DECLARATION 2- PUBLICATIONS
6.2 Methodological approach
6.2.1 Problem background
A systems thinking approach is employed to determine root causes of AM related energy supply problems and their impacts. Case studies from Southern African power utility set-up are used. Systems thinking helps to establish root causes so that analytical techniques can be employed to solve the specific problems that have been identified [26]. The systems approach does so by using causal loop diagrams [2], [28]. The application of systems thinking concept showed how the energy supply problems cascaded from the generation down to the distribution business unit in a vertically integrated power utility firm. At the generation business unit, the systems approach indicated how the use of availability as a metric, as opposed to Energy-Not-Supplied (ENS), had put the utility off-balance. In addition, it showed that outsourcing of refurbishment and maintenance works led to a decline in the firm’s technical-skills-base as demonstrated in Figure 6- 1. In the causal loop diagrams (Figures 6-1 and 6-3), independent variables are at the beginning of arrows, whereas the dependent variables are at the arrow heads. An “s” means: when the independent variable changes, the value of the dependent variable will be above what it was before the input from the independent variable, whereas an “o” means it will be below what it was before
the input from the independent variable. Other symbols and notations used in causal diagrams are as described beneath Figure 6-1.
Figure 6-1 shows that outsourcing enables the firm to focus on core activities, but leads to loss of its technical-skills-base in the long run. In addition, it increases the outsourced contractor’s financial returns and technical capabilities, which in turn increases the host institution’s asset performance. Besides, increase in the contractor’s skill base reduces the host institution’s technical skills, but the effect is delayed (i.e., it is not immediately evident).
s s
o o s
s o
s
s
s
s o
s
s s s
Host institution focus on other core
activities
Host institution Outsourcing technical
activities
Host institution technical skill
base Outsourced contractor
business and financial returns
Outsourced contractor technical capabilities/
skill base
Host institution asset performance
CAPEX
Revenue OPEX
Training
Resources
Investment Dependence
R
R
B
B R
R
R
Key to symbols used:
B
R CAPEX ≡ Capital expenditure
OPEX ≡ Operating expenditure Reinforcing loop
Balancing loop
≡ Delay
Figure 6-1: Systems view of outsourcing technical skill
Figure 6-1 further shows that outsourcing of the host institution’s technical activities enhances its focus on core competencies (activities), but eventually diminishes its technical skills. Finally, as the outsourced contractor increases the host institution’s asset performance, it increases revenue and resources for OPEX and leads to more outsourcing activities. It also increases revenue for CAPEX in investment activities, thereby further increasing asset performance; and enhancing training of the host institution’s staff to advance their technical skills.
The systems view was also applied to evaluate how equipment management paradigms are affecting the operating business risk or the sustainability of power distribution in the industry. Since the Second World War, the equipment management paradigms have evolved from a reactive strategy to preventive, condition-based and proactive strategies, as well as those that incorporate probabilistic models [105]. These paradigms have been distinguished by different characteristics, strategies and rationales (motivations) [26]. Figure 6-2 outlines the evolution of the paradigms.
Each paradigm has a measure of impact on the sustainability of business operations or on the risk profile of the asset base.
Characteristic:
Continuous improvement for competitive
advantage Strategy:
Pre-emptive tasks to optimise reliability,
avoid failure
Proactive with Probabilistic
models 2000-2014 +
(what next?)
Preventive Strategy:
Determined by parameter indicative of
condition
Characteristic:
No warning (surprises)
Strategy:
Fix it after it breaks Rationale:
Short-term Cost savings Characteristic:
Eliminates surprises Strategy:
Time-based schedules Rationale:
Cost reduction to raise margins Characteristic:
Maintain so that it does not break
Rationale:
Opportunity driven business
model
Rationale:
Opportunity driven business model Condition
based
Reactive 1940-1954 1978-2000
1955-1977
Paradigm evolution
Figure 6-2: Evolution of equipment management paradigms
Figure 6-2 shows that the physical AM has gone through four strategic paradigms from 1940 to the present time. Each of these paradigms can be viewed as a technological generation with unique characteristics that distinguishes it from other generations [25], [105]. The first paradigm is the reactive strategy [25], [26]. It was more predominant from the time of the Second World War to around 1954 than it is today. It aims at fixing the assets after failing; hence it subjects the firms to surprises. Its basic rationale is to realize quick wins or short term cost savings. After that, the preventive paradigm emerged, predominantly spanning from around 1955 to 1977. This is implemented through time-based maintenance schedules. The motivation behind this is to reduce costs, thereby raising profit margins; and in so doing to eliminate surprises. The period between 1978 and 2000 was marked by a shift to predominantly condition-based paradigm, where maintenance and renewal regimes or tasks were determined by parameters indicative of the condition or state of the equipment. The rationale for this was to take advantage of every opportunity to lengthen the life of equipment by carrying out maintenance when it is necessary, unlike in the preventive regime where 50% of tasks might be unnecessary and wasteful [25]. Its main characteristic is that the equipment is maintained so that there is no breakdown. Finally, proactive strategies with probabilistic models have mainly been applied in the period between 2000 and the present. This paradigm is predominantly based on pre-emptive tasks that are aimed at optimizing reliability and avoiding failure. Like the condition-based, this is also opportunity driven, but it is characterized by continuous improvement in order to gain competitive advantage over other firms [25].
In practice, industries tend to incorporate a mix of these strategic paradigms. Therefore, even in the paradigm that is predominantly condition-based or proactive, some reactive strategies may still be employed. There are many reasons for such a mix. For example, in this research a case study of the run-to-failure strategy (which is one of the reactive strategies), has been applied and it shows that, traditionally, power utilities view that the strategy is suitable for the less capital-intensive assets. Figure 6-3 outlines a systems view of the strategy. It shows that short term strategies aimed at quick wins lead to the run-to-failure strategy and they negatively affect the AM planning process and asset condition. The case study showed that failure rates in the distribution business unit were very high and that asset managers implemented the run-to-failure strategy as the default strategy.
o s
s o
s s
s s
s s
o
Short term cost savings
Asset condition Run to failure strategy
Long-term sustainability Quick wins
Long term asset planning
Short-term strategies aimed at quick wins
R R
B R
B
Figure 6-3: Systems view of run-to-failure strategy
The case study showed that there was no incentive for instituting radical changes in the distribution business unit as the value of the individual power transformers, relative to their transmission counterparts, was perceived to be very low. This is a reductionist thinking. A holistic, systems approach is required to change that mechanistic thinking in the power sector.
The case study further showed that, unlike the transmission system which in most cases has SCADA technology, most of the MV distribution assets are not connected to the SCADA. That makes control and fault location difficult. For this sub-Saharan Africa scenario, distribution losses have been recorded at as high as 22% (see, for example, Appendix I), which for a small power utility, translate to annual losses due to the ENS to the magnitude of US$ 1.0 million; against annual sales averaging at US$ 3.6 million (i.e., the ENS is 27.7% of annual sales). For this typical case, the capital outlay for extending the SCADA to the distribution (MV) is around US$ 20 million. The context highlighted above sheds some light as to why it is so difficult to have a technological advancement in the distribution sector in the region. Hence, sustainable energy supply cannot be achieved unless there is a paradigm shift in the way energy or power distribution assets are managed. This background reinforces earlier publications that revealed that the distribution system takes 30 to 40% of total investment in the electrical sector, but the industry has not received the technological impact in the same manner as the generation and transmission systems [23].