Measuring process control automation benefits through a human-machine function allocation analysis

Abstract

Often technology is introduced into manufacturing and process control environments to partially automate tasks too complex to fully automate. However, it is not always clear how to measure the benefits of such projects. More often than not, automation eliminates but also shifts human work, and broad productivity measures can fail to capture such changes. To this end, this effort describes a manufacturing case study that looks at human-machine allocation metrics involving a laboratory fermentation unit upgrade. Using a workflow monitoring and function allocation analytic approach, it was determined that upgrading an older microbial culture bioreactor (fermentor) to a new design with intelligent monitoring capabilities resulted in an approximate 17% reduction in dedicated human supervision. This workload reduction allowed scientists to spend less time on repetitive tasks and more time concentrating on other, more open-ended problems that require more expertize. However, the new technology increased human efforts across other functions, suggesting potential mitigation paths for future technology development. This effort illustrates that the impact of new technology on human-machine tasking can be quantified through a function allocation analysis and also provide diagnostic information, both of which are critical in understanding any overall added benefit of intelligent systems.