A Theoretical Framework About the Impact of Human Factors on Manufacturing Process Performance

  • Arredondo-Soto K
  • Carrillo-Gutiérrez T
  • Solís-Quinteros M
  • et al.
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Abstract

The processes developed in manufacturing enterprises are evaluated permanently by different key performance indicators (KPI) to measure their competitiveness. Some of these KPI come from various approaches as the economic, environmental, and social under a sustainable perspective. Within the economic dimension are used indicators such as process time, level of product quality, on-time delivery to the customer, and cost per hour of production. For the environmental dimension, it is assessed the environmental impact in the form of gaseous emissions, solid waste and energy consumption, this is due to incentives and government regulations and the opportunity to reduce costs generated by their irrational use. Similarly, the social dimension has been valued through the recurrent indicator of the number of accidents. The purpose of this chapter is to provide a theoretical framework of how the human factor, since the social, economic, and environmental dimension, affects the productivity; as well as the indicators commonly used in the measurement of performance, the variables that are considered in its measurement and the way companies innovate processes to obtain competitive advantages of this factor. That is why the Toyota Production System (TPS), the Ford Production System (FPS), and the Caterpillar Production System (CPS) are analyzed and contrasted as referents to world class because of maintaining the best production practices. Finally, it aims to highlight the future trends in its consideration to evaluate the overall performance of the organizations, this with the aim to highlight those factors that have a positive effect on strengthening the competitiveness of enterprises.

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Arredondo-Soto, K. C., Carrillo-Gutiérrez, T., Solís-Quinteros, M., & Hernández-Escobedo, G. (2018). A Theoretical Framework About the Impact of Human Factors on Manufacturing Process Performance (pp. 327–352). https://doi.org/10.1007/978-3-319-56871-3_16

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