An Analysis and Study of the Cost of Quality of Innovation in an Industrial Environment

Abstract

The current work presents four different studies: an extensive literature review, a model replication, calibration and correction, and the individual evaluation of two different technological approaches to improve quality via the implementation of six sigma projects and industrial robots. The first study includes the results of several systematic literature reviews and identifies R&D, one innovation precursor, is missing in the most extensive list of costs that compose the cost of quality (COQ) framework. This review establishes that some previous theoretical R&D approaches that should be considered as a defect prevention (P) cost, an important element in the COQ composite. A by-product of such literature review is the identification of a firm’s COQ simulation model that is based on System Dynamics (SD) technology. In the same vein, two technological archetypes were identified to work as R&D proxies to be later adapted to SD modeling. Another byproduct of the literature review is the identification of two design of experiment (DOE) types, their regression model, and the most apposite technique to estimate an optimum value from each regression model’s response variable given certain control variables. The second study replicates the SD-based COQ simulation model while adding details typically omitted; latent variables, least squares, and surface response optimization. The third and fourth studies involve using the SD-modeled technological archetypes (a six-sigma project and an industrial robot) to test their isolated effects as well as additive effects when combined with traditional investments in P on a quality system’s (QS) profitability. The quality system is represented by the replicated, calibrated and corrected SD simulation environment. Such experimentation took place via the two identified DOEs and their respective most ad-hoc optimization techniques to see which combination of investments in prevention, appraisal, and R&D events maximize the QS’ profit net present value (NPV). These two studies’ results provide initial but robust evidence supporting the hypothesis that R&D must be included as part of the prevention activities in the COQ framework. Not doing so, may lead to the loss of several million USD per year in opportunity costs (L). Such L may represent from 70 to 300% of the simulated firm’s profit NPV under common investments in P.