Continual improvement in the insert machining process at a metalworking facility

  • Jorge Martínez ,
  • Ann Wellens
  • a,b Universidad Nacional Autónoma de México, Av. Universidad 3000, CDMX 04510, México
Cite as
Martínez J., Wellens A. (2021). Continual improvement in the insert machining process at a metalworking facility. Proceedings of the 33rd European Modeling & Simulation Symposium (EMSS 2021), pp. 220-223. DOI: https://doi.org/10.46354/i3m.2021.emss.030

Abstract

A certain metalworking company, leader in the manufacture and distribution of tools for the metallurgical industry, has had difficulties due to late deliveries and quality related problems in the powder metallurgy process. The areas with productivity problems are pressing and grinding, which present rework and, consequently, long process times and low throughput. This work describes the optimization of the manufacturing process of the inserts with the best sales in the company, and subsequent agent-based simulation, to determine the degree of improvement in the level of rework and the impact of the optimization. The simulation model was developed in Anylogic, considering raw materials and process machinery as agents, as well as additional elements such as transport trucks and inspection tables. As resources, the forklift and the process operators were considered.
The real contribution of this job was the possibility to analyze and demonstrate scenarios correspond to the state of the process before and after the improvement through a simulation and some statistical tools like Brainstorming, Ishikawa diagram, DOE (design of experiments) and a linear programing. The Productivity was found to be increased by 350% when using tungsten carbide powder with a density of 3.5 g/cm3, already agreed with the raw material supplier plants. Likewise, a correct allocation of personnel for the sandblasting operation, obtained through an integer programming model, leads to an improved productivity.

References

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  2.  Ilzarbe and Tanco (2008). Application of design of experiments (DOE) for process improvement, Magazine Engineering Research Report, 1 (6), 85–94