SME Productivity improve using six sigma and data mining tools

Authors

Pacora Cardozo, Jamblico

Rojas Polo, Jonatán Edward

Reyes Arteaga, Steffano

Cáceres Cansaya, Alexia

Flores Rojas, Luigi Alejandro

Benavente Sotelo, Renzo Alejandro

Abstract

This research project aims to ease SME process control by using DMAIC (Lean Six Sigma). Three topics were applied: Lean Six Sigma, Data Mining, and Augmented Reality. All of this is assisted by the most advanced technology to date. SMEs have small processes and this is why Lean Six Sigma was applied to detect problems, measure, analyze and control. The Poka-Yoke tool works as a link between Data Mining tools and Augmented Reality. The Data Mining tool is the deep learning neuronal net (with more than one hidden layer). The neuronal net will learn the gauges formula and will show results based on the measurements. This tool is related to Lean Six Sigma as the net will show optimal results with controlled processes only. Augmented Reality eases data input for the gauges. Input data will be transmitted through AR cards which will be scanned by Smartphones. These AR cards become unique through the use of the Poka-Yoke tool The expected savings are S/. 6120. The project obtains an NPV of S/. 7811 and a COK of 15.24% which is enough to demonstrate the viability of the project.