Tag Archives: Factorial Indices and Regression Models.

Determination of Combined Effects of Factors that Affect Performance Operatives in Manufacturing Industries, Using Minitab (Published)

This research work determines the degree of impact of some factors in their combined state and interactions effects on the performance of operatives (manufacturing workers) in manufacturing industries. Factors studied include: motivation, power, safety, maintenance, training, equipment and technology. Eighty-two manufacturing workers drawn from thirteen manufacturing Plastic Companies were used. Data were collected using work measurement technique (time studies) and questionnaire (tests studies). Software is used for the various analyses in the study. The software used was Minitab. Software tools used for various analyses in the study are: statistics, correlation, polynomial regression and response surface regression, while t – value, F- ratio, p – values, effect coefficient and variance of inflation factors (VIF) were used to test the hypotheses.  Results from the various statistical analyses were presented, studied and interpreted. The results showed that the identified factors have impact on the performance of the manufacturing workers in the plastic manufacturing industries. The fall in performance of manufacturing workers in plastic industries is due to these cumulative effects of factors. The magnitude of these effects of the combined and interactions on performance are 42.57% ( 0.15), 43.67% ( 0.1) and 43.67% ( 0.05). The effect reduces as confidence interval increases above 90%. The correlation coefficients of the factors to performance are all showing positive linear effects while the regression model coefficients some show negative effects. The models developed in quadratic shape factor are valid in predicting performance and their combined and interactions effects apparently providing information for controlling problems arising in manufacturing workers performance in industries in the South Eastern Nigeria and any other placeThis research work determines the degree of impact of some factors in their combined state and interactions effects on the performance of operatives (manufacturing workers) in manufacturing industries. Factors studied include: motivation, power, safety, maintenance, training, equipment and technology. Eighty-two manufacturing workers drawn from thirteen manufacturing Plastic Companies were used. Data were collected using work measurement technique (time studies) and questionnaire (tests studies). Software is used for the various analyses in the study. The software used was Minitab. Software tools used for various analyses in the study are: statistics, correlation, polynomial regression and response surface regression, while t – value, F- ratio, p – values, effect coefficient and variance of inflation factors (VIF) were used to test the hypotheses.  Results from the various statistical analyses were presented, studied and interpreted. The results showed that the identified factors have impact on the performance of the manufacturing workers in the plastic manufacturing industries. The fall in performance of manufacturing workers in plastic industries is due to these cumulative effects of factors. The magnitude of these effects of the combined and interactions on performance are 42.57% ( 0.15), 43.67% ( 0.1) and 43.67% ( 0.05). The effect reduces as confidence interval increases above 90%. The correlation coefficients of the factors to performance are all showing positive linear effects while the regression model coefficients some show negative effects. The models developed in quadratic shape factor are valid in predicting performance and their combined and interactions effects apparently providing information for controlling problems arising in manufacturing workers performance in industries in the South Eastern Nigeria and any other place

Keywords: Factorial Indices and Regression Models., Industries, Manufacturing Workers, Performance