Planning Horizon and Its Effects on CBM System

:- This study investigates a problem of machine inspection and condition monitoring (CM) for condition based maintenance (CBM) in the Nigerian electric power industry using one and two years as planning horizons. These planning horizons were applied on a developed model and prescribed method of solution of combinatorial optimization to obtain results. A two years planning horizon provides a savings of 10%, 16% and 27% respectively compared to a one year planning horizon for one month, two months and three months inspection intervals. Increasing the planning horizon has the tendency to decrease the CBM total expected cost of the system. Implementation of this strategy stage by stage can provide an optimum planning horizon for the system during its useful life.

INTRODUCTION Over the decades, the Nigerian Electric Power Industry has evolved tremendously. In recent times, it has shown the indication of moving from a regulated enterprise to a deregulated one. However, amount of electric power produced in the last five years has always been below 5,000 MW. With a population of over 180 million people, this amount of electricity is crossly inadequate. The promised made by various government to provide an uninterrupted power supply of electricity to its citizens has failed. Providing 24 hours of electricity daily to Nigerians should be taken as yardstick to measure the performance of any government in Nigeria. The supply of uninterruptable electricity is a figure of merit that measures the level of development of any country. With the concerted effort put up by government in its anti-corruption war and the drive for industrialization, much is still desired to show its reflection in the amount of power available to its citizens. Many companies have closed shops and the remaining few are still struggling to survive.
Proper management of the electricity industry of the country is needed. Deregulation is the key. Installation, operation and maintenance of the facilities in this sector should be the central focus. The use of condition based maintenance will accelerate and fasten growth in the Nigerian electric power industry.
Condition based maintenance (CBM) is an equipment maintenance procedure for detecting the condition of the equipment in order to evaluate whether it will fail during some future period and acting appropriately to avoid the consequence of that failure [1]. Maintenance is carried out when there is an obvious need which will increase the availability of the equipment in the system, as well as lower the maintenance cost. The data acquired could be used to determine whether the system is running at a normal operating condition. If the limits of the preset values are exceeded, the reason behind it can be determined and prediction made for future equipment breakdown and failure. Conditioned based maintenance requires taking the result of the analysis and planning the maintenance afterwards. A structure is needed for effective utilization and communication of condition monitoring data within the establishment requires [2].
Condition monitoring is important to the maintenance personnel as it allows it plan preventive work and possible serious consequences of breakdown [3].CM has the capacity to reduce maintenance cost by 45% [4]. The typical purpose of condition monitoring is to identify potential failure with the intension to accurately schedule maintenance activity so as to prevent operational interruption [5].
These warnings are known as potential failures [6]. It is identifiable physical conditions which indicate that a functional failure is about to occur or is in the process of occurring. Akpan, et al; 2016 presented and solved a CBM problem for a system subject to inspection.
The objective of this work is to investigate the effects of planning horizon on CBM total expected cost (TEC) and to present and solve a formulated combinatorial optimization problem for a four machine system based on two planning horizons of one and two years.
II METHODOLOGY Four turbines in Afam (IV) electric power station in Nigeria were used in the case study. Data were obtained from this source and elaborate discussions were made with managers, supervisors, engineers and maintainers on CBM implementation strategy in the organization. This data was applied on a developed model and combinatorial optimization used as a method of solution.
In this study an exponential distribution was assumed.  (2) where the mean time to failure is given as The cumulative distribution function (CDF) is given as: For an exponential distribution, The CBM model had been presented and solved by Akpan, et al; [7].
where TEC is the total expected cost of the system And, A is the depreciation cost, P is the acquisition cost, m n the planned years of replacement 1 ,  j idi C is the down time cost of machine i in interval j, L P is the production loss and dmi t , the down time for production loss.
The failure cost 1 ,  j i C is expressed as: The unit has four turbines as shown in Table one below. The planning horizons are one and two years respectively (T = 1 year and 2 years). Table one shows the input data for Afam (IV) Electric Power Station.

III
RESULTS AND DISCUSSION Table two shows the total expected cost for a one year planning horizon for the plant.    Table 3 shows the total expected cost for two years planning horizon for Afam (IV) electric power station.