Investigating the Impact of Ergonomic Injury Risk on Productivity and Quality

Goals

Formulate a stochastic method to demonstrate a measurable correlation between an ergonomic intervention and its subsequent effects on work productivity and quality.

Objective

Ergonomic interventions are sometimes difficult to justify from a direct cost-savings standpoint. This is due to several factors, the primary one being focused on injury-related parametric data, which tend to be lagging indicators (e.g., lack of an immediate improvement in injury rates). Also, and importantly, focus on injury reduction alone tends to cloud the positive impact that ergonomic programs and subsequent interventions have on worker productivity and quality-related metrics (e.g., frequency of non-conformance).

From earlier evidence, it can be argued that there exists a measurable correlation between an ergonomic intervention and its subsequent effect on productivity and quality. From a proactive perspective, such relationships are of value, as they could be used to predict the potential cost/benefit of an intervention prior to any capital investments.

The purpose of this research effort is to establish a preliminary step toward the formulation of a stochastic method if such relationships exist. A stochastic method will then enable probabilistic estimates of quality and productivity improvements based on the potential impact of an ergonomic intervention.

Approach

A laboratory-based study involving a series of simulated tasks will be used to develop correlational models between improvements in ergonomics and subsequent effects in regards to quality and productivity in typical aerospace manufacturing environments. A multifactorial repeated measure design will be used to generate a range of ergonomic risk levels.  Ergonomic risk for each task will be quantified by using risk assessment techniques that are commonly used by ergonomic practitioners. For each test configuration, ergonomic risk scores will be recorded as experienced by each participant, and worker performance will be quantified regarding its quality and productivity.