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apmOptimizerTM Professional Package
The apmoptimizerTM Professional Package satisfies the requirements of all the diverse Electro-Mechanical Industries. For this reason we decided to include the PMO and PIO described below as part of this complete Maintenance Package. apmoptimizerTM allows users from Electro-Mechanical industries to perform complete maintenance optimization analysis, including the setting of the best suited Preventive Maintenance and Inspection schedules.
apmoptimizerTM Pro Includes the apmoptimizerTM-Basic modules:
LCC: Life Cycle Cost
ORLA: Optimum Repair Level Analysis
S2A: Sparing to Availability
R2A: Resurces to Availability
FMEA: Failure Mode Effects Analysis, Basic
FTA: Fault Tree Analysis, Basic
PRA: Probabilistic Risk Assessment
RBD: Reliability Block Diagram, Basic
CAfdE: Field Data Analysis
apmoptimizerTM Pro includes the additional modules:
FMECA: Failure Mode Effects and Criticality Analysis, Advanced
FTA: Fault Tree Analysis, Advanced
RBD: Reliability Block Diagram, Advanced
PMO: Preventive Maintenance Optimizer
PIO: Periodic Inspections Optimizer
RCM: Reliability Centered Maintenance
DRP: Design-Reliability-Prediction
Life Cycle Cost Analysis
Life Cycle Cost Analysis (LCC) is an essential decision support tool for controlling the initial and the future cost of any system ownership. If your organization acquires or operates complex, high-cost systems (e.g. building, plant equipment, vehicles etc.) operating and supporting cost may exceed your expectation. LCC can be used to evaluate the cost of a vast range of projects, from a complex site to a specific system component.
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
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In the design phase:
- Design the optimal maintenance structure in advance
- Developing system maintainability and specific system requirements
In the maintenance phase:
- Quantifying and justifying modification, upgrades or replacement solution
- Introducing early stage maintenance alternatives to decrease cost or increase performance and availability
- Making cost and performance trade-off decisions
- Quantifying cost saving strategies
Datasheet
- 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
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Optimum Repair Levels Analysis
| In the design and maintenance of modern equipment and systems, adequate attention must be given to Optimum Repair Level Analysis (ORLA). ORLA is a unique, easy to use decision support tool designed to assist management through an interactive process, to analyze maintenance concepts, alternatives and procedures.
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.
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Key Benefits of the ORLA
- System maintenance and logistic costs reduction
- Optimization of system/equipment repair cost during its life cycle
- Increased productivity
- Trade-offs of various maintenance repair alternatives
- Increased availability and reliability of a system
- Optimal inventory locations
Sparing to Availability
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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.
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Key benefits of the S2A module
- Reduces and optimizes inventory costs
- Evaluates 'pooling' options and shared stock strategies
- Justifies basis for carrying inventory for certain required availability
- Compares alternative vendors and supply routes
- Reduces the risk of running out of stock
- Optimizes the appropriate purchasing schedule of spare parts
Benefits in the design Phase:
- Creates the basis for spare parts quantity to support customer Service Level Agreement (SLA)
- Assists designers to evaluate spare parts cost and quantity during system life cycle
Benefits in the maintenance Phase:
- Provides the basis for creating initial and yearly spare part quantities
- Enables maintenance personnel to identify logistic problems within the supply chain
Datasheet
- 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
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Resources to Availability
The goal of any organization’s management professionals is to maintain an optimal number of resources in the most efficient possible manner. Resources include personnel, support, equipment, tools, facilities and materials. The R2A provides a set of easy-to-use tools that assist management professionals to optimize and meet system availability demands in the most cost-effective way.
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
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Datasheet
- 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
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Failure Mode and Effect Analysis (FMEA) for Maintenance Optimization
FMEA is a method, which supplements the existing and the proposed maintenance strategy. The purpose of FMEA is to identify potential failure modes and effects before failures occur as well as their reasons in order to evaluate the probability and significance of the occurrence and consequently, produce a plan to deploy appropriate maintenance actions.
It is more practical to estimate likely failure modes and sequences in advance, or simulate failures in an experimental situation rather than allowing a failure to occur before a maintenance plan has been instated.
For advanced FMECA please click here
Fault Tree Analysis
Fault tree analysis has been used by a wide range of engineering disciplines as one of the primary methods of predicting system reliability and availability parameters. A fault tree is a pictorial representation of logical relationships between events and it can be used to represent a combination of events that will lead to system failure, called as top event. FTA in the apmoptimizerTM package is used for risk assessment, discovering asset failure and ranking the effects of item failures and human error. The FTA can be used to develop an effective maintenance action to minimize the probability of the undesired event.
For advanced FTA please click here
Risk Assessment and RCM
RCM is a process to determine maintenance activity requirements for critical components and equipment in order to prevent potential failures or to control failure modes. This method uses logic tree analysis to identify maintenance requirements according to safety and operational consequences of each failure. By assigning priorities to components, this method establishes optimized maintenance programs and provides necessary technical basis. Maintenance resources are then used in an effective manner focusing on functional reliability of these components. The process seeks to make best use of different maintenance techniques where unnecessary costly maintenance actions and associated maintenance induced failures can be avoided.
apmoptimizerTM Probabilistic Risk Assessment (SPRA) ensures that critical systems and assets and components are accurately established. PRA is a systematic and comprehensive methodology to evaluate risks associated with asset life-cycle for assessing, in a realistic manner, the likelihood of undesired events. Risk in a PRA is defined as a feasible detrimental outcome of an activity or action. In PRA, risk is characterized by two quantities:
- The magnitude (severity) of the possible adverse consequence(s), and
- The likelihood (probability) of occurrence of each consequence.
Consequences are expressed numerically and their likelihoods of occurrence are expressed as probabilities or frequencies. The total risk is the sum of the products of the consequences multiplied by their probabilities.
Hazard and Operability Study (HAZOP) HAZOP is a fundamental hazard identification technique, which systematically evaluates each part of the system to see how deviations from the design intent can occur and whether they can cause problems (IEC 61882). The technique aims to stimulate the imagination of designers and operators in a systematic manner so that they can identify the cause of potential hazards in a design
RBD - Reliability Block Diagram
A reliability block diagram is a graphical representation of how the components of a system or an asset are connected reliability-wise. The simplest and most elementary configurations of an RBD are the series and parallel configurations. In a reliability block diagram each component of the system is represented as a block that is connected in series, and/or parallel, based on the operational dependency between the assets or their components.
For advanced RBD please click here
Field Data Analysis-MTBF
CAfdE provides a simple tool for analyzing field or test failure data (Weibull).
Failure data can be collected from various IT tools such as ERP, CMMS and CRM.
CAfdE calculates field MTBF & reliability growth
The program contains MTBF goals and if one of the observed MTBF items is lower than the required MTBF, than the program will present a warning.
The results are than saved in the Core database and can be used by the CARE or CAME modules to:
- update the RAMS/ILS reports and
- to optimize the maintenance concept.
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Datasheet
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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
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PMO - Preventive Maintenance Optimizer
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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.
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Key benefits of the PMO module:
- Continuous review of maintenance strategy
- Preparation of reliable and comprehensible maintenance budgets
- Reduction of corrective maintenance measures, i.e. run-to-failure strategy
- Rearrangement or removal/ of maintenance tasks to achieve cost effective and availability optimization
- Minimizing maintenance effort duplication when performing preventive maintenance tasks at different time schedules
Benefits in the design phase:
- Creates a basis for designers in order to prepare maintenance manuals and preventive maintenance schedules
- Enables designers to select appropriate support equipment for preventive maintenance
Benefits in the maintenance phase:
- Reduces maintenance and resources cost
- Bundles and optimizes preventive maintenance tasks to achieve maximum system up-time
Datasheet
- 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
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PIO - Periodic Inspections Optimizer
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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
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Datasheet
- 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.
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Reliability Centered Maintenance
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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.
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Key Benefits of the RCM Module:
- Simplifies the RCM process
- Enhances the RCM by adding PMO results
- Improves maintenance efficiency
- Reduces maintenance failure risk
- Minimizes maintenance costs
- Meets with safety and environmental goals
- Meets with operational goals
Answers to:
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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.
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