Product Design Time Forecasting by Kernel-Based Regression with Gaussian Distribution Weights

Shang, Zhigen; Yan, Hong‐Sen

doi:10.3390/e18060231

Cited by 4 publications

(3 citation statements)

References 35 publications

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“…Questionnaires, interviews and brainstorming are common approaches to identifying IF's from the perspective of experts in industry. Shang & Yan (2016) suggest a method which has been developed to overcome small samples and heteroscedastic noise found in design time forecasting. This method identifies IF's (referred to as time factors and engineering characteristics) through self-administered questionnaires, based on a survey-based methodology.…”

Section: Methods That Identify Factorsmentioning

confidence: 99%

A Matter of Factor: A Proposed Method for Identifying Factors that Influence Design Effort Levels in Product Design

Holliman¹,

Thomson²,

Hird³

et al. 2019

Proc. Int. Conf. Eng. Des.

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Design effort, the amount of time required to complete a project or task (Salam et al., 2009; Salam and Bhuiyan, 2016), is a required resource for any design project which can be influenced by a number of factors. Estimating design effort is a significant challenge that can be mitigated through an understanding of these influential factors. This understanding is held as tacit knowledge by experts, earned through experience; yet, although these factors vary in type and impact, understanding their details can provide insight and improve future estimations. Some previous methods to estimate design effort identify these factors, either from: expert opinion, or historical data analysis with each approach has advantages and disadvantages.This paper is comprised of three parts:A review of published methods and tools for estimating product design effort and whether they consider and identify influential factors; an analysis of possible trends in the identification of factors influencing product design project length; and a new method for identifying the influential factors of product design project length.

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Section: Methods That Identify Factorsmentioning

confidence: 99%

A Matter of Factor: A Proposed Method for Identifying Factors that Influence Design Effort Levels in Product Design

Holliman¹,

Thomson²,

Hird³

et al. 2019

Proc. Int. Conf. Eng. Des.

View full text Add to dashboard Cite

show abstract

“…Some, like Wang et al (2015) and Pollmanns et al (2013) use variations on artificial neural networks as part of their analysis. The second engages with experts to collect their insight into factors, typically through interviews or brainstorming, such as those by Benedetto et al (2018) and Shang & Yan (2016). The final means of identifying factors is through literature review.…”

Section: Approaches To Estimate Design Effort In Product Designmentioning

confidence: 99%

Estimating Design Effort Needs of Product Design Projects Using Captured Expert Knowledge – A Proposed Method

2021

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The quick and accurate estimation of design effort can be make or break for all but the largest of product design consultancies. Traditional design project planning see designers being taken away from the metaphorical drawing board to spend time assessing project briefs and estimating workloads. Typically these designers base these estimates on their tacit knowledge and experience, and for the most part, they are accurate. However, this is time-consuming and therefore (indirectly) costly, as time spent planning, is not time spent designing. Many more sophisticated approaches for estimating design effort have been developed, but many require large bodies of past data and sophisticated analysis, such as artificial neural networks; and others have highly-specific use cases.This paper proposes a new method to develop a design effort estimation tool for product design consultancies. This method captures the tacit knowledge and experience of design team members and the tool replicates it quickly and effectively; graphically modelling factors that influence design effort needs in product design projects.

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“…Allowing for overlapping and iteration between or among design activities in concurrent product development, Yan et al(2010) built a time-computing model to estimate the rework cost and completion time of each of the activities and develop an optimization algorithm to minimize the development completion time under the constraint of the given rework cost budget. In view of small samples and heteroscedastic noise in the estimation of product design time, Shang and Yan (2016) proposed a kernel-based regression with Gaussian distribution weights (GDW-KR) to improve the estimation accuracy. In response to this problem, Yan and Shang (2019) also proposed relative entropy kernel regression (REKR) based on the combination of kernel-based regression and Gaussian margin machines (GMM) to pre-estimate product design time.…”

Section: Literature Reviewmentioning

confidence: 99%

An intelligent pre-estimation method of design time for complex products based on v-SVM

Zheng

2020

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Purpose Improving the prediction accuracy of design time for complex products is significant for improving the accuracy of product development and control plans. The purpose of this study is to propose an intelligent pre-estimation method of design time for complex products based on v-SVM. Design/methodology/approach First, an evaluation model for designer knowledge abilities based on v-SVM is built, which considers the fuzziness and dynamics of designer knowledge abilities. Next, a pre-estimation method for the design time of complex products based on v-SVM is built. This method takes into account the impacts of designer knowledge abilities and design task characteristics on the design time. Then, an adaptive genetic algorithm is programmed to optimize the parameters in the evaluation model and the pre-estimation method. Finally, a practical application and comparative analysis of the proposed pre-estimation method is suggested to verify the validity and applicability of this research. Findings First, the evaluation of designer knowledge abilities is a prediction problem that is both fuzzy and multivariate time series. Second, the pre-estimation of design time is a problem that is fuzzy and multivariate. Third, the pre-estimation accuracy of the proposed method is higher when compared with traditional methods. Originality/value This paper presents an intelligent pre-estimation method of design time for complex products. Unlike previous research, the pre-estimation method takes into account the impacts of both the designer knowledge abilities and the design task characteristics on the design time.

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Product Design Time Forecasting by Kernel-Based Regression with Gaussian Distribution Weights

Cited by 4 publications

References 35 publications

A Matter of Factor: A Proposed Method for Identifying Factors that Influence Design Effort Levels in Product Design

A Matter of Factor: A Proposed Method for Identifying Factors that Influence Design Effort Levels in Product Design

Estimating Design Effort Needs of Product Design Projects Using Captured Expert Knowledge – A Proposed Method

An intelligent pre-estimation method of design time for complex products based on v-SVM

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