A Study into the Use of the Dysfunction Mode and Effects Critical Analysis (DMECA) in a Power Plant

Abstract

Dysfunction Mode and Effect Critical Analysis (DMECA) is a well-established tool for assessing dysfunctions regarding the quality of maintenance and production processes. It is conceptually same as the Total Quality Management (TQM) tool of Failure Mode and Effect Critical Analysis (FMECA). It helps to focus on core challenges while still including a wide range of dysfunctions. Since the nature of dysfunctions and quality issues are very similar, the general idea and framework of a DMECA may be adapted successfully to remove dysfunctions in management process. The DMECA approach, to determine and analyze possible dysfunctions in complex management processes, was developed by Massimo Bertolini, et.al. [2]. They recommended that this method can be applied to various fields such as manufacturing industry, power plant, gas generating plant even where the measure of management process efficiency is more difficult. The analytical tool DMECA works according to the new ISO 9000:2000 standards and the Total Quality Management (TQM) principle concerning the 'process approach'. In this study, DMECA method is applied to determine and analyze the possible dysfunctions in complex management process of a power plant. According to the literature reviewed, probably this is the first to use the DMECA in a large power plant. DMECA is used to analyze each potential dysfunction mode for each elementary activity constituting the plant processes, to identify the subsequent effects. A list of priority interventions of the dysfunction modes then decided. The evaluation of the priorities are utilized to create a classification of the potential dysfunction modes according to a criticality parameter obtained by the combination of severity of the consequences, probability that the dysfunction occurs and chances that it can be detected. The process break-down structure defined during the process identification phase (reported in Figure 4.4 for the firms' processes) 09 sub-processes and 57 activities of job management process were identified. For each activity, possible dysfunctions had established and 175 potential causes have been identified for the whole process of 'job management'. A code number was assigned to each dysfunction with the same criteria as used to map the processes. In order to conduct a criticality analysis of dysfunction, the judgment criteria is defined, by which the unwanted event was assessed. The conversion tables (Table 4.2, 4.3, 4.4 & 4.5) were suggested to translate linguistic judgments into numerical values to obtain a Risk Priority Number (RPN). Thus, it will be possible to judge and evaluate the criticality of the dysfunction causes. Data for this study were collected from the respondents of the study area by using the questionnaire prepared (Appendix A). The interviews were made group wise in the power plant during their work and leisure time with the permission of interviewee as well as management. Each personnel completed the questionnaire independently, with the support of Table 4.5. Mean values (from all questionnaires) of the three parameters; occurrence dysfunctions (OD), Detectability dysfunctions (DD) and severity dysfunctions (SD) for each dysfunction were calculated. Finally, the respective RPNs were obtained as RPN = ODx DD x SD. The calculated RPN values are provided in table 4.6. These products may be viewed as a relative measure of the management dysfunctions. The RPN values can range from 1 to 1000, with 1 being the smallest management dysfunction possible and 1000 being the biggest management dysfunction possible. These values were then used to rank the various causes in the dysfunctions. In case of process with a relatively high RPN, the engineering team must make efforts to take corrective action to reduce the RPN. Likewise, because of a certain dysfunction has a relatively low RPN, the engineering teams should not overlook the causes and should not neglect an effort to reduce the RPN. This is especially true, when the severity of a cause is high. In this case, a low RPN may be extremely misleading, not placing enough importance on a cause where the level of severity may be disastrous. In general, the purpose of the RPN was to rank the various causes documented. The smaller the RPN the better - and - the larger the worse. Dysfunction causes and their relative weights were investigated for each activity in order to determine the most critical and to decide improvement actions. There are only 25 causes of dysfunctions those are critical amongst 175 cusses. The beauty of DMECA method is that it permits to identify and eliminate particular Dysfunctions and simultaneously it will correct or eliminate other problems or inefficiencies indirectly. Therefore, at the end of the DMECA structured process analysis, we obtained schemes where relatively few corrective actions can solve multiple dysfunctions (Table 5.2). This was possible because there were a strong interrelationship between management processes and activities. The main advantage of the methodology is its applicability to the managerial processes of each organization (i.e., firms, public services, local agency or government). In particular, DMECA is a valid technique to evaluate processes efficiency and effectiveness in the field of service sector where measuring, monitoring and correcting the possible dysfunctions in managerial processes are critical to improve the performances of production and maintenance. To analyze the managerial dysfunctions in any organization the DMECA approach is very effective and it involves low cost as it is found in this research work. So, it is a cost effective and can be applied to identify management personnel deficiencies which in turn will be helpful for uninterrupted production and/or maintenance. It identifies, access and ranks dysfunctions that are challenging to eliminate. Thus, the method prevents the consumption of time and cost of production and/or maintenance. In this study an application of the DMECA technique applied in an important power plant (maintenance and production for electricity) to analyze, to evaluate and to improve job management process efficiency. Finally a number of recommendations are made to the management to implement the research findings to the plants. At last but not least some recommendations are also made for further study.