Case Study on the Assessment Effort of the Key Indicator Method for Awkward Body Postures (KIM-ABP)

This case study deals with the derivation of a necessary and sufficient analysis period for the practical application of the Key Indicator Method Awkward Body Posture (KIM-ABP). For the case study involving the de-icing of aircraft in open baskets, we chose a sample with an extreme working position for the deicers, involving continuous forced postures of the legs and torso (Sample A). This is therefore an extremely one-sided posture that workers must maintain for several hours per shift with very few opportunities to rest. It should therefore be expected that KIM-ABP would produce reliable results even with short observation times. To verify the KIM-ABP results, we used EAS as an alternative method (Sample B). Our working hypotheses for this case study are therefore: H1: With KIM-ABP, valid results for the risk areas are achieved after an observation period of 15 minutes. We speak of validity when the ergonomic assessment of forced postures is representative of the strain situation over an entire de-icing season. H2: If the 15-minute analysis period is divided into three randomly selected 5-minute observations, we expect the interquartile range (IQR) of all analysis results for Sample A to be small. Based on experience, we set IQR_max to 50. The influencing factors of the worker (e.g., height, gender), the technical and ergonomic design of the basket, the weather, the time of the day, the volume of traffic, the aircraft type, and the work organization all may have an impact on the KIM results. Since our case study focuses on the procedural economics of KIM-ABP compared to EAS, we kept these influencing factors constant through the study design. Both assessment methods used the same population. Likewise, there is no analyst bias, as a single, experienced analyst evaluated both methods. The problem of calculating values of central tendency and dispersion for classifications on an ordinal scale is addressed. Since the same analyst was used for sample A and sample B, learning effects can be ruled out. The IQR_max-criterion (H2) is violated in five of 13 analyses of Sample A. The standard deviations of KIM-ABP were 64.85 for sample A and 16.26 for sample B. The median absolute deviation (MAD) was 55.4 for sample A and 9.9 for sample B. This means that 15-minute KIM-observations per workstation are not sufficient to yield reliable results in relation to the more refined EAS values in our case study. Similarly, both the macro KIM-ABP method and the more refined EAS method do not allow for a conclusive clarification of the influences of the