A model for improving the applicability of design methodologies to mechanical engineering design routines

Schmitt, Sebastian; Scheitza, Matthias; Groche, Peter

doi:10.1080/09544828.2015.1048198

Cited by 4 publications

(6 citation statements)

References 25 publications

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“…Kreye et al (2012) define uncertainty as a "potential deficiency in any phase or activity of the process which can be characterized as not definite, not known or not reliable". Uncertainty has a substantial effect on how people act during engineering design work (Cash and Kreye 2018;Christensen and Ball 2017), and can negatively impact NPD performance by making activities and decisions more challenging (Blauth, Mauer, and Brettel 2014;Chalupnik, Wynn, and Clarkson 2013;Schmitt, Scheitza, and Groche 2015).…”

Section: Introductionmentioning

confidence: 99%

Exploring the link between uncertainty and project activities in new product development

Lasso

Kreye

Daalhuizen

et al. 2020

Journal of Engineering Design

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Uncertainty is central to engineering design and New Product Development (NPD). While there has been substantial focus on dealing with uncertainty in technical systems and design information, how engineering designers react to and manage uncertainty is also critical to performance. However, an important gap remains in understanding what activities NPD teams engage in based on the specific uncertainty types they face. This gap is investigated via a conceptual framework detailing four uncertainty types (technical, organisational, resource and market) and three project activities (information, knowledge sharing and representation). Evidence is presented from two engineering design cases with 45 interviews, observations, and secondary data. Based on this, specific links are described between uncertainty type and project activity as follows: technical uncertainty drove representation activity, organisational uncertainty drove knowledge sharing activity, resource uncertainty drove knowledge sharing activity, and market uncertainty drove information activity. These findings are developed into a number of propositional relationships between the four uncertainty types and specific project activities, which form the basis for a number of implications for engineering design research and practice.

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Section: Introductionmentioning

confidence: 99%

Exploring the link between uncertainty and project activities in new product development

Lasso

Kreye

Daalhuizen

et al. 2020

Journal of Engineering Design

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“…In addition to VDI 2221, Birkhofer [40] gives a detailed overview of the design development that has taken place so far. However, the existing methods with their sequential structure do not represent real design processes [242], because they do not explicitly capture the iterative steps of product development.…”

Section: Peter Groche and Maximilian Knollmentioning

confidence: 99%

“…In consultation with the internal stakeholder group product realisation, the properties must be compared with customer requirements and wishes. [241,242] Based on the solutions developed in the Product Realisation department, the design unit prepares the decision-making process for the Product Realisation stakeholder group [241].…”

Section: Peter Groche and Maximilian Knollmentioning

confidence: 99%

“…Developing a method that extends the system boundaries of the design process to internal and external influences seems promising to update established approaches and move towards a dynamic, closed-loop system [242]. Therefore, the discussed method is based on specific participants in the product development process and their activities and responsibilities.…”

Section: Peter Groche and Maximilian Knollmentioning

confidence: 99%

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Methods and Technologies for Mastering Uncertainty

Groche

Abele

Groche

et al. 2021

Springer Tracts in Mechanical Engineering

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Uncertainty affects all phases of the product life cycle of technical systems, from design and production to their usage, even beyond the phase boundaries. Its identification, analysis and representation are discussed in the previous chapter. Based on the gained knowledge, our specific approach on mastering uncertainty can be applied. These approaches follow common strategies that are described in the subsequent chapter, but require individual methods and technologies. In this chapter, first legal and technical aspects for mastering uncertainty are discussed. Then, techniques for product design of technical systems under uncertainty are presented. The propagation of uncertainty is analysed for particular examples of process chains. Finally, semi-active and active technical systems and their relation to uncertainty are discussed.

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“…For developing new products, different guidelines, methods, algorithms, and suggestions are available in the literature [1][2][3][4]. According to Kaldate et al [1] matrix methods such as House of Quality are the first step in relating product attributes to engineering parameters.…”

Section: Introductionmentioning

confidence: 99%

Determination of coefficient of friction for a novel bed mechanism

Andhare

Onkar

2021

Eng. Res. Express

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In all the mechanical systems it is important to know the amount of friction and the actual torque required to drive the system. In this context, this manuscript discusses a simple, practical approach for estimating the coefficient of friction and the operating torque in a mechanism used for a novel bed with commode. The commode is brought in useable position by a mechanism which moves the bed platform down and then horizontally away from the commode opening and vice versa. This article presents the design of platform mechanism, estimation of operating torque using a specially designed setup and calculation of the coefficient of friction using basic mechanics. The results show that the coefficient of friction in the mechanism decreases with increase in the load on it. A mean value of coefficient of friction of 0.2396 is estimated from the trials. Calculating the torque to operate the mechanism using the mean value of friction results in some error in the torque values and the error is within 10% of the actual values. Thus, the mean coefficient of friction can be used conveniently for estimating the torque in this mechanism. This friction and torque estimation will be useful for determination of crank sizes for manual turning of screw and motor rating for automatic operation of the mechanism. RECEIVED

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A model for improving the applicability of design methodologies to mechanical engineering design routines

Cited by 4 publications

References 25 publications

Exploring the link between uncertainty and project activities in new product development

Exploring the link between uncertainty and project activities in new product development

Methods and Technologies for Mastering Uncertainty

Determination of coefficient of friction for a novel bed mechanism

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