Knowledge Criticality Assessment and Codification Framework for Major Maintenance Activities: A Case Study of Cement Rotary Kiln Plant

Maintenance experts involved in managing major maintenance activities such as; Major overhauls, outages, shutdowns and turnarounds (MoOSTs) are constantly faced with uncertainties during the planning and/or execution phases, which often stretches beyond the organisation’s standard operating procedures and require the intervention of staff expertise. This underpins a need to complement and sustain existing efforts in managing uncertainties in MoOSTs through the transformation of knowledgeable actions generated from experts’ tacit-based knowledge. However, a vital approach to achieve such transformation is by prioritising maintenance activities during MoOSTs. Two methods for prioritising maintenance activities were adopted in this study; one involved a traditional qualitative method for task criticality assessment. The other, a quantitative method, utilised a Fuzzy inference system, mapping membership functions of two crisp inputs and output accompanied by If-Then rules specifically developed for this study. Prior information from a 5-year quantitative dataset was obtained from a case study with appreciable frequency for performing MoOSTs; in this case, a Rotary Kiln system (RKS) was utilised in demonstrating practical applicability. The selection of the two methods was informed by their perceived suitability to adequately analyse the available dataset. Results and analysis of the two methods indicated that the obtained Fuzzy criticality numbers were more sensitive and capable of examining the degree of changes to membership functions. However, the usefulness of the traditional qualitative method as a complementary approach lies in its ability to provide a baseline for informing expert opinions, which are critical in developing specific If-Then rules for the Fuzzy inference system

Applicability of published data for fatigue-limited design

The use of published fatigue data provides an expedient basis for fatigue-limited engineering design by alleviating the necessity of explicit testing. However, published fatigue data often exhibits incomplete documentation of the associated test conditions. Incomplete documentation introduces uncertainties in fatigue life prediction that may limit the applicability of the published fatigue data for design applications. Characterization of the applicability of published fatigue data is critical for robust fatigue-limited design. However, no quantitative methods have been identified which respond to this requirement. A novel method has been developed to provide a systematic characterization of the applicability of published fatigue data based on internationally recognized standards. This method provides a conceptual mechanism to: 'identify the applicability of published fatigue test data for specific design scenarios' thereby informing engineers of potential limitations of published data and allowing prioritization of multiple data sources; 'identify material domains of insufficient applicability' thereby providing a robust basis for identifying beneficial fatigue test programs; 'compromise between design complexity and the uncertainties inherent in fatigue life prediction; 'define a framework for the appropriate documentation of published fatigue data. A sample of published fatigue data sources associated with a specific fatigue-limited safety' critical design scenario was assessed by the method presented in this paper. For the majority of the sampled references, the associated documentation was insufficient to allow the fatigue test data to be confidently applied to the subsequent design activity