apmOptimizer™ Overview

About apmOptimizer

In today’s challenging business climate, enterprises are under pressure to increase efficiency and bottom line. Existing asset management tools do not provide any optimization methods to reduce maintenance costs and life cycle costs (LCC). Without a powerful logistics and maintenance optimization tool, managers are trapped in a trial-and-error paradigm that leads to losses, useless expenditures, and missed ROI objectives.

BQR’s apmOptimizer is a unique logistics and maintenance optimization tool that enables engineers to model the existing asset maintenance concept and run an optimization process that recommends new cost saving logistics and maintenance policies.

Features

  • The only solution which simultaneously optimizes the logistics strategy and maintenance policy
  • BQRʼs algorithms are superior to existing commercial algorithms
  • apmOptimizerʼs reliability-based algorithms use exact analytical calculations (not Monte-Carlo simulations) for predictive maintenance
  • apmOptimizer’s model can handle large and complex systems with ease
  • Enables scheduling preventive and predictive maintenance actions in a way that maximizes asset availability
  • Generates high savings on spare parts while ensuring asset confidence and availability requirements

ADD-ONS

PACKAGES

  • LCC+ RA
  • LORA
  • Scheduled Maintenance
  • PdM-Predictive Maintenance
  • Inventory optimization
  • Resources Optimization
  • RCM
  • MSG-3
  • Field Data Analysis

apmOptimizer Optimization Software


apmOptimizer models asset behavior and incorporates RCM methodologies for logistics and maintenance optimization. This optimization process produces new maintenance policies for maximizing availability and minimizing Cost of Ownership over the product’s life-cycle.

Several unique algorithms are implemented to find the optimal solution. apmOptimizer is the only analytic optimization tool that is able to model large-scale systems over a short timespan.

Thanks to advanced modeling capabilities, apmOptimizer can produce detailed and realistic models of both in-design and running assets.

Field maintenance and failure logs can be analyzed by BQR-Digital. The analysis results can be used by apmOptimizer in order to increase the model accuracy of operational assets.

Based on this highly realistic model of the existing maintenance concept, and using unique optimization algorithms, the apmOptimizer solutions provide logistics and maintenance optimization for the following aspects:

 

  • Inventory Optimization
    apmOptimizer inventory optimization identifies the most cost-effective spare combination for the given asset requirements / constraints. The asset model accounts for system redundancies, system hierarchy and shared stocks.
  • Maintenance Optimization
    The apmOptimizer maintenance optimization solution is a powerful tool that analyzes existing maintenance behavior and produces an optimized maintenance policy. This facilitates a transition from corrective to preventive maintenance by adjusting the maintenance and inspections schedule. The process results in an average reduction of 35% in life-cycle maintenance costs.
  • ILS Optimization
    The apmOptimizer ILS solution provides an extended implementation of Level Of Repair Analysis (LORA) i.e. choosing the optimal stock sites, repair shops, OEMs and transportation routes. Furthermore, a repair / discard policy is also provided for each item in the asset. The logistical optimization enables either improving asset performance under a budget constraint, or achieving the required availability.

apmOptimizer Optimization Goals

apmOptimizer conducts optimization according to two main parameters: Required asset availability and budget constraints. The Spare, ILS or maintenance optimizations provide an optimal policy that either achieves the required availability at a minimal cost, or reaches the highest availability under a specified budget constraint.

Optimization Process and Integration

apmOptimizer allows the user to define several scenarios, optimize them and compare their costs, performance and availability.

The final output consists of a set of recommendations for Optimal Preventive and Predictive Maintenance schedules, Optimal spares quantities, Optimal resources allocation, and Optimal levels and maintenance sites.

Designed to interface with most Enterprise Asset Management systems (EAM, CMMS, ERP, CAD), the apmOptimizer enables data import / export in order to easily model asset behavior and communicate maintenance policy recommendations back to the asset management system.

The ApmOptimizer solution has already helped many companies around the world in a large range of industry sectors: Aerospace, Aviation, Automotive, Railways, Chemical, Gas and oil, Energy plants, Electronics, Consumer Electronics, Semiconductors, Defense, Medical and more.

apmOptimizer Workflow

A schematic representation of the apmOptimizer workflow and its modules is shown below:

ApmOptimizer asset maintenance optimization

 

Key Features

  • Maximizes Asset Availability
  • Minimizes Asset downtime and downtime damage
  • Provides a clear picture of Asset KPIs
  • Minimizes Asset Life Cycle Cost
  • Optimizes Level of Repair, maintenance level and locations
  • Optimizes spare parts quantity to satisfy availability requirements
  • Optimizes resources allocation to satisfy availability requirements
  • Optimizes preventive and predictive maintenance
  • Improves maintenance processes and maintenance resource utilization

 

What Makes apmOptimizer Better?

  • Highly realistic modeling capabilities, from single item level up to Asset Corporate level
  • Optimization performed at Asset Level for Optimal Asset Performance
  • Unique algorithms providing exact solutions instead of Monte-Carlo based trial-and-error.
  • Accounts for non-exponential failure rate distribution
  • Bundles maintenance tasks to minimize downtime
  • Compares alternative vendors and supply routes
  • Can be used with ERP / EAM / CMMS tools
  • Interoperability between CARE and apmOptimizer tools through Core Database