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BQR's Life Cycle Cost module provides a methodology for computing the overall cost of project alternatives and indicates the lowest overall cost of ownership for its anticipated life span. Typical acquisition costs for a system may include  design and development costs, operating costs, corrective maintenance cost, preventive maintenance cost, cost for spares, downtime and damage costs, loss of production, disposal costs or any other costs.  

Key Benefits of the LCC:

• Trade-offs of various alternatives
• Maintenance and logistic costs reduction
• Evaluation of various options in operation and maintenance
• Accurate total cost forecasting
• System development option analysis
• Break even analysis
• Sensitivity calculations,  Net Present Value (NPV) computations, future and discount cost
• LCC provides early identification of cost drivers

• Calculates cost drivers & full cost of each life cycle phase (investment, development, production, delivery, operation & disposal) as well as, the total life cost using maintenance decisions, defined by user or recommended by CAME optimization modules
• Compares results of different scenarios in united Trade-off table& graph. This comparison enables an expert selection of the most appropriate scenario (the project variants) considering cost & reliability parameters, simultaneously. Usually the better are the reliability parameters, the more expensive is the product & the less expensive is the maintenance. The problem is to select the scenario with appropriate reliability parameters (Mission reliability, Availability, MTBF, Down time) at the minimal total life cycle cost
• Presents Reliability/ Availability vs. Cost results of all considered scenarios/options, thus enabling the user to choose the appropriate scenario/option or to define a new one
• Considers multi-level systems (with blocks indenture breakdown) or 1 level system for ILS proposals
• Provides friendly cost data input for different scenarios
• Generates wide range of reports: summary, detailed, Pareto (sorted by cost drivers) and input data. Each report can be generated by years & as total values. Pareto and detailed reports are effective for analytical purposes, when user seeks the factors of different cost drivers

The ORLA module identifies each item within the system and recommends whether it should be supported under a discard-at-failure or repair maintenance policy.  ORLA recommends on most optimal repair and stock site locations and transportation means between the system's facilities in the maintenance map (e.g. land transportation, air transportation etc.). Optimum maintenance repair policy is achieved over a system's total life cycle based on required system availability and cost constrains. 

Proper planning and control of spare parts inventory is a critical component of an effective asset management program. If the correct parts are not on hand when needed for routine maintenance or repairs, downtime is prolonged. If too many parts are on hand, the company absorbs excessive costs and the overhead of carrying the inventory.

Management of spare parts is often not optimal. In many cases, the value of low-used and unusable parts can be more than 30% of the total value of parts stored. The S2A module checks all spare policies against the required system availability.
 

It recommends the optimal number of spares for multiple possibility stock sites (Source Exchange and Forwards) in the maintenance site map. System availability is achieved for each part number required and its physical location. The S2A enables minimizing the total cost of spares purchased, initially and during lifetime, taking into account repair sites, repair delay time (if applicable), the transportation, packing, down time costs and others.

• Calculates quantity spares for each part number in each stock, providing all required availabilities. The stock site for each block can be defined by user or by ORLA
• Selects the optimal solution providing minimal total cost of spare purchasing, storage, transportation & packaging for all replaceable blocks among all the satisfying solutions
• Calculates maximal achievable availability values for the blocks that the availability requirements can not be satisfied
• Recommends to combine spares with the same part number into one stock location or different locations, according to the least expensive solution
• User can define forward stock in a block replacement site, in addition to central (Exchange) stock locating in any site which provides spares for all blocks of the same part number. If S2A calculates zero spares in a stock, this stock is not recommended
• Considers repair time and delay, spare purchase delay, transportation time, stock delay, mean stock waiting time as a result of possible spare orders queue in the stock
• Considers also sub blocks restoration time (Turn Around Time) in addition to the block repair time for non-replaceable block
• Distinguishes between block reliability models with and without redundancy in the calculation of spare waiting time and sub blocks restoration time

Benefits of the R2A Module: 

• Reduces resources costs
• Evaluates 'pooling' options and shared resources strategies
• Justifies basis for carrying personnel, support equipment, tools, facilities and materials
• Minimizes the total cost of purchasing, storing and transporting spares and resource units, as well as the system down time damage
• Long-term strategic resource planning

• In addition to the optimal number of spares in each stock, R2A calculates the optimal number of each resource unit participating in the replacement or repair of all blocks for each repair site: personnel, support equipment, facilities and materials
• Provides the required availability of the considered system and all blocks the user wants to define
• If the requirement exceeds any feasible availability, the program shows the maximal achieved requirement and minimal achieved restoration time for the system. The user needs to either improve MTBF or decrease the drivers of the restoration time
• The R2A solution minimizes the total cost of purchasing, storing and transporting spares and resource units, as well as, the system down time damage

The main activities are:

• Records operation & maintenance time
• Calculates MTBF estimation and confidence limits
• Recognizes failure time distributions (Weibull)
• Plans MTBF demonstration tests
• Detects MTBF growth/decrease & predicts future MTBF
• Presents tested system as maintenance tree of assemblies
• Collects systems failures data installed in different locations
• Estimates MTBF value, builds confidence intervals for MTBF
• Plans MTBF demonstration tests: sequential, fixed duration and alternative. At each test  moment, shows available decision and calculates expected time to finish
• For all tested blocks recognizes most appropriate failure time distribution from some most  applicable ones. Calculates significance level for all examined distributions
• Performs MTBF growths (or fall) rate estimation using Duane model with confidence probability calculation
• Performs MTBF forecast in a given observation time or needed time to achieve a given target MTBF
• Generates reports in XML and HTML formats: Growth rate statistical analysis, Test time and final  MTBF forecast, and MTBF estimation
• Easy data entry interface for each assembly in the maintenance tree
• Easy data entry for Planned and Performed Preventive Maintenance tasks
• Massive data entry via ODBC driver from other IT system

The PMO Module is important in improving asset or equipment's availability and reliability. Most industries understand the value of reviewing their maintenance strategy over time. Maintenance is one of the largest controllable operating costs in capital-intensive industries.

Unplanned breakdowns can impact an organization in product quality, production capacity, production cost, safety and environmental damage, performance and commercial risk. The PMO module assists managers to evaluate the different options, and recommends an optimal preventive maintenance schedule for a system or component within the system, which provides the required availability as well as minimal corrective and preventive maintenance cost, down time and failure damage cost.

• Recommends Preventive Maintenance (PM) for certain system components having increasing failure rate versus time
• Calculates optimal Mean Time Between PM (MTBPM) for each recommended PM action
• Chooses optimal combinations of blocks that should simultaneously be maintained to reduce the system total down time, assembly, transportation and packaging cost
• Selects optimal common MTBPM for blocks combined together for PM
• Satisfies required Availability, Mission reliability, MTBF, PM free interval (PMU) reliability (PMU survival probability). In case a requirement cannot be achieved, PMO calculates maximal achieved requirement for the above values
• From all PM schedules satisfying the requirements, PMO selects the solution with the minimal total cost. This cost includes PM and CM actions as well as transportation, packaging, spare purchase & storage. It also includes system down time damage & non-system (environmental) damage
• PMO allows users to define one of 6 distribution types (Exponential, Weibull, Lognormal, Uniform, Pareto and Rayleigh) with their parameters, for each lowest system component. They are most important data for PM optimization
• PMO calculates MTBF for all blocks regarding PM restoration

PIO module assists management professionals in decision making based on their field equipment condition rather than fixing equipment when failure occurs, basing maintenance on a set calendar or usage-based schedule. Since system or equipment degradation is hidden, data can only be gathered through equipment monitoring devices or with inspection-scheduled activities.

If damage because of failures is significant, the inspections should be frequent enough to detect critical degradation before the actual failure and damage will occur.
PIO module provides the optimal inspection intervals to provide the required system availability with minimum maintenance cost. Maintenance cost may include inspection cost, restoration cost, down time cost, damage cost etc.

Key benefits of the PIO module:

• Fixes equipment only when needed
• Increase up times
• Avoids unplanned downtime
• Increases productivity and profitability
• Keeps equipment in top working condition
• Reduces maintenance cost
• Provides optimal combinations of different inspections tasks

• Recommends inspection schedule for the failures not evident and not detected immediately with built-in tests (hidden failures). Such failures may be classified in two types: gradual and sudden.
• PIO module allows the user to specify the tasks of inspections performed to check the state of a lowest component (a leaf of the project tree) and to detect its failure, if it occurs. The user can also define tasks on higher levels of the project tree – assemblies, sub systems, system supporting inspection tasks for all their sub blocks.
• Those tasks may present access, disassembly, assembly, testing and other operations necessary for inspection of leaves. All inspection and support tasks are assumed to be performed on operation site and require certain resources – personnel, assembly and measurement tools, materials, utility, sometimes - facility. The cost of such resources may be specified for each operation site and used for optimization.

RCM is an analytical process based on reliability techniques and encompasses well-known analysis methods to determine the appropriate failure management strategies in a maintenance environment. RCM module contains 7 standard questions in an interactive form and uses an interactive decision workflow recommendation. RCM activities include Fault Tree Analysis (FTA), Event Tree Analysis (ETA) and Failure Modes and Effect Analysis (FMEA).

RCM procedures uses the preventive maintenance intervals from the PMO module after optimization. The primary objective of the RCM analysis is to reduce or avoid risk of failures that, if allowed to occur, will adversely impact operational goals, cost, personnel safety, environmental health and mission accomplishment. In order to avoid risk, RCM module provides a decision support tool in regards to perform redesign, preventive maintenance, on-condition maintenance, inspection, etc.

1. What are the functions of the considered item?
2. What are its failure modes?
3. What are the causes & effects of all failure modes in Fault Tree view?
4. What are the end causes of a system failure, their frequencies, probabilities, restoration cost, time and full damage?
5. What are the end effects of each lower cause, their absolute & conditional probability?
6. What actions should prevent the failure mode? (Preventive Maintenance Schedule dialog is opened where user can define PM actions & see the PMO module recommendations)
7. What actions should correct the failure mode if it occurs anyway? (Failure modes dialog are opened with corrective tasks for each step of the failure cause restoration and all required resources: personnel, materials, support equipment, facilities and utilities)

• User interface presents a decision work flow to help user selecting appropriate answers for question 6 and question 7  
• Reports are generated by using input data and user decisions:
  - All required tasks which eliminate critical Lowest Failure Cause by performing Preventive or Corrective maintenance.
  - All required resources for maintenance in each repair site.