A Statistical Solution to Mitigate Functional Requirements Coupling Generated from Process (Manufacturing) Variables Integration-part 2: A Case Study on Clarifying the Effect of Process (Manufacturing) Variables Integration on Functional Requirements Inde

In this part of the work, to illustrate the strength of the “partial and semipartial correlation analysis, as the proposed solution described in detail in part 1, we consider design problem of the manufacturing system of a given product based on a set of hypothetical data and show how to explore the most appropriate integration choices in which the (causal) dependencies of the concerned PVs are minimal. Based on the results of this study, we emphasize that incorporating the identified sensitive PVs into the integration process will eventually lead to coupling among a subset of the product's FRs and isolation of these PVs is recommended as an ideal solution. However, sometimes, in the real world, for some of logical and/or technical reasons; such an ideal solution might be impossible. To deal with such a dichotomy, we use the Design of Experiments (DOE) methodology and offer the idea of controlling the values of the concerned PVs at specific levels to find the most appropriate condition (s) under which the minimal (causal) correlation between the integrated PVs may be achievable. On the basis of this idea, the worthwhile information the manufacturing system designers require to detect the safe levels at which the PVs can be integrated is achievable.