The continuous integration and verification of components is essential in distributed design processes. Identifying the optimal integration and verification frequency, however, can be challenging due to the complexity of product development. Especially the effect of human decision-making in partially isolated development scenarios is difficult to consider. Thus, we performed an experimental study based on the following three steps: first, an extension of the existing parameter design framework, which is used to conduct experiments under laboratory conditions, in which human subjects solve quantitative surrogate design tasks. Second, a series of experiments in which 32 subjects divided into groups of two solved 229 parameter design tasks with a varying integration and verification frequency. And, third, a statistical analysis of the results with respect to development time, coupling strength and process costs. According to our results, development time can be reduced by up to 71%, if the integration and verification frequency is doubled. If process costs are also considered, the optimal frequency can be subject to a conflict of goals between reducing development time and minimising process cost.
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The continuous integration and verification of components is essential in distributed design processes. Identifying the optimal integration and verification frequency, however, can be challenging due to the complexity of product development. Especially the effect of human decision-making in partially isolated development scenarios is difficult to consider. Thus, we performed an experimental study based on the following three steps: first, an extension of the existing parameter design framework,...
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