Abstract
The objective of this work is to adapt and test an agile methodology based on human observation that waives the data collection based on the timing of time in activity. Aiming to evaluate the productivity and non-productivity of workers in a factory during the pipe welding process for use in the construction of industrial plants. Through human observation the data was gathered by registering punctually the activities of the welders during a week. The results obtained by the Monte Carlo simulation were validated by comparing the results obtained by the probability and statistically analysis of the complete sample. After the simulation validation the Sensibility Analysis test was conducted in order to evaluate the variables of higher impact in the performance of the welders. The average of Labour Rating Factor and Idleness Rating Factor obtained by Monte Carlo simulation were respectively, 0.5529 and 0.4549 and by the sampling chart Labour Rating Factor 0.5552 and Idleness Rating Factor 0.4448. The methodology identified 9(nine) actions in the productive state, where the welding activity presents the greatest impact on the output of the mean of the Labour Rating Factor. In addition, 8(eight) actions were considered non-productive, where displacements and human conditions activities have the greatest impact on the Idleness Rating Factor. Furthermore, the results were compared with the work of other Authors. The research results shows the feasibility for industry to use this proposal of an agile methodology for evaluating the workforce performance, spending less resource compared with traditional ones.
Highlights
The performance evaluation and identification of factors that affect productivity in the heavy construction industry area is based mainly in the post-analysis of historical data
The agile methodology of data collection and treatment applied, allows the precise identification of the actions performed by the workers
It has proved to be an effective and simplified tool, allowing the registration of the degree of participation of all the events that make up the Labour and Idleness Rating Factors
Summary
The performance evaluation and identification of factors that affect productivity in the heavy construction industry area is based mainly in the post-analysis of historical data. The work productivity is fundamental information in order to estimate and monitor the deadlines of a construction project. Nowadays, in construction industry its estimative is based in productivity data of publications or in the experience of one or more individuals. In this sense, Song and AbouRizk (2008) affirm that, the historical data of projects maintain important. In the case of welders, which are the focus of this work, welding would be classified as a productive action and activities such as, changing the torch diffusor and regulating the welding machine, would be classified as auxiliary. On the other hand, when a worker isn’t doing anything or doing strange activities to the productive process, the action is classified as non-productive, e.g.: chatting with colleagues, drinking water and in unnecessary displacement
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