- Title
- The development of an optimised decision based methodology for the replacement timing of frontline equipment utilised within the quarrying industry
- Creator
- Basson, Kenneth Mervyn
- Subject
- Decision making
- Subject
- Industrial equipment Industrial equipment -- Maintenance and repair
- Date Issued
- 2018
- Date
- 2018
- Type
- Thesis
- Type
- Doctoral
- Type
- DBA
- Identifier
- http://hdl.handle.net/10948/23647
- Identifier
- vital:30592
- Description
- At present, frontline equipment employed at B&E International, and operating within the quarrying sector is typically replaced as soon as the operating expenses are deemed to be excessive. From a capital budgeting perspective, the trigger for signalling the replacement of equipment occurs when prescribed operating cost performance metrics are violated. In some instances, a further consideration for motivating the replacement of equipment is when the perception arises that the nonavailability of the equipment employed, results in financial losses being incurred by a company. It can therefore be argued that the current equipment replacement timing methodological approach adopted at B&E International is suboptimal in nature. The situation is further aggravated by the fact that in many instances, escalation of commitment manifests itself whereby unnecessary capital is repeatedly invested in order to extend the life of an asset resulting in a situation occurring whereby the required level of investment return is not achieved. In the event of these situations arising, the decision to replace an asset is prolonged as a result of the suboptimal investment decisions being made. The primary focus of this study is to provide a methodological equipment replacement framework that is based upon sound capital budgeting fundamentals. A comprehensive literature review of capital budgeting approaches that specifically focus on the optimal replacement timing of frontline quarrying equipment, did not yield any relevant studies that have been undertaken in this regard. This study did however investigate contemporary equipment replacement approaches based upon a capital budgeting paradigm and highlighted their respective limitations. Convincing evidence obtained, indicated that the most widely accepted method of identifying the optimal replacement timing of equipment occurs when the economic life of the asset is attained. This in itself would therefore infer that a cost minimisation approach is the most pervasive methodological approach adopted in order to identify the optimal replacement timing of equipment. When considering capital investment based decisions, it was found that the discounted cash flow based methodologies are the most widely used and accepted approach applied in the mining industry. Notwithstanding this, one major caveat manifests itself in that when considering the optimal replacement timing of front line equipment within the quarrying industry, the inclusion of uncertainty, flexibility and the associated financial risks was not evident. In order to model these effects, a probabilistic Net Present Value (NPV) approach was adopted and the required Discounted Cash Flow (DCF) models were constructed. Given the uncertainty of the expected cumulative R&M profiles for the asset classes constituting this study, an extensive statistical analysis was carried out in order to establish the required predictive Repair and Maintenance (R&M) models required for the DCF analysis by means of regression analysis. Further regression analyses were conducted in order to model the overall availability and utilisation metrics for the respective asset classes included in this study. The consequence of incurring downtime was investigated and the resultant DCF analysis yielded a significant impact on the Free Cash Flow (FCF) generated by the respective assets. The magnitude of the incurred consequential financial losses incurred as a result of the respective downtime was found to be significant when considering frontline equipment. In order to model the effect of, and the extent to which, the respective independent variables influence the static NPV outcome, a sensitivity analysis was performed. From this, the influence of the independent variables constituting the NPV model employed in this study, were observed. A Real Options Analysis (ROA) approach was initially employed in order to model the effects of FCF uncertainty and the results of carrying out this analysis indicated a minimal influence on the static NPV model referred to earlier. It was therefore concluded that from an equipment replacement timing perspective, the ROA approach did not provide a robust and accurate representation of the probabilistic NPV outcomes anticipated. In order to address these perceived shortcomings, an Monte Carlo Simulation (MCS) model was constructed and the requisite probability distribution functions representing the most influential independent variables determined from the sensitivity analysis were identified and subsequently analysed. The results of the MCS analysis yielded the expected NPV outcomes that were found to be far more conservative compared to the static NPV outcomes referred to previously. Furthermore, the concluding findings of this study indicate that in order to estimate the optimal time to dispose of an asset, a static NPV analysis must first be modelled and thereafter a probabilistic NPV analysis. The respective uncertainty aspects over the lifespan of the assets should be identified to be incorporated into the MCS model. This methodological approach therefore opposes the use of a strictly deterministic based approach and rather predicates the use of a probabilistic NPV based framework. This study further concluded that traditional DCF approaches fail to consider management flexibility in terms of adapting to uncertainty and to also reduce the possibility of “escalation of commitment” occurring as a result of sub-optimal equipment replacement timing decisions by management. The use and acceptance of the traditional DCF approaches are acknowledged, but in order to develop an equipment replacement methodological approach that considers uncertainty and risk on the one hand and also allows for the incorporation of real data over the assets lifetime on the other, the use of an MCS probabilistic NPV based model was found to be the optimal approach to be adopted. The result of updating the static NPV model with updated data as soon as it is obtained enables one to generate accurate probabilistic distribution functions required for the subsequent MCS analysis. By adopting this approach the study has concluded that one can obtain realistic and accurate NPV forecasts from the anticipated FCF estimates. The principal conclusion obtained from this study is that the optimal time in which to replace front line assets employed at B&E International is when the probabilistic net earnings profile, viz., NPV of the equipment is maximized.
- Format
- xix, 321 leaves
- Format
- Publisher
- Nelson Mandela University
- Publisher
- Faculty of Business and Economics Sciences
- Language
- English
- Rights
- Nelson Mandela University
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