Metamodel-driven design optimization using integrative graphical design interfaces: Results from a job-shop manufacturing simulation experiment

Today, engineers are relying more on modern computer tools and techniques to visualize complex data sets; however, few studies have examined the effect of fast, graphical design interfaces on user performance during system design. The objective in this paper is to extend our previous findings in this area by examining the impact of fast, graphical design interfaces on design efficiency and design effectiveness within the context of a job-shop design problem. We accomplish this by investigating the effect of an artificial response delay, intended to mimic computationally intensive analyses, on user performance. Experimental results indicate that user performance deteriorates significantly when a small response delay of 1.5 s is introduced: percent error and task completion time increase, on average, by 9.4% and 81 s, respectively, when the delay is present. The use of first-order, stepwise, and second-order polynomial regression models for approximating the system responses (outputs) is also investigated, and user performance is found to improve when stepwise polynomial regression models are used instead of first- or second-order models. The stepwise models yielded 12% lower error and 91 s faster completion times, on average, over the first-order models; error was 13.5% lower and completion time was 62 s faster, on average, than when second-order models were used. The results confirm our previous findings about the negative impact of response delay on task completion time while demonstrating that delay can also significantly decrease the efficacy of a metamodel-driven graphical design interface.