Improving the turnaround maintenance of the Escravos gas plant
Ishekwene, Isaac Victor
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According to Oliver (2002) the success of turnaround maintenances is measured in terms of the cost of completion, time, safety performance and the performance of the plant afterwards. The Escravos gas plant (EGP) is a gas processing plant that converts associated gas from Chevron owned crude oil wells to liquefied petroleum gas, natural gas and gas condensate (Chevron intranet. Website assessed on September 14, 2007). According to the EGP plant operations coordinator (See interview Appendix A), the plant undergoes a turnaround maintenance exercise once every two years. The major tasks done during these turnaround maintenances are 1. Change–out of three molecular sieve beds. 2. Servicing of three compressor turbines. 3. Servicing of expander turbo–machinery. 4. Clean–out of fired gas heater tubes and burners. 5. Tie–ins for major upgrades. The EGP management does not involve the contractor personnel that carry out the tasks in the management of the turnaround maintenance. The contractor’s personnel simply follow the work plans and instructions developed by the EGP management. The EGP turnaround management team consists of the coordinator who is the head of the turnaround maintenance team, shift supervisors, maintenance supervisors (rotating equipment maintenance supervisor, instrumentation and electrical maintenance supervisor, and static equipment maintenance supervisors), safety supervisors, maintenance planners, process engineers and construction supervisors. All these listed personnel in the preceding paragraph and the supervisors of the contractor teams participate in the pre–turnaround meetings which happen once a month for the first 10 months of the 12 months leading to the turnaround. The meeting frequency increases to once every two weeks during the last two months leading to the turnaround maintenance. The meeting is held daily during the turnaround maintenance and once every two weeks for the first month after the turnaround maintenance. During the preceding months to the turnaround maintenance, the work scope is defined, the job sequence outlined and schedules are developed. Resources requirements are detailed and procured. During the turnaround maintenance the focus of the turnaround meeting is to discuss potential deviations, observe at–risk behaviors and likely challenges. Plans are then made to address these deviations, challenges and at–risk behaviors. After the turnaround maintenance, “lessons learnt” are captured and the turnaround maintenance is closed out. According to the EGP coordinator (see interview in appendix A), the success of its turnaround maintenance is measured by the time used to complete the turnaround maintenance, the total recordable incident rate during the turnaround maintenance, the days away from work, the lost time injury(LTI) and the cost incurred. Poling et al noted that it is difficult to rate turnaround maintenance projects because no two turnaround maintenances strategies are exactly the same. They iterated that the most common tactics used is benchmarking and that benchmarking enables a company to measure and compare its performance against peer companies in a constructive and confidential manner. They pointed out that the quantitative differences computed between a plant and other similar plants using detailed data taxonomy can provide invaluable information regarding improvement opportunities. This is a way of effectively extending a “lessons learned” exercise across multiple companies. According to then however a critical attribute of effective reliability and maintenance benchmarking is the ability to compare disparate assets; but even small differences for similar plants can alter the value of the comparison. Existing literature indicate that the parameters the gas plant management use to rate the safety of its turnaround maintenance (i.e. the total recordable incident rate, the days away from work and the lost time injury)are reactive in nature. They are otherwise called lagging indicators. Lagging indicators are safety performance metrics that are recorded after the accident or incidents has occurred. For example lost time injury is any work related injury or illness which prevents that person from doing any work day after accident (E&P Consultancy Associates. Website assessed on June 15, 2009). In contrast the other group of metrics called pro–active metrics or leading indicators such as at–risk behaviors, near misses and preventive maintenance not completed are parameters that measure safety performance before accident occurs. Leading indicators gained popularity in the 1930’s after Heinrich postulate his iceberg theory (Wright, 2004). Heinrich’s used the iceberg analogy to explain reactive (lagging) and proactive (leading) indicators. Heinrich likened accident and at–risk behaviors to two parts of an Iceberg; the part you see above water and the part hidden under the water. The size of the iceberg above water is relatively small compared to that under water. The iceberg starts to grow under the water and only after they reach a certain size does part of the ice begin to appear above water. Heinrich believed that accidents are the result of root causes such as at–risk behaviors, inconsistencies, wrong policies, lack of training and lack of information. When the number of accidents that occur in an endeavor is measured you get relatively smaller numerical quantities when compared to the number of at–risk behaviors. Heinrich suggested that to eliminate accidents that occur infrequently, organizations must make effort to eliminate the root causes which occur very frequently. This makes sense because imagine a member of personnel coming to work intoxicated every day. Binging intoxicated at work is an at–risk behavior. The employee is very likely to be involved in an accident at some time as a result of his drinking habit. The number of times he is intoxicated if counted will be huge when compared to the impact of the accident when it does occur. The iceberg theory is supported by work from Bird (1980) and Ludwig (1980) who both attempted to establish the correct ratio of accidents to root causes in different industries. Heinrich suggested a ratio of three hundred incidents to twenty nine minor injuries to one major injury. This researcher chose to use the number of at–risk behavior exhibited by the turnaround maintenance teams to rate the safety performance of tasks despite criticism from individuals like Robotham (2004) who said that from his experience minor incidents do not have the potential to become major accidents and Wright et al (2004). Leading indicators are convenient to analysis because of their relative large quantity. In a turnaround environment, the numbers of accidents that occur are relatively few unlike the number of near misses (Bird, 1980). It is easy to statistically analyze thirty at–risk behaviors than four accidents. In addition Fleming et al (2001) noted that data from industry show much success by companies in the reduction of accidents by efforts at reducing the number of at–risk behaviors, increase the number of safety audits, and reduce the number of closed items from audits etc. Phimister et al made similar claims when they said Near miss programs improve corporate environmental, health and safety performance through the identification of near misses. Existing literature also reveals many theories about management styles and their possible impact on performance. The theories are grouped into trait theories, situational theories and behavioral theories. The trait theories tries to explain management styles by traits of the managers like initiative, wisdom, compassion and ambitious. Situational theories suggest that there is no best management style and managers will need to determine which management style best suit the situation. Behavioral theories explain management success by what successful managers do. Behavioral theorists identify autocratic, benevolent, consultative and participatory management styles. Vroom and Yetton (1973) identified variables that will determine the best management style for any given situation. The variables are; 1. Nature of the problem. Is it simple, hard, complex or clear? 2. Requirements for accuracy. What is the consequence of mistakes? 3. Acceptance of an initiative. Do you want people to use their initiative or not? 4. Time–constraints. How much time do we have to finish the task? 5. Cost constraints. Do we have enough or excess to achieve the objective? A decision model was developed by Vroom and Yago (1988) to help managers determine the best management style for different situations based on the variables listed above (See figure six). They also defined five management style could adopt, namely the; 1. Autocratic I style 2. Autocratic II style. 3. Consultative I style 4. Consultative II style 5. Group II style The autocratic I management style is a management style where the leader solves the problem alone using information that is readily available to him/her, is the normal management style of the Escravos gas plant management in all turnarounds prior to 2009. However the Vroom and Yago model recommends the Consultative II management style for the type of work done during the Escravos gas plant turnaround maintenance. According to Coye et al (1995), participatory management or consultative style II creates a sense of ownership in organization. In this management style the leader shares problem with group members individually, and asks for information and evaluation. Group members do not meet collectively, and leader makes decision alone (Vroom and Yago, 1988). Coye et al believe that this management styles instills a sense of pride and motivate employees to increase productivity. In addition they stated that employees who participate in the decisions of the organization feel like they are a part of a team with a common goal, and find their sense of self–esteem and creative fulfillment heightened. According to Filley et al (1961), Spector and Suttle did not find any significant difference in the output of employees under autocratic and participatory management style. This research studies if and how the Escravos gas plant turnaround maintenance can be improved by changing the management style from autocratic I style to consultative II style. Two tasks in the turnaround were studied; namely the change out of the molecular sieve catalyst beds and the servicing of the turbine engines. The turnaround contractor Techint Nigeria Limited divides the work group into teams responsible for specific tasks. Six teams (team A, B, C, D, E and F) were studied. EGP management will not allow the researcher to study more than these six teams for fear of the research disrupting the work. The tasks completed by these teams are amongst those not on the projects critical path so delays caused by the research will not impact the entire turnaround project provided the float on these activities were not exceeded. They also had the fewest number of personnel, so cost impact of the research work could be easier to manager. Teams A, B and C are different maintenance teams comprising of eight personnel each. They were responsible for changing the EGP molecular sieve beds A, B and C respectively in the 2007 and 2009 turnaround. Their tasks are identical because the molecular sieve beds are identical. Teams E, D and F are also maintenance teams comprising of six personnel each. They were responsible for servicing the EGP turbine engines A, B and C during the 2007 and 2009 turnaround maintenance. Their tasks are also identical because the turbine engines are identical. Consultative management style II is exercised by involving team A and team D in the development of the procedures, processes and job safety analysis of all tasks that they were assigned to complete during the 2009 turnaround maintenance. They were also permitted to participate in the turnaround maintenance meetings and to make contributions in the meetings. In the 2007 turnaround maintenance team A and team D only carried out their tasks. They did not participate in the development of procedures and job safety analysis neither did they participate in the turnaround maintenance meetings. The other four teams; team B, team C, team E and team F are used as experimental controls for the research. They did not participate in the development of the procedures, processes nor the job safety analysis for the tasks in either of the turnaround maintenance. They were also not permitted to attend the daily turnaround meetings. They only completed their tasks based on instructions given to them during the 2007 and 2009 turnaround maintenance. It was necessary to study the experimental control teams as the researcher was not sure whether task repetition, increased knowledge or improved team cohesion would lead to a reduced time or a reduced numbers of at–risk behavior. The research tested the hypothesis 1H0 and 1H1 and 2H0and 2H1 at the 0.025 and 0.05 level of significance as follows; Null hypothesis, 1H0: There is no significant difference in the time spent by team A and team Din 2007 when they did not participate in the development of the procedures and processes with the time in 2009 when they did(u1-u2=0). Alternate hypothesis, 1H1: There is a significant difference in the time spent by the team A and Din 2007 when they did not participate in the development of the procedures and processes with the time in 2009 when they did (u1-u2!=0). Null hypothesis, 2H0: There is no significant difference in the number of at–risk behaviors observed to have been exhibited by the team A and team D in 2007 when they did not participate in the development of the procedures and processes with the number in 2009 when they did (u1-u2=0). Alternate hypothesis, 2H1: There is a significant difference in the number of at–risk behaviors observed to have been exhibited by the team A and team D in 2007 when they did not participate in the development of the procedures and processes with the number in 2009 when they did (u1-u2!=0). The student t test was used to analyze these times and number of at–risk behavior. At the 0.025 and the 0.05 level of significance, the data show that there is no difference in the times all the teams used to complete their task in 2007 and in 2009. The researcher concludes that a change in the management style from autocratic I style to consultative II style did not lead to a reduction in the time used by any team to complete their task. However at the 0.025 and the 0.05 level of significance, there is a significant difference in the number of at–risk behaviors of the research team A and team D. There is however no significant difference in the number of at–risk behavior of the control team B, team C, team E and team F at the same level of significance. The researcher concludes that a change in the management style from autocratic I style to consultative II style lead to a reduction in the number of at–risk behavior of team A and team D. In addition the reduction in the number of at–risk behavior of team A and team D could not have been because of task repetition, increased knowledge or improved team cohesion since there is no significant difference in the number of at–risk behavior exhibited by team B, team C, team E and team F. The research can be used by the Escravos gas plant management and the management of any similar process plant to fashion out more cost effective, time effective and safer methods for carrying out their turnaround maintenance. A change in management styles may just be a better approach to improving productivity than giving financial incentives to contractors and personnel. Changes in management style will have to be managed. The change must be gradual because sudden change can be detrimental as people may just need to understand and adapt to the change. The turnaround personnel must also understand the intent so as to prevent conflicts.
- Engineering 
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