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Maintenance Optimization Glossary
Understanding Maintenance Optimization in the Age of AI
| TERM | DEFINITION | CATEGORY |
|---|---|---|
| Asset Availability | The percentage of time an asset is operational and available to perform its intended function over a given period. | Core Strategy |
| Asset Management | The strategic and systematic process of purchasing, operating, maintaining, and upgrading physical assets throughout their lifecycle. | Core Strategy |
| Capacity Planning | The process of ensuring sufficient resources, such as workforce size, skill mix, and geographical coverage, are available to meet forecasted maintenance demand. | Planning & Optimization |
| Constraints | Operational, regulatory, contractual, or resource-related limitations that must be respected during planning, scheduling, and execution. | Planning & Optimization |
| DBGene | DecisionBrain's low-code platform used to build and maintain scalable optimization and scheduling solutions. | Technology & Data |
| Demand Forecasting | The prediction of future maintenance demand based on historical data, usage patterns, and correlated signals such as weather or business activity. | Planning & Optimization |
| Downtime | Period when an asset is unavailable due to failure or maintenance. | Core Strategy |
| Dynamic Adjustments | Real-time modifications to schedules and task assignments in response to operational events such as technician unavailability, urgent work orders, or disruptions. | Operational Execution |
| Facility Services | Services supporting building and infrastructure operations, including maintenance, inspections, and repairs. | Operational Execution |
| Gantt Chart | A visual planning tool used to represent task sequencing, timelines, and dependencies, supporting the optimization of maintenance schedules and turnaround time. | Planning & Optimization |
| IoT & Sensors | Connected devices that collect real-time asset condition and usage data, such as operating cycles or temperature, to support data-driven maintenance decisions. | Technology & Data |
| Key Performance Indicators (KPIs) | Metrics used to measure maintenance and asset performance. | Core Strategy |
| Machine Learning (ML) | Algorithms that learn from historical and real-time data to recognize patterns and improve predictions. | Technology & Data |
| Maintenance Optimization | Use of analytics, optimization algorithms, and AI to define optimal maintenance strategies, schedules, and resource allocation. | Planning & Optimization |
| Tactical Maintenance Planning | Define optimal maintenance plans, typically down to the day/week granularity, bundle tasks, and determine time windows that minimize cost and downtime for each territory. | Planning & Optimization |
| Maintenance Planning Optimization | The use of optimization algorithms and analytics to define optimal maintenance plans, bundle tasks, and determine time windows that minimize cost and downtime. | Planning & Optimization |
| Operational Maintenance Scheduling and Dispatching | Optimal assignment of maintenance tasks to specific technicians, dates, and times with granularity down to the minutes. Integrates with data from external systems, ex. IoT, to provide real time adjustment. | Operational Execution |
| Mean Time Between Failures | A metric used to measure the reliability of an asset. | Core Strategy |
| Operational Planning | Short-term planning focused on the execution of maintenance activities, including daily task assignment, routing, and resource coordination. | Operational Execution |
| Operational Scheduling | The daily assignment of maintenance tasks to technicians, including route optimization and workload balancing. | Operational Execution |
| Outcome-Based Maintenance | Maintenance strategy where the service provider is responsible for achieving agreed performance outcomes (such as uptime, reliability, or cost efficiency), rather than just performing specific maintenance tasks. | Core Strategy |
| Overnight Optimization | Execution of global optimization processes during off-hours to generate an optimal initial schedule for the following operational day. | Operational Execution |
| Planning Horizon | Time period covered by a maintenance or workforce plan. | Planning & Optimization |
| Predictive Maintenance | Maintenance approach based on predicting failures using machine learning algorithms fed with historical and current data, for example IoT data. | Planning & Optimization |
| Preventive Maintenance | Planned and tactically scheduled maintenance activities, typically defined over an annual horizon and executed on a regular or usage-based basis to prevent failures and extend asset lifespan. | Core Strategy |
| Reactive Maintenance | Maintenance performed in response to unexpected failures or breakdowns. | Operational Execution |
| Real-Time Optimization | Dynamic schedule adjustments in response to real-time events. | Operational Execution |
| Service Level Agreement (SLA) | A contractual commitment that defines expected service performance levels, such as uptime, response time, turnaround time, and quality targets. | Core Strategy |
| Smart Activity Bundling | Intelligent grouping of maintenance tasks into a single visit or shutdown based on timing, location, and resource constraints to improve efficiency and reduce downtime. | Planning & Optimization |
| Spare Parts Planning | Forecasting and managing spare parts inventory. | Planning & Optimization |
| Strategic Design | Long-term design decisions related to territory sizing, maintenance policies, workforce structure, and contract strategies. | Core Strategy |
| Strategic Planning | Long-term decisions on asset policies and maintenance strategies. | Core Strategy |
| Tactical Planning | Mid-term planning that translates strategic objectives into actionable plans by forecasting requirements, balancing workloads, and allocating resources efficiently over weeks or months. | Planning & Optimization |
| Task Bundling | Grouping multiple maintenance tasks into a single visit. | Planning & Optimization |
| Strategic Territory Sizing | Optimal design of geographic territories or workload units to distribute expected workloads evenly across maintenance teams | Planning & Optimization |
| Total Cost of Ownership (TCO) | Total lifecycle cost of an asset, including acquisition, operation, and disposal. | Core Strategy |
| Total Life Cost Management | An approach to minimize the total ownership and operating costs of an asset from acquisition to retirement. | Core Strategy |
| Turnaround | The total period during which an asset is unavailable due to maintenance activities, from shutdown to return to service. | Operational Execution |
| Usage Patterns | Historical and real-time data describing how assets are operated, including frequency, intensity, and environmental conditions. | Technology & Data |
| What-If Analysis | Scenario-based analysis used to test and compare alternative planning decisions in order to understand their impact on key performance indicators such as cost, service level, efficiency, and risk. | Technology & Data |
| Work Order | A formal request or authorization that initiates specific maintenance work, including task scope, priority, and required resources. | Operational Execution |
| Workforce Planning | The process of determining optimal workforce size, skills, and locations to meet maintenance demand. | Planning & Optimization |
| Workforce Scheduling | Assignment of employees to tasks, shifts, and routes while respecting constraints. | Operational Execution |
To have these concepts at hand anytime, download the Maintenance Optimization Solutions Cheat Sheet (PDF).
Understanding Maintenance Optimization in the Age of AI
Read our blog post on Maintenance Optimization in the age of AI.
Maintenance Optimization Solutions Cheat Sheet (PDF)
We’ve consolidated everything you need to know about Maintenance Optimization.
DecisionBrain is a leading provider of advanced decision support software that is used to solve the world’s hardest supply chain, workforce and maintenance planning, scheduling & logistics optimization problems. With over 400 person-years of experience in machine learning, operations research and mathematical optimization, DecisionBrain delivers custom-fit decision support systems where packaged applications fall short. Read more about us or contact us to talk about our solutions!
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