  
Governance System ◽  
Past Performance ◽  
Gmm Estimation ◽  
Content Type ◽  
Dynamic Framework

Purpose The purpose of this paper is to examine the relationship between corporate governance (CG) and microfinance institution (MFI) performance, using a dynamic panel generalised method of moments (GMM) estimator to mitigate the serious issues with endogeneity. Design/methodology/approach Inconsistent findings and a general lack of empirical results for the microfinance industry leave an unclear message regarding the impacts of CG on MFI performance, especially in emerging economies. The authors use GMM estimation techniques to examine whether CG has an influence on MFI performance. Findings This study confirms that the MFIs’ contemporaneous performance and CG characteristics are statistically significantly positively linked with their past performance. This study finds statistically significant governance effects on MFI performance, including the presence of international directors and/or donor representatives on the board, client representatives on the board, percentage of non-executive directors and the quality of the national governance system. Practical implications These findings provide some insights for policy-makers and practitioners to develop suitable policies and guidelines to streamline MFIs’ operations in emerging countries. Moreover, national and international investors and donors may use these finding as a benchmark for their investment and funding decisions. Originality/value This paper is the first to estimate the CG and performance relationship of MFIs in a dynamic framework by applying the GMM estimation method. This approach improves upon traditional estimation methods by controlling the likely sources of endogeneity. Further, this paper examines whether quality of national-level governance characteristics is related to performance measures of profitability and outreach of MFIs.

The impact of gender inequality in education and employment on economic performance in Turkey: evidence from a cointegration approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ömer Esen ◽  
Gamze Yıldız Seren
Keyword(s):  
Least Squares ◽  
Economic Performance ◽  
Ordinary Least Squares ◽  
Estimation Methods ◽  
Content Type ◽  
Cointegration Tests ◽  
Johansen Cointegration ◽  
Education And Employment ◽  
The Impact

PurposeThis study aims to empirically examine the impact of gender-based inequalities in both education and employment on economic performance using the dataset of Turkey for the period 1975–2018.Design/methodology/approachThis study employs Johansen cointegration tests to analyze the existence of a long-term relation among variables. Furthermore, dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) estimation methods are performed to determine the long-run coefficients.FindingsThe findings from the Johansen cointegration analysis confirm that there is a long-term cointegration relation between variables. Moreover, DOLS and FMOLS results reveal that improvements in gender equality in both education and employment have a strong and significant impact on real gross domestic product (GDP) per capita in the long term.Originality/valueThe authors expect that this study will make remarkable contributions to the future academic studies and policy implementation, as it examines the relation among the variables by including the school life expectancy from primary to tertiary based on the gender parity index (GPI), the gross enrollment ratio from primary to tertiary based on GPI and the ratio of female to male labor force participation (FMLFP) rate.

Competitive capabilities in knowledge-intensive services firms: strategic advantages of born globals in a peripheral region

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marta Muñoz Guarasa ◽  
Bruno Brandão Fischer
Keyword(s):  
Service Sector ◽  
Ordinary Least Squares ◽  
Peripheral Region ◽  
Quality Of Services ◽  
Service Firms ◽  
Born Global ◽  
Specific Domain ◽  
Content Type ◽  
Knowledge Intensive

Purpose While the born global (BG) phenomenon has been well established in the literature, studies on accelerated internationalization of firms in the service sector have been scarce, particularly for the specific case of knowledge-intensive services (KIS). The purpose of this paper is to explore which competitive characteristics differentiate KIS BGs from other KIS firms in the context of a peripheral region. Design/methodology/approach The empirical focus of this study comprehends primary survey data from 250 Spanish KIS firms (Andalusia) that have been internationalized and analyzed through ordinal and ordinary least squares regressions. The authors address the “born-global effect” on five features of interest, namely, entry mode, technological capabilities, qualification of staff, external resources and quality of services. Findings Results suggest that KIS BGs in Andalusia perceive exports as a more relevant form of internationalization than its non-BG peers. Also, KIS BGs in Andalusia present higher levels of technological intensity. Differences in terms of staff qualification, access to extramural R&D resources and the quality of services could not be identified. Research limitations/implications The main limitation of this research concerns its cross-sectional character, thus hindering the evaluation of developmental trajectories taking place in the cohort under scrutiny. Such an approach would allow a better comprehension of the competitiveness dynamics in internationalized KIS firms. Also, because this assessment is geographically restricted to Andalusia, Spain, the authors recommend caution in establishing direct comparisons and appropriation of results for other regional/national contexts. Practical implications Recommendations for public policy include establishing the necessary infrastructures to encourage the technological development of KIS companies and provide support – through export promotion agencies, for instance – for early approximation with foreign markets. Taking into account the contributions of KIS firms for the development of a peripheral economy, this involves the need to establish instruments that provide strategic information to internationalize, as well as lines of funding for these companies. Originality/value Empirical evidence on KIS BGs is needed to fully grasp its differences to other internationalized service firms. The analysis within this specific domain represents an advance in the literature on this subject. Also, the context of peripheral regions – considering their economic differences to core areas – has been understudied. The elaboration and application of the survey have allowed the authors to have access to primary in-depth data and, therefore, to build a better understanding of KIS BGs in Andalusia, Spain.

Robust optimization approach to production system with failure in rework and breakdown under uncertainty: evolutionary methods

2015 ◽  
Vol 35 (1) ◽  
pp. 81-93 ◽  
Author(s):  
Masoud Rabbani ◽  
Neda Manavizadeh ◽  
Niloofar Sadat Hosseini Aghozi
Keyword(s):  
Mathematical Model ◽  
Robust Optimization ◽  
Production Planning ◽  
Production System ◽  
Demand Uncertainty ◽  
Optimization Techniques ◽  
Planning Problem ◽  
Optimization Approach ◽  
Content Type ◽  
Evolutionary Methods

Purpose – This paper aims to consider a multi-site production planning problem with failure in rework and breakdown subject to demand uncertainty. Design/methodology/approach – In this new mathematical model, at first, a feasible range for production time is found, and then the model is rewritten considering the demand uncertainty and robust optimization techniques. Here, three evolutionary methods are presented: robust particle swarm optimization, robust genetic algorithm (RGA) and robust simulated annealing with the ability of handling uncertainties. Firstly, the proposed mathematical model is validated by solving a problem in the LINGO environment. Afterwards, to compare and find the efficiency of the proposed evolutionary methods, some large-size test problems are solved. Findings – The results show that the proposed models can prepare a promising approach to fulfill an efficient production planning in multi-site production planning. Results obtained by comparing the three proposed algorithms demonstrate that the presented RGA has better and more efficient solutions. Originality/value – Considering the robust optimization approach to production system with failure in rework and breakdown under uncertainty.

The behaviour of solder pastes in stencil printing with electropolishing process

2013 ◽  
Vol 25 (3) ◽  
pp. 164-174 ◽  
Author(s):  
Yong‐Won Lee ◽  
Keun‐Soo Kim ◽  
Katsuaki Suganuma
Keyword(s):  
Circuit Board ◽  
Surface Finishing ◽  
Design Parameters ◽  
Solder Paste ◽  
Stencil Printing ◽  
Printing Process ◽  
Content Type ◽  
Solder Paste Printing ◽  
Solder Mask

PurposeThe purpose of this paper is to study the effect of the electropolishing time of stencil manufacturing parameters and solder‐mask definition methods of PCB pad design parameters on the performance of solder paste stencil printing process for the assembly of 01005 chip components.Design/methodology/approachDuring the study, two types of stencils were manufactured for the evaluations: electroformed stencils and electropolished laser‐cut stencils. The electroformed stencils were manufactured using the standard electroforming process and their use in the paste printing process was compared against the use of an electropolished laser‐cut stencil. The electropolishing performance of the laser‐cut stencil was evaluated twice at the following intervals: 100 s and 200 s. The performance of the laser‐cut stencil was also evaluated without electropolishing. An optimized process was established after the polished stencil apertures of the laser‐cut stencil were inspected. The performance evaluations were made by visually inspecting the quality of the post‐surface finishing for the aperture wall and the quality of that post‐surface finishing was further checked using a scanning electron microscope. A test board was used in a series of designed experiments to evaluate the solder paste printing process.FindingsThe results demonstrated that the length of the electropolishing time had a significant effect on the small stencil's aperture quality and the solder paste's stencil printing performance. In this study, the most effective electropolishing time was 100 s for a stencil thickness of 0.08 mm. The deposited solder paste thickness was significantly better for the enhanced laser‐cut stencil with electropolishing compared to the conventional electroformed stencils. In this printing‐focused work, print paste thickness measurements were also found to vary across different solder‐mask definition methods of printed circuit board pad designs with no change in the size of the stencil aperture. The highest paste value transfer consistently occurred with solder‐mask‐defined pads, when an electropolished laser‐cut stencil was used.Originality/valueDue to important improvements in the quality of the electropolished laser‐cut stencil, and based on the results of this experiment, the electropolished laser‐cut stencil is strongly recommended for the solder paste printing of fine‐pitch and miniature components, especially in comparison to the typical laser‐cut stencil. The advantages of implementing a 01005 chip component mass production assembly process include excellent solder paste release, increased solder volume, good manufacture‐ability, fast turnaround time, and greater cost saving opportunities.

Multiobjective approach developed for optimizing the dynamic behavior of incremental linear actuators

2014 ◽  
Vol 33 (3) ◽  
pp. 953-964 ◽  
Author(s):  
Imen Amdouni ◽  
Lilia El Amraoui ◽  
Frédéric Gillon ◽  
Mohamed Benrejeb ◽  
Pascal Brochet
Keyword(s):  
Multiobjective Optimization ◽  
Dynamic Model ◽  
Dynamic Behavior ◽  
Pareto Front ◽  
Computing Time ◽  
Design Parameters ◽  
Parallel Optimization ◽  
Optimization Approach ◽  
Content Type ◽  
Linear Actuators

Purpose – The purpose of this paper is to develop an optimal approach for optimizing the dynamic behavior of incremental linear actuators. Design/methodology/approach – First, a parameterized design model is built. Second, a dynamic model is implemented. This model takes into account the thrust force computed from a finite element model. Finally, the multiobjective optimization approach is applied to the dynamic model to optimize control as well as design parameters. Findings – The Pareto front resulting from the optimization approach (or the parallel optimization approach,) is better than the Pareto, which is obtained from the only application of MultiObjective Genetic Algorithm (MOGA) method (or parallel MOGA with the same number of optimization approach objective function evaluations). The only use of MOGA can reach the region near an optimal Pareto front, but it consumes more computing time than the multiobjective optimization approach. At each flowchart stage, parallelization leads to a significant reduction of computing time which is halved when using two-core machine. Originality/value – In order to solve the multiobjective problem, a hybrid algorithm based on MOGA is developed.

Response surface approach to robust design of assembly cells through simulation

2018 ◽  
Vol 38 (4) ◽  
pp. 450-464 ◽  
Author(s):  
Cem Savas Aydin ◽  
Senim Ozgurler ◽  
Mehmet Bulent Durmusoglu ◽  
Mesut Ozgurler
Keyword(s):  
Response Surface ◽  
Robust Design ◽  
Performance Measures ◽  
Performance Optimization ◽  
Design Approach ◽  
Shop Floor ◽  
Optimization Approach ◽  
Content Type ◽  
Performance Variability ◽  
Noise Factors

Purpose This paper aims to present a multi-response robust design (RD) optimization approach for U-shaped assembly cells (ACs) with multi-functional walking-workers by using operational design (OD) factors in a simulation setting. The proposed methodology incorporated the design factors related to the operation of ACs into an RD framework. Utilization of OD factors provided a practical design approach for ACs addressing system robustness without modifying the cell structure. Design/methodology/approach Taguchi’s design philosophy and response surface meta-models have been combined for robust simulation optimization (SO). Multiple performance measures have been considered for the study and concurrently optimized by using a multi-response optimization (MRO) approach. Simulation setting provided flexibility in experimental design selection and facilitated experiments by avoiding cost and time constraints in real-world experiments. Findings The present approach is illustrated through RD of an AC for performance measures: average throughput time, average WIP inventory and cycle time. Findings are in line with expectations that a significant reduction in performance variability is attainable by trading-off optimality for robustness. Reductions in expected performance (optimality) values are negligible in comparison to reductions in performance variability (robustness). Practical implications ACs designed for robustness are more likely to meet design objectives once they are implemented, preventing changes or roll-backs. Successful implementations serve as examples to shop-floor personnel alleviating issues such as operator/supervisor resistance and scepticism, encouraging participation and facilitating teamwork. Originality/value ACs include many activities related to cell operation which can be used for performance optimization. The proposed framework is a realistic design approach using OD factors and considering system stochasticity in terms of noise factors for RD optimization through simulation. To the best of the authors’ knowledge, it is the first time a multi-response RD optimization approach for U-shaped manual ACs with multi-functional walking-workers using factors related to AC operation is proposed.

A novel robust multivariate regression approach to optimize multiple surfaces

2018 ◽  
Vol 52 (4-5) ◽  
pp. 1233-1243
Author(s):  
Amir Moslemi ◽  
Mirmehdi Seyyed-Esfahani
Keyword(s):  
Response Surface ◽  
Multivariate Regression ◽  
Ordinary Least Squares ◽  
Response Surfaces ◽  
Response Models ◽  
New Approach ◽  
Global Criterion ◽  
Global Criterion Method ◽  
Controllable Factors ◽  
Criterion Method

Response surface methodology involves relationships between different variables, specifically experimental inputs as controllable factors, and a response or responses by incorporating uncontrollable factors named nuisance. In order to optimize these response surfaces, we should have accurate response models. A common approach to estimate a response surface is the ordinary least squares (OLS) method. Since OLS is very sensitive to outliers, some robust approaches have been discussed in the literature. Most problems face with more than one response which are mostly correlated, that are called multi-response problem. This paper presents a new approach which takes the benefits of robust multivariate regression to cope with the mentioned difficulties. After estimating accurate response surfaces, optimization phase should be applied in order to have proper combination of variables and optimum solutions. Global criterion method of multi-objective optimization has also been used to reach a compromise solution which improves all response variables simultaneously. Finally, the proposed approach is described analytically by a numerical example.

Impact of board size on the accounting returns and the asset quality of Indian banks

2020 ◽  
Vol 62 (4) ◽  
pp. 297-313
Author(s):  
Ankur Shukla ◽  
Sivasankaran Narayanasamy ◽  
Ramachandran Krishnakumar
Keyword(s):  
Robust Regression ◽  
Positive Impact ◽  
Ordinary Least Squares ◽  
The Body ◽  
Board Size ◽  
Content Type ◽  
Indian Banks ◽  
Asset Quality ◽  
The Impact

Purpose The purpose of the paper is to explore the impact of board size on the accounting returns and asset quality of Indian banks. Design/methodology/approach This paper uses ordinary least squares regression, robust regression and panel data methods for estimation, based on data collected for a sample of 29 Indian banks that are listed on the National Stock Exchange (NSE) and form part of the NSE-500 index over a period of eight financial years 2009-2016. The data pertaining to the board size of the sample banks is collected from the annual reports of banks, whereas the data relating to return on assets (ROA) and ratio of the gross non-performing assets to total assets and control variables (bank age and bank size) is extracted from ACE Equity database. Findings This paper concludes that the size of the governing board has a positive impact on the accounting returns (measured through ROA) of the Indian banks. Further, board size is observed to be insignificant in determining the asset quality of Indian banks. Originality/value This paper contributes to the literature and practitioners in a number of ways. First, to the best of the authors’ knowledge, this is the first study on the impact of board size on the accounting returns and asset quality of Indian banks. The findings of the study contribute new theoretical insights to the body of knowledge on the influence of the size of the board, which may be useful for future researchers. Second, banks may enhance their financial performance by taking cognizance of the findings of this study. Finally, equity investors may make use of the findings of this article in deciding on whether to invest in a bank’s stock/lend to the bank based on board size of the bank.

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