Statistical Analysis and Data Envelopment Analysis to Improve the Efficiency of Manufacturing Process of Electrical Conductors

The main focus of this research was to develop an approach using statistical tools and Data Envelopment Analysis (DEA) to tackle productivity measurements and benchmarking problems in the electrical conductor manufacturing environment. A tooling efficiency study was carried out with a nozzle used for the manufacture of 23-A WG wires. The efficiency of five types of tooling, four non-Mexican-manufactured types and one Mexican-manufactured type, were compared. Analysis of Variance (ANOVA) and the Tukey test were applied. Six factors influencing the performance of the tooling during the manufacturing process were considered: productivity, quality, time, machine, operator, and color of the insulating material, with a focus on the efficiency of the tooling die-nozzle. The results demonstrated that two die-nozzle models exhibited the best performance; one was the Mexican model, surpassed by a non-Mexican model, with a capability process index Cpk = 1.26 indicating superior performance for the 3DND die-nozzle according to the statistical analyses performed. Subsequently, a super-efficiency DEA model of inputs-oriented with non-decreasing returns to scale (NDRS) corroborated the statistical results, representing an innovative combination of techniques for knowledge in manufacturing processes of electrical conductors. Input data were obtained from a manufacturer of electrical conductors serving the automotive sector in Querétaro City, Mexico.