In this empirical study we are proposing to conduct a longitudinal, quantitative research design on a population of machines to test Hays’ (2022) theory that the Operating Equipment Effectiveness (OpEE®) score with a quality status indicator will increase productivity and reduce the associated cost of maintenance (CoM) through improving reliability (see Figure 1). In addition to this test, this paper will pursue answers to the research question whether firms using status indicator(s) will achieve more consistent and timely maintenance than firms using standard maintenance practices as measured by the established performance indicator OpEE®. The expected results will show that using a quality status indicator will significantly improve maintenance timeliness and consistency, which will improve overall productivity, and reduce the cost of maintenance. This study will provide a significant contribution to machine maintenance and productivity research by demonstrating a method to adopt quality status indicator(s) using sensors, the Internet of Things (IoT), and provide proactive maintenance strategies to optimize machine productivity in a variety of use cases and industries.