ABSTRACT
Industrial innovation and advancement owe their sustainable foundation to some measurement scale (Badiru 2008). We must measure work before we can improve it as part of the evaluation of human performance (Wilson and Corlett 2005). This conveys the importance of work measurement in industry, business, and government. Productivity is the battle cry of industry, but what is not measured cannot be improved. Thus, work measurement should be a key strategy for productivity measurement. The following quote provides an inspirational foundation for the pursuit of work measurement activities, both from the standpoint of research and that of applications:
Introduction ............................................................................................................ 349 Effect of Learning .................................................................................................. 350 Univariate Learning Curve Models ........................................................................ 351 Log-Linear Model .................................................................................................. 351 Multivariate Learning Curve Model ...................................................................... 353 Model Formulation ................................................................................................ 354 Bivariate Model ...................................................................................................... 354 Comparison with Univariate Model .......................................................................360 Potential Applications ............................................................................................ 361 Impact of Multivariate Learning Curves ................................................................364 Conclusion .............................................................................................................364 References .............................................................................................................. 365
Aft (2010) suggests that the academic research of work measurement has realworld values and practical applications for industry. He summarizes that the standards obtained through work measurement help provide essential information for the successful management of an organization. Such information includes the following:
• Data for scheduling • Data for staf¥ng • Data for line balancing • Data for materials requirement planning • Data for wage payment • Data for costing • Data for employee evaluation
In each of these data types, the effect of learning in the presence of multiple factors should be taken into consideration for operational decision-making purposes.
