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Overview

apmOptimizer ^(TM) - Improving Maintenance Effectiveness and Reducing Resource Waste

An Expert System for Maintenance Planning Optimization
In today’s competitive global business climate, enterprises are under increasing pressure to reduce costs in order to meet tougher performance and production goals with maximum return on asset investment. Unplanned equipment downtime greatly affects the earnings of any enterprise and must be minimized. Risks should also be minimized, as well as the costs of keeping those risks low. Asset maintenance is a significant cost factor for companies to improve performance and maintain availability during the asset’s life cycle. Maintenance is a key factor for succeeding in asset management. apmOptimizer is an expert system for maintenance optimization which allows manufacturers, service-providers and Maintenance Repair and Overhaul (MRO) organizations to scientifically analyze, improve and optimize all relevant aspects of maintenance strategies. These strategies involve planning and execution of the following factor: Repair or discard Corrective / preventive / predictive maintenance Spare parts allocation & procurement Human resources Support & Test Equipment Tools and materials.   Using apmOptimizer typically leads to an average savings of 35% on maintenance and logistic costs as well as reducing loss of production and damage costs.

apmOptimizer is a powerful decision support tool, which allows a wide range of enterprises in various sectors to analyze and optimize their asset usage. apmOptimizer allows companies to quantify the maintenance costs drivers versus the availability / utilization of an asset, and vice versa. By using apmOptimizer, an optimal solution is recommended where the cost is minimized and the availability/performance is maximized. apmOptimizer allows multiple scenarios comparisons to perform “spent cost” and “performance” analysis of the asset over its anticipated life span.

Key Benefits

• Can be used under ERP / EAM / CMMS tools
• Reduces maintenance and logistic costs
• Reduces resource waste
• Increases availability and performance
• Minimizes the system down time damage
• Avoids unplanned downtime
• Increases productivity and profitability
• Minimizes the system / equipment repair costs during its life cycle
• Recommends repair or discard policy for each assembly   
• Recommends repair sites and stock sites for each assembly  
• Recommends equipment repair only when needed
• Optimizes preventative maintenance and inspection schedules
• Groups preventative and inspection tasks in one combined cycled scheduled time slot to minimized down time 
• Keeps equipment in top working condition
• Minimizes spare parts kept in stock
• Evaluates 'pooling' options and shared spare part strategies
• Minimizes the total cost of purchasing, storing and transporting spare parts
• Creates a basis for spare part logistics
• Compares alternative vendors and supply routes
• Reduces probability of running out of stock
• Reduces human resource costs
• Reduces support equipments, tools and materials costs
• Enables an improvement in maintenance personnel utilization
• Creates a basis for maintenance personnel, support equipments, tools, facilities and materials records

apmOptimizer is a Trademark of BQR

Datasheet

apmOptimizer Maintenance Concept

A maintenance concept is a general description of the maintenance tasks and resources required in support of a given asset or system and the designation of the maintenance level (organizational, intermediate, and depot levels) for every assembly within the asset.
It includes basic policies such as repair/discard decisions, maintenance and spare parts locations and logistic support requirements (e.g. facilities, personnel, tools and transportations). In short, it defines in detail the procedures and resources necessary for maintenance support for the asset . 

A major element in defining a Maintenance Concept is the structure of maintenance levels to be used in support of an asset. Maintenance, both corrective and preventive, may be achieved at the site where the system is used, referred to as the organizational level, and/or at an intermediate level and/or at manufacturer’s plant facility, the depot level. These levels are dictated by task complexity, personnel skill level requirements, test equipment and special facility needs.
Usually the initial Maintenance Concept consists of manufacturer recommendations, or experience or short-term, competitive concept studies. At this phase alternative concepts should be evaluated for feasibility to provide the basis for assessing the merits (i.e. advantages and disadvantages, Life Cycle Cost, Availability and degree of risk). apmOptimizer evaluates Maintenance Concept alternatives to provide the most efficient system concept.

apmOptimizer Integration in IT systems

 

apmOptimizer provides end-to-end asset maintenance optimization. apmOptimizer can be easily be integrated to any database of Legacy, EAM, ERP or CMMS system and to virtually any next generation software that may be available in the future. apmOptimizer periodically collects relevant data from the management system database. Such data may include: failure information, maintenance tasks, spare parts transaction, financial data, etc. apmOptimizer provides the analyzed and optimized recommendations via a apmOptimizer interface or transfer data directly to other maintenance management systems.

 

Traditional Mistakes in Implementing Asset Management Systems

A common mistake made by manufacturers and service organizations is to utilize extensive spare parts optimization software packages for the existing maintenance concept; without checking the option of changing the entire Maintenance Concept to reduce total Life Cycle Costs (LCC).
Maintenance concept decisions such as repair / discard or scheduled/unscheduled maintenance can affect the stock levels and the total LCC. Optimization of spare parts alone, without considering maintenance concepts matters collectively (i.e. ORLA, PMO, PIO, R2A and S2A) will usually yield inventory cost saving. However, at the same time, LCC will be increased beyond the inventory savings.

Correct spare parts optimization can only be achieved following maintenance concept optimization to reduce total asset LCC, without lessening asset operational availability. The optimization process provided by apmOptimizer meets these criteria to the fullest extent possible.

Another common mistake is determining the number of spare parts needed in inventory based on average MTBF. The average MTBF is calculated by adding up the operational hours and dividing by the number of failures. This way the user will learn years later that he may have too many spares from one item and insufficient spares for another, while never having the exact number needed.

apmOptimizer provides a complete solution that at first optimizes the maintenance concept and then takes into account the failure time distribution for each item. As a result, the user is able to calculate the optimal number of spare parts needed initially and on an annual basis.

apmOptimizer Reliability Analysis in Maintenance Optimization

Failure rates of an asset are usually age-dependent. The actual amount of time between failures will depend on many factors including: operating conditions, environmental factors, vibration, stress (electrical, mechanical, etc.), usage profile, and other factors. Severe conditions such as high ambient temperatures or a heavy load can significantly shorten component lifetimes and reduce maintenance and component replacement intervals. Observing the failures that have occurred in the field will reveal the actual reliability performance of the asset. Reliability is defined as the probability that an asset will perform its required function under stated conditions for a specific period of time. Predicting failure rate with some degree of confidence under present normal usage depends on correctly choosing the distribution that matches the failure data. A key requirement for maintenance optimization is to have a fundamental understanding of the failure time distribution and failure modes of a component within the asset. By understanding the failure modes and looking at the probability and the distribution of failure of a particular sub-component, the best judgment can be made regarding the appropriate long-term and short-term corrective actions. Failure rates and distribution directly affect the human and equipment resources, spare quantities, optimal preventive maintenance intervals, and optimal inspection intervals. Obtaining a more reliable asset performance requires more preventive maintenance and inspections, which in turn drives up costs and in some cases reduces asset availability. However, less preventive and predictive maintenance means more forced outages, higher repair costs, increased loss of production and damage cost. apmOptimizer provides the most balanced solution for performing the minimal maintenance needed to achieve maximum availability at minimum cost. The reliability data to be used in apmOptimizer can be retrieved from two sources. The first one is from prediction performed by the manufacturer of the assembly and the second is from analyzing field data collected by the operator. For prediction data, apmOptimizer provides the CARE-MTBF or the MRS modules and for field data the CAfdE module.

 

 

apmOptimizer Maintenance Optimization Process:

 

 

Asset Degradation is the slow, usually unnoticed, degradation of an asset’s performance over time. Determining optimal maintenance policy requires collecting data for critical components and equipment. Only by understanding the asset’s degradation, deterioration or failure behavior, as well as the cost of possible solutions, can managers determine the multi-metric optimal maintenance policy. For example, a policy which lets an asset run to failure will result in shut down, followed by corrective repair, may seem to be reasonable. However, optimization based on degradation study might show that an alternative policy, such as prevention or inspections, is far superior. The goal of a Maintenance Optimization Process is to select the appropriate Maintenance Concept for each component within a system, taking into account system availability, costs (LCC), system reliability, risk and safety. apmOptimizer is the ideal optimization tool for providing maintenance solutions from the component or equipment level, up to the entire plant or enterprise, or vice versa. In addition, apmOptimizer is able to optimize across any level, such as “for all machines across the organization”. The Maintenance Optimization Process begins with analyzing current asset performance, including the Maintenance Concept with all its maintenance and logistic aspects, and provides the detailed understanding and visualization needed to make the correct decisions. apmOptimizer will review the asset Maintenance Concept for cost and availability, and the outcome will present the best solution for the repair policy (discard or repair and where to repair), maintenance (preventive or corrective), spare part policy (quantities and locations) and resources (support equipment, manpower, facilities and materials). In modeling the current update Maintenance Concept, field reliability data must be collected at the assembly level to enhance predicted component failure rates with real-life experiences. This will update the reliability prediction based on valid historical data. Thereafter, a system model is built to include the infrastructure and all relevant maintenance and cost data. Once the model is complete, the optimization steps can be conducted. The first optimization step is the Optimum Repair Level Analysis (ORLA), which recommends the optimal repair or discard level for each component in the system. For a repairable assembly, fewer annual spare parts are needed; for a discarded assembly, more annual spare parts are required, but there is no repair cost. The next step is the PMO followed by the PIO, recommending the best schedule for preventive and inspection maintenance. The last optimization steps are the R2A/S2A that recommends the optimized resources and spare parts for achieving the required availability with minimum cost. During each step, Life Cycle Cost and operational asset availability or performance is monitored. All recommendations should at least adhere to the minimum required performance levels. If there are some ways to achieve the requirement, apmOptimizer recommends the solution resulting in the lowest costs. Based on data from actual usage and experience; the model and analyses should be updated to incorporate adjustments to the maintenance concept. Maintenance optimization can be achieved only when dealing with all maintenance aspects simultaneously. Handling one issue at a time will not effectively reduce the maintenance cost. By performing all apmOptimizer steps, the LCC will be reduced while availability will comply with the requirement or will be increased.

  

 

apmOptimizer Workflow

 

 

 

The first step is to model the existing maintenance concept. The second step is to fill up the maintenance model with reliability figures. The reliability figures can be retrieved by using the CARE predictive software package, or by the CAfdE module within the apmOptimizer package for field data analysis. CARE® is another software tool developed by BQR to help designers improve product reliability during the design stage. The failure rate distribution of each assembly or component, coming either from CARE or from CAfdE is stored in the core database. apmOptimizer will use this data and will provide optimal recommendations to the ERP/EAM/CMMS for management decisions.    To be able to create world-class optimized maintenance organization, precise information is needed combined with the ability to scientifically analyze, improve and optimize all relevant aspects of maintenance data. Combining asset management system (ERP/ CMMS /EAM) with the apmOptimizer tool into one seamless system will have positive effects on optimized equipment up-time, lower maintenance costs, and improve overall plant efficiency.    Information regarding asset maintenance failures is not always correctly recorded (coded) into the maintenance system. The quality of the records transferred by the asset management system are monitored and analyzed by the apmOptimizer system. In case reliability data are not correctly provided by the asset management system, CARE package (Provided by BQR) shall provide the predicted missing reliability data to build the initial maintenance concept by the apmOptimizer.  After defining the initial maintenance concept, the apmOptimizer procedure should be used and the optimal solution is stored in the Core database.  In order to update the maintenance concept with new field data periodically, weekly, bi-weekly or monthly, the collected field data from the last date until current date is analyzed by CAFDE and apmOptimizer updates the failure rates and distributions in the core database. The apmOptimizer is then run again and new recommendations can be provided to the ERP system for final approval. This method assures maintained results accuracy as time progresses.

 

 

 

The apmOptimizer Suite consists of the Following Key Modules:

 

 

Life Cycle Cost (LCC) Analysis
LCCA provides a methodology for computing the overall cost of maintenance concept or acquisition alternatives. It indicates the overall cost of owning and operating an asset in relation to its anticipated life span. Typical acquisition costs for a system may include design and development, operation, corrective maintenance, preventive maintenance, spare parts, downtime and damage, loss of production, disposal and any other costs. apmOptimizer shows all cost drivers on Pareto tables which drill down to the lowest assembly level.

Optimum Repair Level Analysis (ORLA)
ORLA is a unique, easy to use decision support tool designed to assist management through an interactive process that analyzes maintenance concepts, alternatives and procedures. The ORLA module recommends whether an item should be considered under a discard-at-failure or repair policy. ORLA recommends optimal repair and stock site locations and means of transportation (such as land or air) between the system's maintenance facility locations (forward stocks, central stocks, repair sites, vendors etc.). An optimum maintenance repair policy is achieved over a system's total life cycle based on required system availability constraints and minimum cost.

Preventive Maintenance Optimizer (PMO)
PMO assists managers to evaluate different options, and recommends an optimal Preventive Maintenance (PM) schedule for the entire system or a component within the system. This schedule combines PM of different parts in a shared PM sessions (if it is profitable) to reduce removal – assembly, access and check operations, number of system stops and total down time. PMO provides the required availability as well as minimal corrective and preventative maintenance cost, down time and failure damage cost.

Periodic Inspections Optimizer (PIO)
PIO assists in decision-making based on asset field conditions rather than fixing the asset when failure occurs. Since system or equipment degradation is hidden, data can only be gathered through equipment monitoring devices or with inspection-scheduled activities. If damage due to failures is significant, the inspections should be frequent enough to detect critical degradation before the actual failure and damage occurs. The PIO module recommends the optimal inspection intervals to provide the required system availability with minimum maintenance cost (inspection, restoration, down time and damage costs).

Sparing to Availability (S2A)
S2A checks all spare part policies against the required system availability. It recommends the optimal number of spare parts for each replaceable part number and multiple stock sites (Exchange and Forwards) in the maintenance site map. Required system availability is achieved, if it is possible. Otherwise the maximum feasible availability is calculated. The S2A enables minimizing the total cost of spare parts initially purchased, and of their handling during lifetime, taking into account repair sites, repair delay time (if applicable), lead time, transportation, packing, down time costs and others.

Resources to Availability (R2A)
The goal of the R2A module is to recommend the optimal number of maintenance resources at each maintenance site covering all expected maintenance tasks (corrective and preventive) performed at this site and providing given availability of all serviced systems with minimum service and damage cost. Resources include personnel, support equipment, tools, facilities and materials.

Reliability Centered Maintenance (RCM)
The primary objective of the RCM analysis is to reduce or avoid risk of failures. RCM is an interactive manual process based on traditional methods. It encompasses well-known analysis methods used by maintenance engineers and is intended to determine appropriate failure management strategies. The RCM module contains seven standard questions in an interactive form and uses an interactive decision workflow to achieve accurate recommendations on how to prevent safety related failures. RCM tools include Fault Tree Analysis (FTA), Failure Modes & Effect Analysis (FMEA), and full system restoration cost and damage evaluation for each failure. RCM procedures may use automatically the preventive maintenance recommendations and intervals from the PMO and PIO modules after optimization. The primary objective of the RCM analysis is to reduce or avoid risk of failures.

Maintenance Steering Group (MSG-3 by ATA)
MSG-3 assists air carriers (commercial aviation) to enhance their operational safety. Invented by the Maintenance Steering Group (MSG) of Air Transport Association (ATA), MSG-3 is a method of developing maintenance/inspection tasks for aircrafts. The apmOptimizer-MSG-3’s decision-making logic is applied to each significant item categorizing the failure as a safety, operational and/or economic failure in nature. Each category follows its own route in the logic flow and leads to a preventative or inspection schedule to reduce the safety risk.

LSAR for MIL-STD-1388
Logistic Support Analysis Record is a relational electronic database used by defense industries to document the results of the LSA associated with MIL-STD-1388/2B. The LSAR provides a way to produce ad hoc queries for the use of all system life cycle phases as an aid in developing logistics procedures. LSAR contains various logistical and RAM data such as maintenance concept, including corrective and preventative maintenance tasks, tools, personnel, facilities, etc. apmOptimizer-1388 can import a ready 1388 database, to optimize the maintenance concept and to export the results into a 1388 format. apmOptimizer-1388 contains hundreds of checking rules to validate the 1388 data.

Field Data Analysis (FDA)
FDA is the interface between the ERP/EAM/CMMS tool and apmOptimizer. FDA receives in batch mode all field failures, analyzes the occurrence and provides the MTBF estimations and failure time distribution for each assembly/component. This module can run on a daily/ weekly/monthly basis and store the results in the core database for use by apmOptimizer.

 

Key Features

 

 

• One integrated set of tools, which cover all aspects of system performance estimation and maintenance optimization


• Graphical representation of asset maintenance concepts (e.g. maintenance site locations, organizational/intermediate/depot levels, spare parts location)


• Makes extensive use of libraries such as: part numbers, maintenance tasks, failure modes, maintenance resources, personnel, tools, ATE, facilities etc.


• User can easily generate maintenance concept scenarios to evaluate availably and LCC of each scenario.


• Provides optimal maintenance plan for each maintenance site location


• Provides optimal maintenance concept for each part


• Recommends optimal spare parts policy for the entire enterprise


• Provides optimal sparing to ensure maximum availability


• Provides optimal transportation means (e.g. land, air)


• Provides optimal scheduling by grouping preventive and inspection tasks


• Provides optimal preventive maintenance schedule for parts with increasing failure rate (degradation)


• Defines optimal inspection intervals for parts with hidden failure modes (e.g. for safety systems used on demand)


• Recommends minimum set of maintenance resources (personnel, tools, facilities) providing required restoration down time of the systems serviced at a repair shop


• Provides decision support tool to buy or overhaul an asset during its life span


• Interfaces with most ERP/EAM/CMMS and Legacy systems

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