Cost Effective Support
In these days of economic constraint yet increasing demand for performance, the challenge of cost effective equipment support is pushed to the limits. Two of the most desired objectives in the operation of complex assets are: Reduce operating costs, and Increase equipment availability.
Is this really achievable?
Yes it is! Proper analysis and systematic processes are applied to develop Performance Based Supportability. In these processes, analytical tools are used to develop, store and evaluate information about operational equipment and the support environment. The Canadian Department of National Defence (DND) has developed a set of analytical models over the past 15 years. In a teaming arrangement with Pennant Information Services, these products have been brought to the commercial market.
Is a Windows based product that provides the power of a modern GUI and the sophistication of the embedded proven DND algorithms. OmegaPS Analyzer can determine the best repair policy for equipment and reduce the cost of spare parts. OmegaPS Analyzer comprises three analysis models: Sparing, LORA and LCC.
OmegaPS Analyzer is a stand-alone software tool. However, we have integrated OmegaPS Analyzer with OmegaPS LSAR to provide much of the equipment structure and relevant data for modeling.
System Analysis, the default mode, defines the number of spares required for each item; an optimal allocation of these spares to meet a specified system MOE at minimum spares investment or to meet a specified spares budget with a maximum system MOE.
Mission Analysis mode assumes a number of equipment will be sent on a mission for a specified duration and that only on-site maintenance will be possible. The module provides a list of the spares required to maintain the equipment at a specified "Measure of Effectiveness", such as availability.
Single Item Analysis option was developed for use during initial procurement to quickly provide estimations of the number of spares required for an item, optimal allocations for the spares organization and cost of the spares. It provides a worst case spares scenario for the planner. Single Item Analysis will optimize on the trade-off between components of a given subsystem.
Sensitivity Analysis is available to study how sensitive the solution is to variations in key input parameters, and can be effective either globally or specifically in a sequence of values.
Measures of Effectiveness - Effectiveness is a function of many different factors such as repair capability, stock on hand, and supply delay time. For example, the supply department may be trying to meet their goal of satisfying 90% of all orders received, whereas operations may be trying to ensure that 75% of a fleet is operational on any given day. The MOE to choose is the one that best demonstrates whether the desired system goal is being met.
The OmegaPS Analyzer user can select five possible MOEs:
- Expected System Delay Time;
- Expected Number of System Backorders;
- Operational Availability;
- Intermittent Availability;
- Probability of Mission Accomplishment.
Level of Repair
Systems need to be maintained if they are to be ready for use when required. When new equipment is fielded, decisions must be made as to whether a failed item should be repaired or discarded. OmegaPS Analyzer enables the user to choose a maintenance policy based on experience and design, then use the LORA model to improve it.
The LORA model compares costs between the optimal disassembly and repair policy and the cost of the original maintenance policy. It provides the user with the possible net savings (if any) for each component and the total savings possible if every maintenance recommendation is adopted. The user has the capability of assessing the inflationary effects on the maintenance policy, essential for long term planning. The inflation categories are:
Substantial savings can be realized when an optimal disassembly and repair policy is chosen. The LORA model provides disassembly levels for all components of an equipment. It compares the cost of the optimal disassembly policy with the cost of the original disassembly policy provided by the user. In the case of any replaceable unit, the optimal disassembly policy is conditional on the disassembly policy of its parent.
Support and Test Equipment that can be shared among several items have their allocation to echelons coordinated with the maintenance plans of these items, with infeasible combinations being eliminated.
Although fixed set-up costs are ignored in the analysis, the module does provide the user with the ability to perform marginal value analysis on the costs of facilities with respect to the number of repairs performed at a specified site.
In cases where input data is based on engineering or contractor estimates as opposed to actual data, it is recommended that a study be conducted to determine how sensitive the solution is to variations in some input parameters. OmegaPS Analyzer provides a convenient method of performing sensitivity analysis by providing the user with a wide range of sensitivity factors that are applied at run-time and do not affect the data stored in the databases. Sensitivity analysis can be effected either globally on all values of a parameter or can automatically assess a sequence of changes to a specific value.
OmegaPS Analyzer provides for full trade off analysis to test the "what if?" scenarios. By comparing the results of a comparative analysis against the baseline, the user can determine the relative merit of different decisions.