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Article
Publication date: 16 April 2018

Jinglai Wu, Zhen Luo, Nong Zhang and Wei Gao

This paper aims to study the sampling methods (or design of experiments) which have a large influence on the performance of the surrogate model. To improve the…

Abstract

Purpose

This paper aims to study the sampling methods (or design of experiments) which have a large influence on the performance of the surrogate model. To improve the adaptability of modelling, a new sequential sampling method termed as sequential Chebyshev sampling method (SCSM) is proposed in this study.

Design/methodology/approach

The high-order polynomials are used to construct the global surrogated model, which retains the advantages of the traditional low-order polynomial models while overcoming their disadvantage in accuracy. First, the zeros of Chebyshev polynomials with the highest allowable order will be used as sampling candidates to improve the stability and accuracy of the high-order polynomial model. In the second step, some initial sampling points will be selected from the candidates by using a coordinate alternation algorithm, which keeps the initial sampling set uniformly distributed. Third, a fast sequential sampling scheme based on the space-filling principle is developed to collect more samples from the candidates, and the order of polynomial model is also updated in this procedure. The final surrogate model will be determined as the polynomial that has the largest adjusted R-square after the sequential sampling is terminated.

Findings

The SCSM has better performance in efficiency, accuracy and stability compared with several popular sequential sampling methods, e.g. LOLA-Voronoi algorithm and global Monte Carlo method from the SED toolbox, and the Halton sequence.

Originality/value

The SCSM has good performance in building the high-order surrogate model, including the high stability and accuracy, which may save a large amount of cost in solving complicated engineering design or optimisation problems.

Details

Engineering Computations, vol. 35 no. 2
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 1 March 1996

Lance A. Matheson

In statistical process control, a number of items are selected from all items produced every h time units (which we will refer to as an inspection period); these items are…

2216

Abstract

In statistical process control, a number of items are selected from all items produced every h time units (which we will refer to as an inspection period); these items are used to make inferences about the state of an unreliable machine or process. This paper considers an unreliable process which can shift from an acceptable in‐control state to an unacceptable out‐of‐control state. Based on a Shewhart‐type c‐chart, this paper extends the framework developed in Klastorin et al. to define the expected number of samples needed to confirm that the process shift has occurred when we use a sequential sample of the last n items produced in an inspection period. Comparing this result to the case where a random sample is used, we show that the probability of detecting the shift using a sequential sample is greater than or equal to the probability of detecting the shift using a random sample. Thus, sequential samples will result in a control chart that requires fewer expected samples to detect a shift and has lower expected total costs.

Details

Benchmarking for Quality Management & Technology, vol. 3 no. 1
Type: Research Article
ISSN: 1351-3036

Keywords

Article
Publication date: 5 October 2015

Xiaoke Li, Haobo Qiu, Zhenzhong Chen, Liang Gao and Xinyu Shao

Kriging model has been widely adopted to reduce the high computational costs of simulations in Reliability-based design optimization (RBDO). To construct the Kriging model…

422

Abstract

Purpose

Kriging model has been widely adopted to reduce the high computational costs of simulations in Reliability-based design optimization (RBDO). To construct the Kriging model accurately and efficiently in the region of significance, a local sampling method with variable radius (LSVR) is proposed. The paper aims to discuss these issues.

Design/methodology/approach

In LSVR, the sequential sampling points are mainly selected within the local region around the current design point. The size of the local region is adaptively defined according to the target reliability and the nonlinearity of the probabilistic constraint. Every probabilistic constraint has its own local region instead of all constraints sharing one local region. In the local sampling region, the points located on the constraint boundary and the points with high uncertainty are considered simultaneously.

Findings

The computational capability of the proposed method is demonstrated using two mathematical problems, a reducer design and a box girder design of a super heavy machine tool. The comparison results show that the proposed method is very efficient and accurate.

Originality/value

The main contribution of this paper lies in: a new local sampling region computational criterion is proposed for Kriging. The originality of this paper is using expected feasible function (EFF) criterion and the shortest distance to the existing sample points instead of the other types of sequential sampling criterion to deal with the low efficiency problem.

Details

Engineering Computations, vol. 32 no. 7
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 6 November 2017

Leshi Shu, Ping Jiang, Li Wan, Qi Zhou, Xinyu Shao and Yahui Zhang

Metamodels are widely used to replace simulation models in engineering design optimization to reduce the computational cost. The purpose of this paper is to develop a…

Abstract

Purpose

Metamodels are widely used to replace simulation models in engineering design optimization to reduce the computational cost. The purpose of this paper is to develop a novel sequential sampling strategy (weighted accumulative error sampling, WAES) to obtain accurate metamodels and apply it to improve the quality of global optimization.

Design/methodology/approach

A sequential single objective formulation is constructed to adaptively select new sample points. In this formulation, the optimization objective is to select a sample point with the maximum weighted accumulative predicted error obtained by analyzing data from previous iterations, and a space-filling criterion is introduced and treated as a constraint to avoid generating clustered sample points. Based on the proposed sequential sampling strategy, a two-step global optimization approach is developed.

Findings

The proposed WAES approach and the global optimization approach are tested in several cases. A comparison has been made between the proposed approach and other existing approaches. Results illustrate that WAES approach performs the best in improving metamodel accuracy and the two-step global optimization approach has a great ability to avoid local optimum.

Originality/value

The proposed WAES approach overcomes the shortcomings of some existing approaches. Besides, the two-step global optimization approach can be used for improving the optimization results.

Details

Engineering Computations, vol. 34 no. 8
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 1 January 1962

GREAT BRITAIN will find 1962 to be a year of grave decisions. The negotiations for our entry into the Common Market will reach a climax. Wages and prices hang like a grim…

Abstract

GREAT BRITAIN will find 1962 to be a year of grave decisions. The negotiations for our entry into the Common Market will reach a climax. Wages and prices hang like a grim question mark over the future. These are only two of the many problems calling for the right solutions. Members of every political party, industrialists and trades union leaders, friends and foes of the Common Market are agreed on one point. Much keener competition is inevitable and upon our success in it depends this country's future.

Details

Work Study, vol. 11 no. 1
Type: Research Article
ISSN: 0043-8022

Article
Publication date: 18 December 2009

Marvin Rothwell, Eui Park and Daebeom Kim

The reduction of the time and resources spent inspecting product is critical to the success of Company L's continued resourcing efforts. The use of Mil‐Std and other…

1236

Abstract

The reduction of the time and resources spent inspecting product is critical to the success of Company L's continued resourcing efforts. The use of Mil‐Std and other sampling plans with acceptance numbers greater than zero usually results in increased inspection sizes and potential for controversy in inspection results between inspectors. The time and resources used to complete these outgoing inspections are directly related to the amount of product currently required to be inspected in order to determine the acceptance or rejection of a lot of finished goods. This paper proposes a new sampling policy that will allow Company L to reduce the size of outgoing inspections. The data used in the paper are from 2006 to 2007. It is a combination of Overseas Inspection reports from all suppliers as well as sales volumes for products sold to Company L's partner companies. There are currently over 80 suppliers that manufacture products for Company L. The major finding of this paper is that it is possible to reduce inspection size while still maintaining, or in most cases reducing, the risks associated with sample inspections. This will be accomplished by switching from the current Mil‐Std plan to a Zero acceptance number sampling plan.

Details

Asian Journal on Quality, vol. 10 no. 3
Type: Research Article
ISSN: 1598-2688

Keywords

Article
Publication date: 8 November 2018

Amos H.C. Ng, Florian Siegmund and Kalyanmoy Deb

Stochastic simulation is a popular tool among practitioners and researchers alike for quantitative analysis of systems. Recent advancement in research on formulating…

Abstract

Purpose

Stochastic simulation is a popular tool among practitioners and researchers alike for quantitative analysis of systems. Recent advancement in research on formulating production systems improvement problems into multi-objective optimizations has provided the possibility to predict the optimal trade-offs between improvement costs and system performance, before making the final decision for implementation. However, the fact that stochastic simulations rely on running a large number of replications to cope with the randomness and obtain some accurate statistical estimates of the system outputs, has posed a serious issue for using this kind of multi-objective optimization in practice, especially with complex models. Therefore, the purpose of this study is to investigate the performance enhancements of a reference point based evolutionary multi-objective optimization algorithm in practical production systems improvement problems, when combined with various dynamic re-sampling mechanisms.

Design/methodology/approach

Many algorithms consider the preferences of decision makers to converge to optimal trade-off solutions faster. There also exist advanced dynamic resampling procedures to avoid wasting a multitude of simulation replications to non-optimal solutions. However, very few attempts have been made to study the advantages of combining these two approaches to further enhance the performance of computationally expensive optimizations for complex production systems. Therefore, this paper proposes some combinations of preference-based guided search with dynamic resampling mechanisms into an evolutionary multi-objective optimization algorithm to lower both the computational cost in re-sampling and the total number of simulation evaluations.

Findings

This paper shows the performance enhancements of the reference-point based algorithm, R-NSGA-II, when augmented with three different dynamic resampling mechanisms with increasing degrees of statistical sophistication, namely, time-based, distance-rank and optimal computing buffer allocation, when applied to two real-world production system improvement studies. The results have shown that the more stochasticity that the simulation models exert, the more the statistically advanced dynamic resampling mechanisms could significantly enhance the performance of the optimization process.

Originality/value

Contributions of this paper include combining decision makers’ preferences and dynamic resampling procedures; performance evaluations on two real-world production system improvement studies and illustrating statistically advanced dynamic resampling mechanism is needed for noisy models.

Details

Journal of Systems and Information Technology, vol. 20 no. 4
Type: Research Article
ISSN: 1328-7265

Keywords

Article
Publication date: 1 August 1967

THE British Motor Corporation has taken an important step in setting up a new centre to give a thorough training in modern management and techniques to many of its own…

Abstract

THE British Motor Corporation has taken an important step in setting up a new centre to give a thorough training in modern management and techniques to many of its own people. Of course, Haseley Manor, the Corporation's staff college for almost ten years, has done much to weld together the constituent companies which make up the parent body and it created a climate of good management during a period of rapid growth.

Details

Work Study, vol. 16 no. 8
Type: Research Article
ISSN: 0043-8022

Article
Publication date: 1 August 1966

INCENTIVE schemes are used by five‐sixths of British industry and at least a third of them are based on false values. Yet in general managements are satisfied with their…

47

Abstract

INCENTIVE schemes are used by five‐sixths of British industry and at least a third of them are based on false values. Yet in general managements are satisfied with their schemes and have no desire to change them. That is only one of the startling findings in the Survey on Incentive Payments which its Industrial Engineering Committee has carried out for the Institution of British Managers.

Details

Work Study, vol. 15 no. 8
Type: Research Article
ISSN: 0043-8022

Article
Publication date: 1 December 2004

Paurav Shukla

The study addresses the effect of product usage, satisfaction derived out of the same and the brand switching behaviour in several product categories while looking at the…

5894

Abstract

The study addresses the effect of product usage, satisfaction derived out of the same and the brand switching behaviour in several product categories while looking at the product involvement level in the Indian marketplace. A fair amount of work has been done in the area of customer satisfaction and loyalty and many customer satisfaction indexes are available in the market using different variables and characteristics. The study attempts to understand the brand switching behaviour of the customers and its relation not with just satisfaction derived out of the product but also connects to the usage pattern of the customers and product involvement. Five categories (vehicles, television, soap, hair oil, and ice cream), involving varying levels of involvement were chosen. Cluster analysis was used to understand the grouping of the characteristics across the categories and their effect on brand switching behaviour in correlation with satisfaction and involvement level. It was observed that product usage and related level of satisfaction fail to explain the brand switching behaviour. Product involvement was found to have moderate impact on readiness to switch. The study emphasises that marketers will have to keep a constant eye to understand the usage pattern associated with their products and the satisfaction derived out of it and also at how customers involve themselves with the product to lessen the brand switching behaviour among their customers.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 16 no. 4
Type: Research Article
ISSN: 1355-5855

Keywords

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