Determination of factors affecting the learning rate of workers in the food processing industry

Date

6-2016

Degree

Bachelor of Science in Industrial Engineering

College

College of Engineering and Agro-Industrial Technology (CEAT)

Adviser/Committee Chair

Josefa Angelie D. Revilla

Abstract

Labor as one of the most exploited job in developing countries should be given focus. The evaluation of workers in the manufacturing industry through the use of learning curve has been a great tool in observing workers' performance. Most industries have an established learning rate which is used in estimating the performance level of workers depending on the number of units produced. Nevertheless the food processing industry has not been able to use the learning curve in evaluating workers. The objective of the study is to identify the factors that significantly affect the learning rate of workers in the food processing industry. Two performance factors -length of stint and degree of complexity, and two worker-related factors- age and experience were identified. Gender was also considered but it was found that like any other industry, it is not gender-biased. Length of stint is the length of continuous performance from the point of hiring to the point of data collection. Degree of complexity is the rank of the processes considered based on how difficult they are relative to others. Age and experience are the characteristics of a worker considered. It was found that length of stint, age, and experience were significant factors having a negative correlation with learning rate. Gender was proven insignificant. The model developed in the study returned an R² value of 65.46% which suggests that half of the variability in learning state is determined by the significant factors. Lastly, the study yielded an absolute error of 3.70% which indicates a reliable model.

Language

English

Location

UPLB College of Engineering and Agro-Industrial Technology (CEAT)

Call Number

LG 993.5 2016 E66 /M38

Document Type

Thesis

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