Profit without Risk: MRO Optimization
MRO risk management and profit maximization for complex production systems using simulation modeling and optimization
Get a consultationWhere do complex production chains lose profit in maintenance, repair, and continuity?
Traditional MRO approaches often lead to significant losses:
Complex Chains
Dozens of interdependent processing stages; a failure in one link cascades throughout the entire production chain.
High Cost of Downtime
Every hour of critical equipment downtime (furnace, conveyor, mill) means direct financial losses and disruption of shipment plans – up to $300k/hour in losses.
Limited MRO Budget
How to allocate resources among thousands of technical activities to achieve maximum effect and not "burn through" money?
Hidden Risks
Non-obvious dependencies and "bottlenecks"; which minor repair today will prevent tomorrow's catastrophe and loss of annual profits?
Prioritization Difficulties
Decisions are often made based on experience or intuition, rather than objective data on risks and impact on final profit.
Sound familiar?
Relying on old MRO methods in complex production systems means not seeing the full picture of risks and missing opportunities to protect your profit.
Outdated MRO Approaches: A Hidden Threat to Your Profit
Relying on old MRO methods in complex production systems means not seeing the full picture of risks and missing opportunities to protect your profit.
PM (Preventive Maintenance)
Does not account for actual condition, criticality, and interdependencies. Often leads to unnecessary repairs or fails to prevent failures.
Reactive Maintenance ("Firefighting")
The most expensive approach: unscheduled downtime, urgent procurements, contract disruption. Does not manage risks, only reacts to consequences.
Expert Assessments
Subjective, difficult to scale to thousands of equipment units, dependent on the experience of specific individuals.
Difficulty in Calculating ROI
It is hard to prove the economic effect of preventive measures and link repair costs to the overall profitability (EBITDA) of the chain.
Using outdated MRO approaches leads to profit loss and prevents the full realization of production process optimization potential.
New Solution: Synergy of Optimization and Simulation Modeling
We combine two digital models for superior results: global optimality of the MRO portfolio within budget and detailed visualization of the production system operation and risk consequences.
MRO Problem
Simulation Model
Deep analysis of risk consequences
Optimization Model
Selection of the most profitable activities
Optimal MRO Plan
Result of SM + OM Synergy
- A justified, optimal MRO plan directly linked to profit maximization.
- A reliable picture of residual risks after all countermeasures.
- Balanced decisions without over/underestimating risks.
- Combination of detailed understanding (SM) and optimal choice (OM).
Optimization Model: Selecting the Most Profitable Repairs
Main task: forming an MRO activity portfolio that yields the best financial result within budget and other constraints.
- 1Selects MRO activities where avoidable irrecoverable damage exceeds costs.
- 2Models optimal adaptation of the technological chain during risk realization.
- 3Averages the probability of equipment stops and time over periods.
- 4Analyzes all risk combinations, selects the best portfolio for profit maximization.
Simulation Model: Deep Analysis of Activities and Risk Consequences
Main task: detailed assessment of potential profit losses from various risks and response measures.
- 1Visualizes chain reactions of risks for complex production chains over time.
- 2Simulates emergency response measures with limited chain reconfiguration.
- 3Inventories, production, and logistics are modeled continuously, while accidents are modeled as random events.
- 4The "cost" of risks is calculated separately for each or for selected sets of risks.
Methodology: From Data to Optimal MRO Plan
Our approach combines deep analysis of risk consequences (SM) and mathematical optimization of the activity portfolio (OM) to achieve maximum profit.
Data Collection
Analysis of technological schemes, operating modes, failure history, repair costs, inventories, plans, and economic parameters.
SM Development
Creation of a digital twin for key production chains, configuration of failure logic, repairs, and flows.
OM Development
Construction of a mathematical model for selecting the optimal MRO portfolio within budget, considering SM data.
Validation and Optimization
Model validation against historical data, calibration, launching optimization calculations.
Implementation and Results
Formation of an optimal MRO plan, integration of results into planning systems, monitoring of effect.
Measurable Results: MRO Optimization as a Profit Center
Comparing the simulated MRO plan with the traditional approach shows significant improvements:
3-5%
Reduction in EBITDA losses from downtime
15-20%
Budget reallocation to critical activities
Reduction
Reduction in technological risks
Increase
Increase in Return on Investment (ROI) in the MRO budget
Justification of MRO costs: Example of model analysis
| Code | Equipment Unit Name | Failure Probability | Downtime Duration | % Influence | MRO Cost | Risk-Profit | Model Decision |
|---|---|---|---|---|---|---|---|
| 567002623 | Connecting Path 1 | 10% | 30 | 10% | 100 | 0 | do not pay |
| 8900420023 | Railway Track 1 | 40% | 40 | 100% | 30 | 200 | pay |
| 1230420737 | Railway Dead Ends 1 | 40% | 30 | 100% | 20 | 100 | pay |
| 4560420026 | Railway Track 2 | 40% | 30 | 100% | 50 | 100 | do not pay |
| 7890420031 | Ore Storage | 5% | 10 | 50% | 10 | 5 | do not pay |
| 1010420055 | Conveyor №3 | 20% | 25 | 80% | 45 | 90 | pay |
| 1120420099 | Mill №1 | 30% | 60 | 90% | 150 | 400 | pay |
| 1310420111 | Pumping Station | 15% | 20 | 70% | 25 | 30 | do not pay |
What Determines the Cost of Downtime per Hour
Key factors determining financial losses when equipment stops
Traditionally Accounted Factors
Factors additionally considered by the model
Direct repair costs
Cost of spare parts, materials, and labor for repair personnel.
Lost unit output
Calculated based on nominal equipment productivity.
Simplified income calculation
Product of underproduced volume by price.
Direct penalties
Penalties for disrupting delivery times under contracts.
Personnel salary
Wages of idle production personnel.
Reduction in total system output
Accounting for the impact of downtime on the entire technological chain, including buffers and flows.
Dynamic calculation of lost margin
Calculation based on forecast price minus variable costs.
Domino effect
Accounting for cascading downtimes of adjacent production areas and transport systems.
Effectiveness of buffers and reserves
Real mitigating impact of warehouse stocks and backup equipment.
Urgency surcharges
Additional costs for emergency repairs and urgent logistics.
Impact of downtime moment
Accounting for seasonality, market conditions, and availability of finished product inventory.
Cost of alternatives
Calculation of costs for external purchases to compensate for semi-product disruptions.
Accurate assessment of downtime cost is a key factor for effective MRO planning. Our methodology allows for precise quantification of these parameters and prioritization of activities.
Case Study: MRO Optimization in a Mining Company
Learn how our solution helped a leading mining enterprise significantly reduce costs and equipment downtime.
Client
A large mining company with a fleet of critical equipment.
Situation
- Frequent unplanned equipment downtime
- High costs for emergency repairs
- Suboptimal allocation of MRO resources
- Difficulty in assessing failure risks and their consequences
Project Goals
- 1Reduce unplanned downtime by 25%
- 2Decrease MRO costs by 15%
- 3Optimize the use of repair teams and spare parts
- 4Increase overall enterprise productivity
Implementation
- 1Collection and analysis of failure and repair data
- 2Development of a simulation model for production processes and MRO
- 3Creation of an optimization model for repair planning
- 4Integration of models and scenario risk analysis
- 5Formation of an optimal annual MRO plan
Examples of Model Analysis
Simulation Model Example: Furnace Substation Failure
- Identified cascade effect (warehouse overload, semi-product deficit)
- Quantified damage ($1.2M/hour of downtime)
- Identified bottlenecks and proposed solutions
Optimization Model Example: Annual MRO Plan Formation (Budget $800M)
- Analyzed ~15,000 activities (request $3 billion)
- Calculated cost/benefit ratio for each
- Optimal portfolio of ~3,800 activities selected within budget
Global Experience: MRO Optimization in Large Companies
Examples of applying advanced analysis and optimization methods for MRO and risk management in resource extraction and industrial companies, similar to the approach presented in this case study.
| Company and Size | Economic Benefits | Models Used * |
|---|---|---|
| BHP, $60 billion | Chain savings $1.2 billion | Optimized strategies |
| Shell, $380 billion | 10-20% downtime reduction, 15% cost reduction | AI/ML, simulation models |
| Rio Tinto, $55 billion | Equipment utilization +5-15% | Predictive and optimization models |
| Vale, $40 billion | Savings $7.8 million in 18 months | Predictive models, EAM/APM |
| Copper Mine ~$10 billion | Savings $1.12 million per year | Process and discrete-event modeling |
| Chadormalu $646 million | Savings up to 23.3% of costs | Analytic Network Process (ANP) |
* many models are components or analogs of the integrated SM+OM approach presented earlier.
Download Our Presentation
Get more detailed information about our solutions in a PDF presentation with a more detailed description of our solutions. Download it now or request a PPTX presentation with animation for management demonstration.
Download Presentation
Get a Consultation
Leave your contact details, and our specialist will contact you to discuss MRO optimization opportunities in your company