Maintenance human factors in the South African electricity transmission industry

Abstract

The introduction of Industry 4.0 highlights a strong focus on the social dimensions within Maintenance 4.0. Highly skilled staff will be required to interpret data analytics, perform smart work procedures and do maintenance planning with a systems perspective. Maintenance performance measurements have always reflected the changes in industry and maintenance revolutions. To enable the move to Maintenance 4.0, a clear strategy will be needed to include these social dimensions into a maintenance performance measurement framework.

Theory on maintenance human factors are mainly based in the aviation sphere. It focusses on training managers, supervisors and accident investigators to identify and mitigate maintenance human factors that can lead to severe and fatal accidents. Significant maintenance human factors outside of the aviation sphere are rarely studied. Literature on how these maintenance human factors should be measured and incorporated into maintenance performance measurement frameworks has been greatly neglected. This thesis aims to address these shortcomings.

The aim of this thesis was to determine measurements for maintenance human factors, that when applied to a maintenance measurement framework, will have a significant impact to improve both maintenance performance, reduce maintenance errors and the maintenance technician’s mental state. It additionally aimed to expand the body of knowledge on maintenance human factors to include the South African electricity transmission industry.

To achieve the inclusion of significant maintenance human factors into a maintenance performance measurement framework, possible measurements had to be determined for each maintenance human factor. This was done through an explorative literature review that applied to all industries. To determine the most mentioned maintenance human factors, a systematic literature review was done. The outcome of the systematic literature was used as a starting point for data collected from maintenance technicians within the South African electricity transmission industry.

High workload, time pressure, fatigue and communication were found to have the most significant impact on personal maintenance errors made from maintenance technician’s perspective. A maintenance human factor performance (MHFP) framework, MHFP indicators (high workload, time pressure, fatigue and communication) and weightings was developed. A total maintenance performance (TMP) framework for the South African electricity transmission industry was developed. The TMP consisted of 9 indicators: system performance, equipment performance, maintenance planning, maintenance completion percentage, maintenance human factor performance (MHFP), maintenance cost ratio percentage, maintenance errors, personnel cost ratio percentage and safety.

Measurement methods for the MHFP indicators were chosen: eight questions from the chronic work overload scale of the Trier Inventory of Chronic Stress (TICS), the adapted time pressure scale questionnaire, the Fatigue Severity Scale and the adapted Downs-Hazen Communication Satisfaction Questionnaire were chosen to be used as measuring methods for these maintenance human factors.

The MHFP and TMP frameworks were included into a proposed hierarchical maintenance performance framework for the South African electricity transmission industry. The frameworks provides a methodology to calculate a measurable value by using measuring methods.

A two-round Delphi method was used to validate the proposed hierarchical maintenance performance framework for the South African electricity transmission industry, inclusive of maintenance human factors.

Four significant maintenance human factors were identified by the maintenance technicians. Time pressure and communication were validated with the Delphi questionnaire. High workload was not validated in the Delphi questionnaire as there was no clear consensus achieved. There were, however, contradictions between the responses from the various questionnaire target groups, the prevailing opinion in literature and the prior findings of this thesis. The contradictions were discussed and it was concluded that high workload will remain as a significant contributor that leads to maintenance human errors.

The Delphi questionnaire, posed to a panel of experts, that included top management decision makers who can utilize the outcomes of the Delphi study, confirmed that: • Measuring the most influential maintenance human factors could have benefits in terms of performance, reduction in human error and better management of these influential maintenance human factors. • Inclusion of Maintenance Human Factor Performance within a TMP framework could benefit maintenance performance within Transmission.

This validated the final research output from an organisational view.

Identifying the most significant maintenance human factors that lead to maintenance human errors within the electricity transmission industry will provide a contribution to academic knowledge as research in this field is limited. Incorporation of measurements of these factors into an organisational performance measurement frameworks is uncommon in industry. Performance measurement frameworks needs to be industry specific. This research output contributes to academic knowledge by providing a method of doing this within the South African electricity transmission industry.

A practical, implementable contribution is made with the thesis providing a calculation methodology to calculate an exact total maintenance performance score for both maintenance and maintenance human factors.

Finally, by implementing a maintenance performance framework that includes the up-and-coming social dimensions of Industry 4.0, the successful implementation of Maintenance 4.0 can be improved.