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.
ix
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. / Thesis (M.Ing. (Development and Management Engineering))--North-West University, Potchefstroom Campus, 2012.
| Identifer | oai:union.ndltd.org:NWUBOLOKA1/oai:dspace.nwu.ac.za:10394/7061 |
| Date | January 2011 |
| Creators | Ishekwene, Isaac Victor |
| Publisher | North-West University |
| Source Sets | North-West University |
| Detected Language | English |
| Type | Thesis |
Page generated in 0.0031 seconds