ENG8104 Asset Management in an Engineering Assignment Sample

Evaluation of Alternative Development and Management Options for Assets in The Network

An asset lifecycle is defined as a series of steps that are involved in the management of an asset. This begins at planning, the assets life, and to its eventual disposal. An asset's lifecycle can be tracked and evaluated based on several factors, including the cost of replacement, its role, or how crucial it is to the business and its overall reliability. Two major ways of asset maintenance are predictive-based and condition-based maintenance. These maintenance strategies are both proactive are meant to decrease downtime and increase reliability.

Predictive-Based Maintenance

Predictive-based maintenance is used as a predictive strategy for asset failures through data-enabled techniques (Meyer & Vincent 2019). Predictive maintenance encompasses a series of few steps, the first being establishing baselines. Baselines, in this case, are the initial conditions of assets before the process begins and sensors can be put in place, which are acceptable working conditions of the assets. Predictive-based maintenance checks for abnormalities based on these initial baselines.

Any time equipment records different parameters, the sensors trigger the predictive maintenance protocol. After the establishment of baselines, relevant sensors are fixed to the asset. These are mainly mechanical devices such as vibration meters or temperature sensors attached to the assets to monitor them. These devices are then connected to a central station or dashboard where all data collected can be stored and analyzed. Finally, inspections are automatically triggered when abnormalities occur, when conditions limits are exceeded or when the people monitoring the dashboard schedule the inspection manually.

Predictive-based maintenance however needs an investment of people and resources to see it through. Types of predictive-maintenance include vibrational analysis, acoustical (ultrasonic) analysis, and infrared analysis. An example of predictive-based maintenance is in a centrifugal pump. The pump has many and heavy rotations which are created a baseline for initially. A vibration sensor is then fixed to monitor the pump and is connected to a central dashboard. Whenever there is a problem in the vibrations, the crew is notified. This method, there is a reduction of maintenance costs by 22% to 30%, breakdown elimination of 70% to 75%, and an increase in production of 20% to 25% to show its economic significance, (Sullivan 2010).

This method has its pros and cons. One of its major strengths is its increase in uptime and downtime reduction. The method also streamlines incurred costs by labor reduction, inventory, and equipment costs and in the process of improving safety. On the other hand, predictive-based maintenance is expensive to implement and maintain and is also time-intensive. Predictive maintenance is for larger organizations. It requires big capital investments. However, it brings about major cost savings in maintenance and higher profits overall.

Condition-Based Maintenance

This method uses measurements made by equipment only when there are failures or repairs are needed. The method involves determining the precise maintenance points by visually inspecting equipment, performing tests, or gathering data and diagnostics. This method, therefore, allows people to act only on a need basis. This method however uses condition monitoring and measurements. Monitoring measures specific device parameters such as sound and vibrations while taking records of major changes that could result in defects. The maintenance personnel notes regular condition measurements from the parameters therefore providing the equipment's current health. As equipment health conditions decline, the personnel work and repair the equipment to its normal state.

Condition-based systems reduce downtime to assets. An example of a centrifugal fan, the fan has a distinct sound in normal conditions and considerably low noise levels when everything is working normally. However, as the fan starts becoming faulty, noises increase. The crew will, therefore, know when to replace when the fan noise levels become too much. This, therefore, means that the maintenance crew can replace the fan before it becomes faulty. This reduces the downtime since maintenance can be measured and done before total breakdown. Identification of faults helps maintenance crews make more informed decisions.

This method has its strengths and weaknesses. The major strength is that maintenance work is only done when needed hence reducing the labor needed to monitor the systems all the time. The system also reduces the unplanned events of downtime while improving the prioritization of maintenance time. However, there are high installation costs, training costs, and also maintenance. Further, it is difficult to choose the proper equipment for sensors since unlike the predictive method, the equipment is not monitored all the time. Condition-based maintenance is expensive considering the benefits. However, some organizations have critical equipment that needs conditional-based maintenance. In this case, this method reduces the downtime from this equipment. It also ensures that not so many people are used in monitoring equipment hence savings in maintenance.

Discounted Cash Flow

The EAC formula is

Asset price * Discount Rate + Annual Maintenance Costs

1- (1+Discount Rate) - periods

EAC option 1 = 0 * 0.06 + 0

1 – (1+ 0.06)-0

EAC1= $0

EAC2 = 5000000 * 0.06 + 50000

1 – (1+ 0.06)-60

EAC2 = $359,374

EAC3 = 3700000 * 0.06 + 45000

1- (1+ 0.06) -60

EAC3 =$ 273,940

EAC4 = 6000000 * 0.06 + 20000

1- (1+ 0.06) -100

EAC4= $381,064

EAC5 = 1400000 * 0.06 + 30000

1- (1+ 0.06) -15

EAC5 = $174,147

EAC6 = 2500000 * 0.06 + 35000

1- (1+ 0.06) 35

EAC6 = $207,434

Order from least to the greatest equivalent annual cost

Option 1- do nothing at $0

Option 5- undertaking minor changes to the original asset at $174,147

Option 6- rehabilitating existing asset at $207,434

Option 3- developing new asset option 2 at $273,940

Option 2- developing new asset option 1 at $ 359,347

Option 4- developing new asset option 3 at $381,064

Ranking by highest benefit/cost ratio

Option 3 – 500000/273940 = 1.825

Option 5- 250000/174147 = 1.436

Option 2 – 500000/359374 = 1.391

Option 4- 500000/ 381064 = 1.312

Option 6- 250000/207434 = 1.205

Option 1- 0/0 = 0

Discussion of Findings

All the above options have their implications and could all affect asset allocation. For the first option, the choice may be to do nothing in investment. This is a risk-free option since no investment is made whatsoever. However, no returns can be expected from it. Investment has to be made for returns to come. For the second option, a big investment is made and which is expected to run for a long period of 60years. The expected returns are good but the average annual maintenance cost is relatively high. However, there are minor issues with the community, stakeholders, and the environment. Despite the good returns, an asset that is to run for such a long time should be accepted communally. The asset should also use as little as possible for annual maintenance costs.

Option 3 involves the development of an asset, cheaper than option 2s' asset but several issues with stakeholders, environment, and community just like option 2s' asset. The returns are equivalent to option 2' and there is a similar lifespan for the assets. The asset however has lower and more reasonable average maintenance costs being 90% of options 2s' maintenance costs.

Option 3, therefore, beats option 2 by far. Option 4 has the biggest investment of $6 million. The asset is expected to run for the longest time among all the options with 100 years. The asset has the least average annual maintenance of $20000, 44% of options 3s' maintenance. The returns are however the same. There are however same environmental and stakeholder issues. This option is good owing it to the good returns and low operation costs. It however requires a lot of investment for a very risky and very long time. Finally, the results in returns remain unchanged from the previous options.

Option 5 involves upgrading the already existing asset. This option requires the least investment. The expected revenue is however half of the two previous options and annual maintenance costs remain average. The option however has the least life span. The maintenance costs are also reasonably high compared to the expected lifespan. The revenue is also low. The last option involves the rehabilitation of existing assets. This however has a bigger investment than option 5 and a bigger lifespan of 20 more years. The annual maintenance costs are however higher than option 5. The annual expected revenue for the option is same as the option 5. Compared to option 5, it requires more investment and requires more annual maintenance costs. It also requires an investment of almost twice that of option 5.

Many factors come into place when deciding between options. The number of years, the investment amount, annual maintenance costs, and expected revenue have to be collectively evaluated for the best option. From the above findings, the best options are options 3 and 5. Option 5 is a good option but lacks a good period. It is however able to produce well with the small capital investment. Option 3 stands out as the best option. Despite the minor environmental and stakeholder issues from the asset, it has good returns and a sound investment amount. It also has an average maintenance cost and runs for a long period.

Considerations in Network Programming

Asset allocation refers to an investment strategy in which people divide their investments among different and diverse asset classes to reduce investment risks ("Asset Allocation - Overview, Examples, Strategies for Asset Allocation", 2020). Several factors are considered during programming. The overall goal factor is considered. This refers to unique or individual aspirations to achieve a given level of saving or return for a particular desire or reason. The goal or outcome affects how the person chooses to invest. Another reason is the risk tolerance of the individual investing. This refers to the limit to which the person is willing and able to lose an initial investment in anticipation of profits or higher returns in the future.

For example, investors who don't risk big prefer to invest in more secure assets and avoid risky ones. However, big risk takers risk their resources even on very risky assets and anticipate returns. Investors also consider the time. This refers to the duration that the investor is going to invest. This directly relates to the risk tolerance of the investor. Long time investments are at a higher risk than short term ones. Short term investments are on the other hand less risky. Investments are risks that could make or break an investor. However, investors need to be wise in considering which assets they choose to invest in. They should critically consider these factors and come up with informed decisions on the best investments.

Optimization Approaches for Network Programming

Several techniques have been put forward as optimization approaches. However, the main optimization techniques are the policy-based asset management and performance-based asset management program.

Policy-based asset management supports a life-cycle approach which is long term, to evaluating investment costs and benefits. These decisions may be based on formula-based calculations, historical funding baselines, or deal-making instead of on current performance targets and objectives. These programs should define directions and overall priorities for a company’s equipment management. It should also relate, a measure of performance, objectives, and performance targets. The approach does not however state what priorities should be first-only that independent agencies and their policy teams analyze and discuss options to policy and adopt the ones thought to be warranted.

Performance-based asset management pragmas on the other hand support preservation of existing assets by the use of identifiable targets and measures. These enable decision-makers in identifying the best balance between utilization and availability for any asset at a given moment basing it on the current performance measures prioritized to the current business strategy. However, the lack of effective performance measures for operation, engineering, and maintenance result in performance approaches that are based more on budget cost management than on the assets performance management.

Applying Network Programing to The Prioritization of Asset Development Options

Prioritization of asset development involves several considerations. The best way for asset prioritization is the asset criticality ranking. This involves a combination of several factors which include consequences, reliability, and detectability. In this case, consequences are the consequence of failure, which includes the impact on production, environment, safety, and repair costs. The reliability of an asset entails the likelihood that a fault could occur leading to functional failure. Detectability of the defect condition entails the likeliness of detecting the onset of the failure, therefore, avoiding consequences.

A scenario of two assets, if an asset is unreliable and does not have means of detecting failure and could have huge consequences, it poses a great risk, and attention should be given to the asset. It will, therefore, achieve a high asset criticality ranking. On the other side, an asset that is reliable with minimal downtimes has a good failure detecting strategy and poses little risk in taking preventative action, the asset will receive a low critical ranking. The ranking, therefore, declares assets as critical, essential, or non-essential.

The ranking puts consequence, reliability, and detectability in levels. For example, for maintenance, the levels could; insignificant, minor, moderate, major, and extreme. The stakeholders however create their ranking tailored to the situation on hand.

Near Optimization Method for Network Programming

The rank;

Asset 4: at $ 1,500,000

Asset 2: at $ 1,800,000

Asset 1: at $ 2,300,000

Asset 3: at $ 2,800,000

Projects that could be carried out with budget

The budget is $6,800,000 dollars

Manageable projects include; asset 1 and asset 3 totaling to $5,600,000.

Future of assets not developed

These assets are sound and very feasible. However, compared to the cost of assets, their operating costs are relatively high. A positive strategy should be to reduce the operation costs before investments can be made. Just like option 1, the other options should use minimal resources to run into operation. This will increase profits while minimizing costs.

The Prioritization Process

This process helps reduce the time for management to solve general problems of resource allocation (Menshikh & Avsentev, 2018). The process is a combinatorial problem, putting together three levels into solving to implement solutions for specific problems. The process performs sets of tasks to form control actions on the managed system. The actions are performed in order. Execution time for each action is dependent on the number of resources allocated where organizational systems act as decision-makers. Many and different resource allocation options may be used to reduce the performance time of all actions. After this, a mathematical model for resource allocation optimization is done to reduce the time taken to make managerial decisions through the creation of algorithms for solving problems concerned with the general resource allocation.

Problems are described and resource allocation options are selected. Actions are assigned to certain groups of performers and in turn, there is a group of sub-actions or partially ordered operations that can be performed from the respective group. Resource allocation means an increase in the number of group performers. This may in turn lead to a reduction of action time performance by groups to which performers can be added, therefore the overall performance of the series of actions. Then there are several steps; the first being the duration assessment of the performance of individual actions depending on the performers per group. The second step is assessing the overall performance time for all actions depending on the quantitative composition of performers group.

The third step involves finding the allocation of the available resources by groups that minimize the overall performance time of all actions.

The process ensures that the best assets are given priority in a field where options are competing. The chosen options put into consideration different aspects necessary for consideration during asset development. For the first option, asset 1, the cost of investment is relatively high. The asset is expected to run for 50 years and the value of the investment is not far from the asset's cost. This, therefore, means that there will be low operational costs. This is a good investment. This is mainly because of the low operational costs. Option 3 represents an asset that is resource-intensive but uses low operational costs. The return on investment will be good owing to the low operational costs. The asset also runs for a long period making it very profitable. Overall, the two assets are expected to do better than the others and give better returns.

Future improvements would include an addition in the lifespan of the assets. An increase in the number of years means that the asset will be profitable for longer. There would be also a reduction in the costs of operation as a strategy to maximize profits. The cost of assets would also go down to allow stakeholders to invest in many assets to distribute risk as well as getting profits from many assets. This would also mean more profits from average assets. Finally, more options could be considered to make more informed decisions due to the presence of many options.

References

Asset Allocation - Overview, Examples, Strategies for Asset Allocation. (2020). Retrieved 27 May 2020, from https://corporatefinanceinstitute.com/resources/knowledge/strategy/asset-allocation/

Menshikh, V., Samorokovskiy, A., & Avsentev, O. (2018, March). Models of resource allocation optimization when solving the control problems in organizational systems. In Journal of Physics: Conference Series (Vol. 973, No. 1, p. 012040). IOP Publishing.

Meyer Zu Wickern, Vincent. (2019). Challenges and Reliability of Predictive Maintenance. 10.13140/RG.2.2.35379.89129.

Sullivan, G., Pugh, R., Melendez, A. P., & Hunt, W. D. (2010). Operations & maintenance best practices-a guide to achieving operational efficiency (release 3) (No. PNNL-19634). Pacific Northwest National Lab. (PNNL), Richland, WA (United States).

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